NS2-IEEE PROJECTS

ABSTRACT

Network topology tomography can infer a tree topology for single-source networks using end-to-end measurements. However, multipath routing, which introduces multiple paths between end-hosts, violates the tree topology model. In this letter, we demonstrate that such nontree topologies are also identifiable. We employ graph cuts and show the nontree topology can be decomposed into two identifiable subtopologies. And by reconnecting the cut paths, the nontree topology can be recovered after obtaining these subtopologies. To detect the paths that share cuts, we propose a scheme based on measurements of the end-to-end packet arrival order. Simulation results show that our scheme achieves the desirable detection accuracy.

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ABSTRACT

The proliferation of new online Internet services has substantially increased the energy consumption in wired networks, which has become a critical issue for Internet service providers. In this paper, we target the network-wide energy-saving problem by leveraging speed scaling as the energy-saving strategy. We propose a distributed routing scheme–HDEER–to improve network energy efficiency in a distributed manner without significantly compromising traffic delay. HDEER is a two-stage routing scheme where a simple distributed multipath finding algorithm is firstly performed to guarantee loop-free routing, and then a distributed routing algorithm is executed for energy-efficient routing in each node among the multiple loop-free paths. We conduct extensive experiments on the NS3 simulator and simulations with real network topologies in different scales under different traffic scenarios. Experiment results show that HDEER can reduce network energy consumption with a fair tradeoff between network energy consumption and traffic delay.

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ABSTRACT

This paper introduces the mobile access coordinated wireless sensor network (MC-WSN)—a novel energy efficient scheme for time-sensitive applications. In conventional sensor networks with mobile access points (SENMA), the mobile access points (MAs) traverse the network to collect information directly from individual sensors. While simplifying the routing process, a major limitation with SENMA is that data transmission is limited by the physical speed of the MAs and their trajectory length, resulting in low throughput and large delay. In an effort to resolve this problem, we introduce the MC-WSN architecture, for which a major feature is that: through active network deployment and topology design, the number of hops from any sensor to the MA can be limited to a pre-specified number. In this paper, we investigate the optimal topology design that minimizes the average number of hops from sensor to MA, and provide the throughput analysis under both single-path and multipath routing cases. Moreover, putting MC-WSN in the bigger picture of network design and development, we provide a unified framework for wireless network modeling and characterization. Under this general framework, it can be seen that MC-WSN reflects the integration of structure-ensured reliability/efficiency and ad-hoc enabled flexibility.

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ABSTRACT

Existing research on data collection using wireless mobile vehicle network emphasizes the reliable delivery of information. However, other performance requirements such as life cycle of nodes, stability and security are not set as primary design objectives. This makes data collection ability of vehicular nodes in real application environment inferior. By considering the features of nodes in wireless IoV, such as large scales of deployment, volatility and low time delay, an efficient data collection algorithm is proposed for mobile vehicle network environment. An adaptive sensing model is designed to establish vehicular data collection protocol. The protocol adopts group management in model communication. The vehicular sensing node in group can adjust network sensing chain according to sensing distance threshold with surrounding nodes. It will dynamically choose a combination of network sensing chains on basis of remaining energy and location characteristics of surrounding nodes. In addition, secure data collection between sensing nodes is undertaken as well. The simulation and experiments show that the vehicular node can realize secure and real-time data collection. Moreover, the proposed algorithm is superior in vehicular network life cycle, power consumption and reliability of data collection by comparing to other algorithms.

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ABSTRACT

MANET routing protocols are designed based on the assumption that all nodes cooperate without maliciously disrupting the operation of the routing protocol. AODV is a reactive MANET routing protocol that is vulnerable to a dramatic collapse of network performance in the presence of blackhole attack. The paper introduces a new concept of Self-Protocol Trustiness (SPT) in which detecting a malicious intruder is accomplished by complying with the normal protocol behavior and lures the malicious node to give an implicit avowal of its malicious behavior. We present a Blackhole Resisting Mechanism (BRM) to resist such attacks that can be incorporated into any reactive routing protocol. It does not require expensive cryptography or authentication mechanisms, but relies on locally applied timers and thresholds to classify nodes as malicious. No modifications to the packet formats are needed, so the overhead is a small amount of calculation at nodes, and no extra communication. Using NS2 simulation, we compare the performance of networks using AODV under blackhole attacks with and without our mechanism to SAODV, showing that it significantly reduces the effect of a blackhole attack.

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ABSTRACT

Establishing secret common randomness between two or multiple devices in a network resides at the root of communication security. In its most frequent form of key establishment, the problem is traditionally decomposed into a randomness generation stage (randomness purity is subject to employing often costly true random number generators) and an information-exchange agreement stage, which relies either on public-key infrastructure or on symmetric encryption (key wrapping). In this paper, we propose a secret-common-randomness establishment algorithm for ad hoc networks, which works by harvesting randomness directly from the network routing metadata, thus achieving both pure randomness generation and (implicitly) secret-key agreement. Our algorithm relies on the route discovery phase of an ad hoc network employing the dynamic source routing protocol, is lightweight, and requires relatively little communication overhead. The algorithm is evaluated for various network parameters in an OPNET ad hoc network simulator. Our results show that, in just 10 min, thousands of secret random bits can be generated network-wide, between different pairs in a network of 50 users.

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ABSTRACT

This letter considers a single hop wireless multicast network. We first introduce a new two-level queuing system consisting of a main queue and a virtual queue, where each packet in the virtual queue is associated with a user index set. Then, we propose a network coding based packet scheduling method to maximize the system input rate under the queue stability constraint. Our analytical and simulation results demonstrate the effectiveness of the proposed solution.

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ABSTRACT

Multicast transmission based on real-time network state information is a resource-friendly technique to improve the energy efficiency and reduce the traffic burden for cellular systems. This paper evaluates the effectiveness of this technique for downlink transmissions. In particular, a scenario is considered in which multiple mobile users (MUs) asynchronously request to download one common message locally cached at a base station (BS). Due to the randomness of both the channel conditions and the request arrivals from the MUs, the BS may choose to intelligently hold the arrived requests, especially when the channel conditions are bad or the number of requests is small, and then serve them in one shot later via multicasting. Clearly it is of great interest to balance the delay (incurred by holding the requests) and the energy efficiency (EE, defined as the energy cost per request), and this motivates us to quantify the fundamental tradeoff for the proposed “hold-then-serve” scheme. For the scenario with single channel and unit message sizes, it is shown that for a fixed channel bandwidth, the delay-EE tradeoff reduces to judiciously choosing the optimal stopping rule for when to serve all the arrived requests, where the effect of the bandwidth on the achievable delay-EE region is discussed further. By using optimal stopping theory, it is shown that the optimal stopping rule exists for general Markov channel models and request arrival processes. Particularly, for the hard deadline and proportional delay penalty cases, it is shown that the optimal stopping rule exhibits a threshold structure, and the corresponding threshold in the former case is time varying while in the latter case it is a constant. Finally, for the more general scenario with multiple channels and arbitrary message sizes, the optimal scheduling is formulated as a Markov decision process problem, where some efficient suboptimal scheduling algorithms are proposed.

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ABSTRACT

Based on the common interest of mobile users (MUs) in a social group, the dissemination of content across the social group is studied as a powerful supplement to conventional cellular communication with the goal of improving the delay performance of the content dissemination process. The content popularity is modeled by a Zipf distribution to characterize the MUs’ different interests in different contents. The factor of altruism (FA) terminology is introduced for quantifying the willingness of content owners to share their content. We model the dissemination process of a specific packet by a pure-birth-based Markov chain and evaluate the statistical properties of both the network’s dissemination delay as well as of the individual user-delay. Compared to the conventional base station (BS)-aided multicast, our scheme is capable of reducing the average dissemination delay by about 56.5%. Moreover, in contrast to the BS-aided multicast, increasing the number of MUs in the target social group is capable of reducing the average individual user-delay by 44.1% relying on our scheme. Furthermore, our scheme is more suitable for disseminating a popular piece of content.

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ABSTRACT

Although widely used, TCP has many limitations in meeting the throughput and latency requirements of applications in wireless networks, high-speed data center networks, and heterogeneous multi-path networks. Instead of relying purely on retransmission upon packet loss, coding has potential to improve the performance of TCP by ensuring better transmission reliability. Coding has been verified to work well at the link layer but has not been fully studied at the transport layer. There are many advantages but also challenges in exploiting coding at the transport layer. In this article, we focus on how to leverage end-to-end coding in TCP. We reveal the problems TCP faces and the opportunities coding can bring to improve TCP performance. We further analyze the challenges faced when applying the coding techniques to TCP and present the current applications of coding in TCP.

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ABSTRACT

 In this paper, we consider a cascaded radio frequency (RF) and hybrid RF/free space optical (FSO) system where several mobile users transmit their data over an RF link to a decode-and-forward relay node (e.g., a small cell base station) and the relay forwards the information to a destination (e.g., a macro-cell base station) over a hybrid RF/FSO backhaul link. The relay and the destination employ multiple antennas for transmission and reception over the RF links while each mobile user has a single antenna. The RF links are orthogonal to the FSO link but half-duplex with respect to each other, i.e., either the user-relay RF link or the relay-destination RF link is active. For this communication setup, we derive the optimal fixed and adaptive link allocation policies for sharing the transmission time between the RF links based on the statistical and instantaneous channel state information (CSI) of the RF and FSO links, respectively. Thereby, we consider the following two scenarios depending on the delay requirements: 1) delay-limited transmission where the relay has to immediately forward the packets received from the users to the destination, and 2) delay-tolerant transmission where the relay is allowed to store the packets received from the users in its buffer and forward them to the destination when the quality of the relay-destination RF link is favorable. Our numerical results illustrate the effectiveness of the proposed communication architecture and link allocation policies, and their superiority compared to existing schemes, which employ only one type of backhaul link.

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ABSTRACT

 In recent years, as wireless sensor networks (WSNs) are widely diffused, multiple overlapping WSNs constructed on the same area become more common. In such a situation, their lifetime is expected to be extended by cooperative packet forwarding. Although some researchers have studied about cooperation in multiple WSNs, most of them do not consider the heterogeneity in the characteristics of each WSN such as battery capacity, operation start time, the number of nodes, nodes locations, energy consumption, packet size and/or data transmission timing, and so on. In a heterogeneous environment, naive lifetime improvement with cooperation may not be fair. In this paper, we propose a fair cooperative routing method for heterogeneous overlapped WSNs. It introduces an energy pool to maintain the total amount of energy consumption by cooperative forwarding. The energy pool plays a role of broker for fair cooperation. Finally, simulation results show the excellent performance of the proposed method.

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ABSTRACT

 Wireless sensor networks (WSNs) are vulnerable to selective forwarding attacks that can maliciously drop a subset of forwarding packets to degrade network performance and jeopardize the information integrity. Meanwhile, due to the unstable wireless channel in WSNs, the packet loss rate during the communication of sensor nodes may be high and vary from time to time. It poses a great challenge to distinguish the malicious drop and normal packet loss. In this paper, we propose a channel-aware reputation system with adaptive detection threshold (CRS-A) to detect selective forwarding attacks in WSNs. The CRS-A evaluates the data forwarding behaviors of sensor nodes, according to the deviation of the monitored packet loss and the estimated normal loss. To optimize the detection accuracy of CRS-A, we theoretically derive the optimal threshold for forwarding evaluation, which is adaptive to the time-varied channel condition and the estimated attack probabilities of compromised nodes. Furthermore, an attack-tolerant data forwarding scheme is developed to collaborate with CRS-A for stimulating the forwarding cooperation of compromised nodes and improving the data delivery ratio of the network. Extensive simulation results demonstrate that CRS-A can accurately detect selective forwarding attacks and identify the compromised sensor nodes, while the attack-tolerant data forwarding scheme can significantly improve the data delivery ratio of the network.

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ABSTRACT

 Policy and path updates are common causes of network instability, leading to service disruptions or vulnerable intermediate states. In this letter, we propose the reverse update, an update scheme for software-defined networking that guarantees to preserve properties of flows during the transition time. We prove through a formal model that the proposal achieves consistent policy updates, in which in-transit packets are always handled in the next forwarding hops by the same or a more recent policy. The main contributions are: 1) a relaxation of the concept of per-packet-consistency in the data plane of software-defined networking; and 2) a policy update scheme, proved to be consistent and efficient. A software-defined networking simulator was developed and validated. The results of our simulations show that the proposed reverse update scheme is faster and has lower overhead than the current two-phase update proposed in the literature.

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ABSTRACT

 We study the scaling properties of a georouting scheme in a wireless multi-hop network of  n mobile nodes. Our aim is to increase the network capacity quasi-linearly with  n , while keeping the average delay bounded. In our model, we consider mobile nodes moving according to an independent identically distributed random walk with velocity  v and transmitting packets to randomly chosen fixed and known destinations. The average packet delivery delay of our scheme is of order  1/v , and it achieves network capacity of order  ({n}/{\log n\log \log n}) . This shows a practical throughput-delay tradeoff, in particular when compared with the seminal result of Gupta and Kumar, which shows network capacity of order {(n/\log n)}^{1/2} and negligible delay and the groundbreaking result of Grossglauser and Tse, which achieves network capacity of order  n but with an average delay of order  \sqrt {n}/v . The foundation of our improved capacity and delay tradeoff relies on the fact that we use a mobility model that contains straight-line segments, a model that we consider more realistic than classic Brownian motions. We confirm the generality of our analytical results using simulations under various interference models.

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ABSTRACT

A Mobile Ad hoc NETwork (MANET) is a collection of autonomous nodes that have the ability to communicate with each other without having fixed infrastructure or centralized access point such as a base station. This kind of networks is very susceptible to adversary’s malicious attacks, due to the dynamic changes of the network topology, trusting the nodes to each other, lack of fixed substructure for the analysis of nodes behaviors and constrained resources. One of these attacks is black hole attack. In this attack, malicious nodes inject fault routing information to the network and lead all data packets toward themselves, then destroy them all. In this paper, we propose a solution, which enhances the security of the Ad-hoc On-demand Distance Vector (AODV) routing protocol to encounter the black hole attacks. Our solution avoids the black hole and the multiple black hole attacks. The simulation results using the Network Simulator NS2 shows that our protocol provides better security and better performance in terms of the packet delivery ratio than the AODV routing protocol in the presence of one or multiple black hole attacks with marginal rise in average end-to-end delay and normalized routing overhead.

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ABSTRACT

 Tree networks are widely applied in Sensor Networks of Internet of Things (IoTs). This paper proposes an Efficient Tree-based Self-organizing Protocol (ETSP) for sensor networks of IoTs. In ETSP, all nodes are divided into two kinds: network nodes and non-network nodes. Network nodes can broadcast packets to their neighboring nodes. Non-network nodes collect the broadcasted packets and determine whether to join the network. During the self-organizing process, we use different metrics such as number of child nodes, hop, communication distance and residual energy to reach available sink nodes’ weight, the node with max weight will be selected as sink node. Non-network nodes can be turned into network nodes when they join the network successfully. Then a tree-based network can be obtained one layer by one layer. The topology is adjusted dynamically to balance energy consumption and prolong network lifetime. We conduct experiments with NS2 to evaluate ETSP. Simulation results show that our proposed protocol can construct a reliable tree-based network quickly. With the network scale increasing, the self-organization time, average hop and packet loss ratio won’t increase more. Furthermore, the success rate of packet in ETSP is much higher compared with AODV and DSDV.

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ABSTRACT

 MANET routing protocols are designed based on the assumption that all nodes cooperate without maliciously disrupting the operation of the routing protocol. AODV is a reactive MANET routing protocol that is vulnerable to a dramatic collapse of network performance in the presence of blackhole attack. The paper introduces a new concept of Self-Protocol Trustiness (SPT) in which detecting a malicious intruder is accomplished by complying with the normal protocol behavior and lures the malicious node to give an implicit avowal of its malicious behavior. We present a Blackhole Resisting Mechanism (BRM) to resist such attacks that can be incorporated into any reactive routing protocol. It does not require expensive cryptography or authentication mechanisms, but relies on locally applied timers and thresholds to classify nodes as malicious. No modifications to the packet formats are needed, so the overhead is a small amount of calculation at nodes, and no extra communication. Using NS2 simulation, we compare the performance of networks using AODV under blackhole attacks with and without our mechanism to SAODV, showing that it significantly reduces the effect of a blackhole attack

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ABSTRACT

 Secure data collection is an important problem in wireless sensor networks. Different approaches have been proposed. One of them is overhearing. We investigate the problem of constructing a shortest path overhearing tree with the maximum lifetime. We propose three approaches. The first one is a polynomial-time heuristic. The second one uses ILP (Integer Linear Programming) to iteratively find a monitoring node and a parent for each sensor node. The last one optimally solves the problem by using MINLP (Mixed-Integer Non-Linear Programming). We have implemented the three approaches using MIDACO solver and MATLAB Intlinprog, and performed extensive simulations using NS2.35. The simulation results show that the average lifetime of all the network instances achieved by the heuristic approach is 85.69% of that achieved by the ILP-based approach and 81.05% of that obtained by the MINLP-based approach, and the performance of the ILP-based approach is almost equivalent to that of the MINLP-based approach.

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ABSTRACT

 Flooding is the simplest way of broadcasting, in which each node in the network retransmits an incoming message once. Simple flooding technique in wireless Ad-hoc networks causes the broadcast storm problem. However, this technique is inefficient in terms of resource consumption such as bandwidth and energy. This paper presents a new hybrid scheme that combines different techniques that collaborate to reduce overhead and conserve energy. We propose an Energy-Efficient Adaptive Forwarding Scheme, that utilizes the information of the 1-hop neighbouring radios. In this scheme nodes do not need a positioning system or distance calculation to determine their location. In addition to the previous works, the proposed protocol divides the network into different groups based on their transmission-power levels. Therefore, the node which receives HELLO message from different groups is considered a Gateway node. This node efficiently participates in forwarding RREQ packets and the unnecessary redundant retransmission is avoided. The performance evaluation of the proposed protocol shows a reduction in the routing overhead and in energy consumption, when compared with the Pure-Flooding AODV and Dynamic-Power AODV using NS2

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ABSTRACT

 A mobile ad hoc network (MANET) is a collectionof wireless nodes, which works well only if those mobile nodes aregood and behave cooperatively. The lack of infrastructuresupport and resource constraint is the key issue that causesdishonest and non-co-operative nodes. Therefore, MANET isvulnerable to serious attacks. To reduce the hazards from suchnodes and enhance the security of the network, this paperextends an Ad hoc On-Demand Multipath Distance Vector(AOMDV) Routing protocol, named as Trust-based Secured Adhoc On-demand Multipath Distance Vector (TS-AOMDV), whichis based on the nodes’ routing behavior. The proposed TSAOMDVaims at identifying and isolating the attacks such asflooding, black hole, and gray hole attacks in MANET. With thehelp of Intrusion Detection System (IDS) and trust-based routing, attack identification and isolation are carried out in two phases ofrouting such as route discovery and data forwarding phase. IDSfacilitates complete routing security by observing both controlpackets and data packets that are involved in the routeidentification and the data forwarding phases. To improve therouting performance, the IDS integrates the measured statisticsinto the AOMDV routing protocol for the detection of attackers. This facilitates the TS-AOMDV to provide better routingperformance and security in MANET. Finally, the Trust basedSecured AOMDV, TS-AOMDV is compared with the existingAOMDV through the NS2 based simulation model. Theperformance evaluation reveals that the proposed TS-AOMDVimproves the performance in terms of throughput by 57.1%more than that of an AOMDV under adversary scenario. Thesimulated results show that the TS-AOMDV outperforms theAOMDV routing protocol.

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ABSTRACT

With the developing understanding of Information Security and digital assets, IT technology has put on tremendous importance of network admission control (NAC). In NAC architecture, admission decisions and resource reservations are taken at edge devices, rather than resources or individual routers within the network. The NAC architecture enables resilient resource reservation, maintaining reservations even after failures and intra-domain rerouting. Admission Control Networks destiny is based on IP networks through its Security and Quality of Service (QoS) demands for real time multimedia application via advance resource reservation techniques. To achieve Security & QoS demands, in real time performance networks, admission control algorithm decides whether the new traffic flow can be admitted to the network or not. Secure allocation of Peer for multimedia traffic flows with required performance is a great challenge in resource reservation schemes. In this paper, we have proposed our model for VoIP networks in order to achieve security services along with QoS, where admission control decisions are taken place at edge routers. We have analyzed and argued that the measurement based admission control should be done at edge routers which employs on-demand probing parallel from both edge routers to secure the source and destination nodes respectively. In order to achieve Security and QoS for a new call, we choose various probe packet sizes for voice and video calls respectively. Similarly a technique is adopted to attain a security allocation approach for selecting an admission control threshold by proposing our admission control algorithm. All results are tested on NS2 based simulation to evalualate the network performance of edge router based upon network admission control in VoIP traffic

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ABSTRACT

 In Mobile Ad-hoc NETwork (MANET) each node has the possibility to move freely in the space and communicate with each other over wireless link without any centralized controller or base station. These characteristics makes MANET useful and practical in several fields like military scenarios, sensor networks, Rescue operations, students on campus, etc. but this kind of network still suffers from a number of problems, power consumption is one of the most crucial design concerns in Mobile Ad-hoc networks as the nodes in MANET have battery limited. In this paper, we will discuss about the aspect of energy consumption in MANET’s routing protocols. A performance comparison of four routing protocols Dynamic Source Routing (DSR), Ad hoc On-Demand Distance Vector (AODV), Destination-Sequenced Distance Vector (DSDV) and Optimized Link State Routing (OLSR) with respect to average energy consumption are explained thoroughly. Then, an evaluation of how the varying parameters of network in diverse scenarios affect the power consumption in these four protocols is discussed. A detailed simulation model using Network Simulator 2 (NS2) with different mobility and traffic models is used to study their energy consumption.

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ABSTRACT

Mobile devices play an integral role in our day lives and have brought the revolutionary change in business, education, and entertainment. Moreover, the emergence of cloud computing technology greatly extended the significance of smart device. On the other hand, the smart devices experience the problem when obtaining the multiple cloud services during the handoff process. In this paper, we propose an energy detection (ED) analytical model for handoff process that calculates the energy consumption for each handoff process in the cloud computing environment. Our ED analytic model is developed to examine the consumed energy for different handoff processes in cloud computing. The model helps the mobile users to get prior information for the status of the mobile when executing the handoff process. To reconfirm the validity of ED analytical model, we have test programmed in NS2. The results demonstrate that the ED analytical model efficiently detects the energy consumption of mobile devices during the handoff process in cloud computing environment.

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ABSTRACT

A study of the application of nonconvex regularization operators to the electromagnetic sounding inverse problem is presented. A comparison is presented among three nonconvex regularization algorithms: one smooth usually considered, two nonsmooth, and a convex one, the total variation (TV) operator. One of the nonsmooth nonconvex regularization methods is a novel implementation based on the Legendre–Fenchel transform and the Bregman iterative algorithm. The nonconvex regularization operator is approximated by the convex dual, and the minimization is then implemented considering the equivalence between the Bregman iteration and the augmented Lagrangian methods. The algorithm is simple and provides for better models when applied to synthetic data, than those obtained with TV, and other nonconvex smooth regularizers. Results of the application to field data are also presented, observing that NS2 recovers a model in better agreement with the truth, compared to those obtained with additional magnetometric resistivity data by other researchers

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ABSTRACT

Nowadays Wireless Sensor Networks have attracted worldwide research and industrial interest, because they can be applied in various areas. Geographic routing protocols are very suitable to wireless sensor networks because they use location information when they need to route packets. Obviously, location information is maintained by Location-Based Services provided by network nodes in a distributed way. The location based services can be classified into two classes: Flooding-Based and Rendezvous-based location services.In this paper we choose to compare two hierarchical rendezvous location based-services, GLS (Grid Location Service) and HLS (Hierarchical Location Service) coupled to the GPSR routing protocol (Greedy Perimeter Stateless Routing).The simulations were performed using NS2 simulator for wireless sensor networks to evaluate the performance and power of the two services in term of location overhead, the request travel time (RTT) and the query Success ratio (QSR).This work presents also the scalability performance study of both GLS and HLS, specifically, what happens if the number of nodes N increases. The study will focus on three qualitative metrics: The location maintenance cost,the location query cost and the storage cost.

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ABSTRACT

 A Mobile Ad hoc NETwork (MANET) is a collection of autonomous nodes that have the ability to communicate with each other without having fixed infrastructure or centralized access point such as a base station. This kind of networks is very susceptible to adversary’s malicious attacks, due to the dynamic changes of the network topology, trusting the nodes to each other, lack of fixed substructure for the analysis of nodes behaviors and constrained resources. One of these attacks is black hole attack. In this attack, malicious nodes inject fault routing information to the network and lead all data packets toward themselves, then destroy them all. In this paper, we propose a solution, which enhances the security of the Ad-hoc On-demand Distance Vector (AODV) routing protocol to encounter the black hole attacks. Our solution avoids the black hole and the multiple black hole attacks. The simulation results using the Network Simulator NS2 shows that our protocol provides better security and better performance in terms of the packet delivery ratio than the AODV routing protocol in the presence of one or multiple black hole attacks with marginal rise in average end-to-end delay and normalized routing overhead.

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ABSTRACT

A Mobile Ad hoc NETwork (MANET) is much more vulnerable to attack than a wired network due to the dynamic changes of the network topology, high mobility, limited physical security and lack of centralized administration. Unfortunately, the routing protocols are designed based on the assumption that all nodes trust each other and cooperate without maliciously disrupting the operation of routing. This paper analyzes the impact of security attacks on the performance of the AODV routing protocol. Simulations are setup in the NS-2 network simulator and the performance of the AODV routing protocol is discussed under black hole, flooding and rushing attacks. This analysis is provided in terms of performance metrics, such as a packet delivery ratio, the average end-to-end delay and normalized routing load.

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ABSTRACT

Today’s generation has perceived wireless networking prospective applications in tremendously erratic and vibrant surroundings. Businesses as well as individuals pick wireless medium as their choice as it facilitates flexibility of location. It’s obvious due to its convenience in terms of mobility, portability or even ease of installation at any preferred location. Mobile network has an intrinsic scalability restraint in terms of attainable network capability. The potential challenge of wireless communication in Smart cities network is, the environs that these communications travel through is changeable. So, the wireless networks which have ability to resolve their own fragmented communication links will definitely enhance their pervasive recognition. Due to the expansion of network capability changes are made to the network design and infrastructures giving way to new techniques for system development for this type of medium. Since it’s the beginning there are initial hiccups, despite that, the modern advances in self-healing wireless networks are good enough in resolving the problem. The downlinks are repaired by using power conscious steady nodes. Authors have proposed, a self-healing structure and mobile Power aware stable nodes for smart city networks. Proposed design has been checked using NS2 simulator with existing schemes and show good results in most of the cases.

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ABSTRACT

 In this paper, we consider random access, wireless, multi-hop networks, with multi-packet reception capabilities, where multiple flows are forwarded to the gateways through node disjoint paths. We explore the issue of allocating flow on multiple paths, exhibiting both intra- and inter-path interference, in order to maximize average aggregate flow throughput (AAT) and also provide bounded packet delay. A distributed flow allocation scheme is proposed where allocation of flow on paths is formulated as an optimization problem. Through an illustrative topology it is shown that the corresponding problem is non-convex. Furthermore, a simple, but accurate model is employed for the average aggregate throughput achieved by all flows, that captures both intra- and inter-path interference through the SINR model. The proposed scheme is evaluated through Ns2 simulations of several random wireless scenarios. Simulation results reveal that, the model employed, accurately captures the AAT observed in the simulated scenarios, even when the assumption of saturated queues is removed. Simulation results also show that the proposed scheme achieves significantly higher AAT, for the vast majority of the wireless scenarios explored, than the following flow allocation schemes: one that assigns flows on paths on a round-robin fashion, one that optimally utilizes the best path only, and another one that assigns the maximum possible flow on each path. Finally, a variant of the proposed scheme is explored, where interference for each link is approximated by considering its dominant interfering nodes only.

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ABSTRACT

Wireless Sensor Communication Networks have more concern on its routing techniques. Since the WSCNs nodes are battery powered, routing algorithms should assure the concept of energy saving without affecting the other performance metric like Throughput, Delay and Packet delivery ratio etc. The modified AOMDV called as Enhanced Energy Efficient Multipath Routing Protocol (EEEMRP) is a proposed algorithm with the concept of crossbreed the AOMDV routing with the Cuckoo Search algorithm. In this paper, we compare the QoS parameters such as Throughput, Average Delay and Packet Delivery ratio with Traditional Flat Routing Protocols such as DSR, DSDV and with AODV. Simulation is performed using NS2 and the results show that the proposed EEEMRP routing protocol is better than DSR, DSDV and AODV.

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ABSTRACT

Wireless Sensor Network (WSN) are of paramount significance since they are responsible for maintaining the routes in the network, data forwarding, and ensuring reliable multi-hop communication. The main requirement of a wireless sensor network is to prolong network energy efficiency and lifetime. Researchers have developed protocols Low Energy Adaptive Clustering Hierarchy (LEACH) and Power-Efficient Gathering in Sensor Information Systems (PEGASIS) for reducing energy consumption in the network. However, the existing routing protocols experience many shortcomings with respect to energy and power consumption. LEACH features the dynamicity but has limitations due to its cluster-based architecture, while PEGASIS overcomes the limitations of LEACH but lacks dynamicity. In this paper, we introduce PEGASIS-LEACH (P-LEACH), a near optimal cluster-based chain protocol that is an improvement over PEGASIS and LEACH both. This protocol uses an energy-efficient routing algorithm to transfer the data in WSN. To validate the energy effectiveness of P-LEACH, we simulate the performance using Network Simulator (NS2) and MATLAB.

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ABSTRACT

In this paper, We propose a novel framework to improve the end-to-end transmission delay (E2ETD) and packet delivery ratio (PDR) of existing contention based synchronous MAC protocols designed for wireless sensor networks, without increasing the duty cycle (DC). This is achieved by partitioning the n deployed sensor nodes into k disjoint sets (DSs) which are of almost equal size. It then suitably modifies the cycle structure followed by the existing contention based synchronous MAC protocols by mapping the data transmission process of k existing cycles into one restructured cycle. To evaluate the performance of this approach, we implement RMAC, PRMAC, and CLMAC protocols in the proposed framework using ns2.35 simulator. Results indicate that our scalable framework reduces the E2ETD and increases the PDR significantly at the cost of a very small increase in average energy consumption.

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ABSTRACT

 Devices in wireless mesh networks can operate on multiple channels and automatically adjust their transmission rates for the occupied channels. This paper shows how to improve performance-guaranteed multicasting transmission coverage for wireless multi-hop mesh networks by exploring the transmission opportunity offered by multiple rates (MR) and multiple channels (MC). Based on the characteristics of transmissions with different rates, we propose and analyze parallel low-rate transmissions (PLT) and alternative rate transmissions (ART) to explore the advantages of MRMC in improving the performance and coverage tradeoff under the constraint of limited channel resources. We then apply these new transmission schemes to improving the WMN multicast experience. Combined with the strategy of reliable interference-controlled connections, a novel MRMC multicast algorithm (LC-MRMC) is designed to make efficient use of channel and rate resources to greatly extend wireless multicast coverage with high throughput and short delay performance. Our NS2 simulation results prove that ART and LC-MRMC achieve improved wireless transmission quality across much larger areas as compared to other related studies.

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ABSTRACT

This work develops an equilibrium model for finding the optimal distribution strategy to maximize performance of key predistribution protocols in terms of cost, resilience, connectivity, and lifetime. As an essential attribute of wireless sensor networks, heterogeneity and its impacts on random key predistribution protocols are first discussed. Using supernetworks theory, the optimal node deployment model is proposed and illustrated. In order to find the equilibrium performance of our model, all optimal performance functions are changed into variational inequalities so that this optimization problem can be solved. A small-scale example is presented to illustrate the applicability of our model.

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In this paper, we propose a novel low-cost localization algorithm tailored for multihop heterogeneous wireless sensor networks (HWSNs) where nodes’ transmission capabilities are different. This characteristic, if not taken into account when designing the localization algorithm, may severely hinder its accuracy. Assuming different nodes’ transmission capabilities, we develop two different approaches to derive the expected hop progress (EHP). Exploiting the latter, we propose a localization algorithm that is able to accurately locate the sensor nodes owing to a new low-cost implementation. Furthermore, we develop a correction mechanism, which complies with the heterogeneous nature of wireless sensor networks (WSNs) to further improve localization accuracy without incurring any additional costs. Simulations results show that the proposed algorithm, whether applied with or without correction, outperforms in accuracy the most representative WSN localization algorithms.

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This letter proposes a novel data gathering scheme for wireless sensor networks (WSNs) that limits the energy expenditure, and hence, prolongs network lifetime. Data gathering is modeled as an auction where a node broadcasts its own result only if it is higher than the maximum already-broadcasted result by other nodes. For a WSN of 100 nodes, the mathematical and simulation results show that the proposed scheme can save up to 70% of the energy consumption with <;1% performance loss, compared with the conventional scheme.

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In this paper, we consider a compressive sleeping wireless sensor network (WSN) for monitoring parameters in the sensor field, where only a fraction of sensor nodes (SNs) are activated to perform the sensing task and their data are gathered at a fusion center (FC) to estimate all the other SNs’ data using the compressive sensing (CS) principle. Typically, research published concerning CS implicitly assume the sampling costs for all samples are equal and suggest random sampling as an appropriate approach to achieve good reconstruction accuracy. However, this assumption does not hold for compressive sleeping WSNs, which have significant variability in sampling cost owing to the different physical conditions at particular SNs. To exploit this sampling cost nonuniformity, we propose a cost-aware activity scheduling approach that minimizes the sampling cost with constraints on the regularized mutual coherence of the equivalent sensing matrix. In addition, for the case with prior information about the signal support, we extend the proposed approach to incorporate the prior information by considering an additional constraint on the mean square error (MSE) of the oracle estimator for sparse recovery. Our numerical experiments demonstrate that, in comparison with other designs in the literature, the proposed activity scheduling approaches lead to improved tradeoffs between reconstruction accuracy and sampling cost for compressive sleeping WSNs.

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A Wireless Sensor Network (WSN) is a distributed set of sensors deployed to work together for collective sensing and possible data processing. A WSN can be used to monitor environmental behavior and structural integrity in a variety of application fields, thus becoming an integral part of the consumer electronics of smart buildings in smart cities. Due to ever-increasing population growth, along with limited natural resources, smart cities are expected to be the wave of the future. For instance, WSNs are widely used in industrial settings with machine monitoring and play an important role in monitoring the structural integrity of large buildings and bridges. This article focuses on existing WSN simulation frameworks that could be integrated with realtime hardware prototypes. We analyze and compare various such simulation frameworks, and we determine a suitable simulation environment that supports specific software packages.

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Key predistribution schemes accommodate secure connectivity by establishing pairwise keys between nodes. However, ensuring security for all communication links of a wireless sensor network (WSN) is nontrivial due to the memory limitations of the nodes. If some of the links are not available due to the lack of a primary security association between the transmitter and the receiver, nodes can still send their data to the base station but probably not via the best route that maximizes the network lifetime. In this study, we propose a linear programming framework to explore the incomplete secure connectivity problem with respect to its impact on network lifetime, path length, queue size, and energy dissipation. The numerical results show that if any two nodes share a key with a probability of at least 0.3, then we should expect only a marginal drop (i.e., less than 3.0%) in lifetime as compared to a fully connected network.

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Airborne relaying can extend wireless sensor networks (WSNs) to remote human-unfriendly terrains. However, lossy airborne channels and limited battery of unmanned aerial vehicles (UAVs) are critical issues, adversely affecting success rate and network lifetime, especially in real-time applications. We propose an energy-efficient cooperative relaying scheme which extends network lifetime while guaranteeing the success rate. The optimal transmission schedule of the UAVs is formulated to minimize the maximum (min-max) energy consumption under guaranteed bit error rates, and can be judiciously reformulated and solved using standard optimisation techniques. We also propose a computationally efficient suboptimal algorithm to reduce the scheduling complexity, where energy balancing and rate adaptation are decoupled and carried out in a recursive alternating manner. Simulation results confirm that the suboptimal algorithm cuts off the complexity by orders of magnitude with marginal loss of the optimal network yield (throughput) and lifetime. The proposed suboptimal algorithm can also save energy by 50 percent, increase network yield by 15 percent, and extend network lifetime by 33 percent, compared to the prior art.

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Wireless sensor network (WSN) brings a new paradigm of real-time embedded systems with limited computation, communication, memory, and energy resources that are being used for huge range of applications where the traditional infrastructure-based network is mostly infeasible. The sensor nodes are densely deployed in a hostile environment to monitor, detect, and analyze the physical phenomenon and consume considerable amount of energy while transmitting the information. It is impractical and sometimes impossible to replace the battery and to maintain longer network life time. So, there is a limitation on the lifetime of the battery power and energy conservation is a challenging issue. Appropriate cluster head (CH) election is one such issue, which can reduce the energy consumption dramatically. Low energy adaptive clustering hierarchy (LEACH) is the most famous hierarchical routing protocol, where the CH is elected in rotation basis based on a probabilistic threshold value and only CHs are allowed to send the information to the base station (BS). But in this approach, a super-CH (SCH) is elected among the CHs who can only send the information to the mobile BS by choosing suitable fuzzy descriptors, such as remaining battery power, mobility of BS, and centrality of the clusters. Fuzzy inference engine (Mamdani’s rule) is used to elect the chance to be the SCH. The results have been derived from NS-2 simulator and show that the proposed protocol performs better than the LEACH protocol in terms of the first node dies, half node alive, better stability, and better lifetime.

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Reducing energy consumption of wireless sensor nodes extends battery life and / or enables the use of energy harvesting and thus makes feasible many applications that might otherwise be impossible, too costly or require constant maintenance. However, theoretical approaches proposed to date that minimise WSN energy needs generally lead to less than expected savings in practice. We examine experiences of tuning the energy profile for two near-production wireless sensor systems and demonstrate the need for (a) microbenchmark-based energy consumption profiling, (b) examining start-up costs, and (c) monitoring the nodes during long-term deployments. The tuning exercise resulted in reductions in energy consumption of a) 93% for a multihop Telos-based system (average power 0.029 mW) b) 94.7% for a single hop Ti- 8051-based system during startup, and c) 39% for a Ti- 8051 system post start-up. The work reported shows that reducing the energy consumption of a node requires a whole system view, not just measurement of a “typical” sensing cycle. We give both generic lessons and specific application examples that provide guidance for practical WSN design and deployment.

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This paper studies the intercept behavior of an industrial wireless sensor network (WSN) consisting of a sink node and multiple sensors in the presence of an eavesdropping attacker, where the sensors transmit their sensed information to the sink node through wireless links. Due to the broadcast nature of radio wave propagation, the wireless transmission from the sensors to the sink can be readily overheard by the eavesdropper for interception purposes. In an information-theoretic sense, the secrecy capacity of the wireless transmission is the difference between the channel capacity of the main link (from sensor to sink) and that of the wiretap link (from sensor to eavesdropper). If the secrecy capacity becomes nonpositive due to the wireless fading effect, the sensor’s data transmission could be successfully intercepted by the eavesdropper and an intercept event occurs in this case. However, in industrial environments, the presence of machinery obstacles, metallic frictions, and engine vibrations makes the wireless fading fluctuate drastically, resulting in the degradation of the secrecy capacity. As a consequence, an optimal sensor scheduling scheme is proposed in this paper to protect the legitimate wireless transmission against the eavesdropping attack, where a sensor with the highest secrecy capacity is scheduled to transmit its sensed information to the sink. Closed-form expressions of the probability of occurrence of an intercept event (called intercept probability) are derived for the conventional round-robin scheduling and the proposed optimal scheduling schemes. Also, an asymptotic intercept probability analysis is conducted to provide an insight into the impact of the sensor scheduling on the wireless security. Numerical results demonstrate that the proposed sensor scheduling scheme outperforms the conventional round-robin scheduling in terms of the intercept probability.

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This paper is concerned with developing a distributed k-means algorithm and a distributed fuzzy c-means algorithm for wireless sensor networks (WSNs) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multiagent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is first proposed to find the initial centroids before executing the distributed k-means algorithm and the distributed fuzzy c-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances, while the proposed distributed fuzzy c-means algorithm is capable of partitioning the data observed by the nodes into different measure-dependent groups with degrees of membership values ranging from 0 to 1. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that given by the centralized clustering algorithms.

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Energy harvesting (EH) has been proposed as a promising technology to extend the lifetime of wireless sensor networks (WSNs) by continuously harvesting green/renewable energy. However, the intermittent and random EH process as well as the complexity in achieving global network information call for efficient energy management and distributed resource optimization. Considering the complex interactions among individual sensors, we use the game theory to perform distributed optimization for the general multi-channel multi-access problem in an EH-WSN, where strict delay constraints are imposed for the data transmission. Sensors’ competition for channel access is formulated as a non-cooperative game, which is proved to be an ordinal potential game that has at least one Nash equilibrium (NE). Furthermore, all the NE of the game is proved to be Pareto optimal, and Jain’s fairness index bound of the NE is theoretically derived. Finally, we design a fully distributed, online learning algorithm for the multi-channel multi-access in the EH-WSN, which is proved to converge to the NE of the formulated game. Simulation results validate the effectiveness of the proposed algorithm.

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This paper introduces two main contributions to the wireless sensor network (WSN) society. The first one consists of modeling the relationship between the distances separating sensors and the received signal strength indicators (RSSIs) exchanged by these sensors in an indoor WSN. In this context, two models are determined using a radio-fingerprints database and kernel-based learning methods. The first one is a non-parametric regression model, while the second one is a semi-parametric regression model that combines the well-known log-distance theoretical propagation model with a non-linear fluctuation term. As for the second contribution, it consists of tracking a moving target in the network using the estimated RSSI/distance models. The target’s position is estimated by combining acceleration information and the estimated distances separating the target from sensors having known positions, using either the Kalman filter or the particle filter. A fully comprehensive study of the choice of parameters of the proposed distance models and their performances is provided, as well as a study of the performance of the two proposed tracking methods. Comparisons with recently proposed methods are also provided.

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Coverage is an important issue that has been widely discussed in wireless sensor networks (WSNs). However, it is still a big challenge to achieve both purposes of full coverage and energy balance. This paper considers the area coverage problem for a WSN where each sensor has variable sensing radius. To prolong the network lifetime, a weighted Voronoi diagram (WVD) is proposed as a tool for determining the responsible sensing region of each sensor according to the remaining energy in a distributed manner. The proposed mechanism, called SRA, mainly consists of three phases. In the first phase, each sensor and its neighboring nodes cooperatively construct the WVD for identifying the responsible monitoring area. In the second phase, each sensor adjusts its sensing radius to reduce the overlapping sensing region such that the purpose of energy conservation can be achieved. In the last phase, the sensor with the least remaining energy further adjusts its sensing radius with its neighbor for maximizing the network lifetime. Performance evaluation and analysis reveal that the proposed SRA mechanism outperforms the existing studies in terms of the network lifetime and the degree of energy balance.

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The integration between data collection methods in wireless sensor networks (WSNs) and compressive sensing (CS) provides energy efficient paradigms. Single-dimensional CS approaches are inapplicable in spatial and temporal correlated WSNs while the Kronecker compressive sensing (KCS) model suffers performance degradation along with the increasing data dimensions. In this letter, a neighbor-aided compressive sensing (NACS) scheme is proposed for efficient data gathering in spatial and temporal correlated WSNs. During every sensing period, the sensor node just sends the raw readings within the sensing period to a randomly and uniquely selected neighbor. Then, the CS measurements created by the neighbor are sent to the sink node directly. The equivalent sensing matrix is proved to satisfy both structured random matrix (SRM) and generalized KCS models. And, by introducing the idea of SRM to KCS, the recovery performance of KCS is significantly improved. Simulation results demonstrate that compared with the conventional KCS models, the proposed NACS model can achieve vastly superior recovery performance and receptions with much fewer transmissions

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Supercapacitors (SCs) have been used in energy harvesting wireless sensor networks (WSNs) to relieve the life cycle limitations that most traditional rechargeable storage devices suffer from. SC-operated WSNs present new challenges for power management due to its high self-discharge and charge redistribution. Power management algorithms have been developed to reduce self-discharge loss, but few studies have focused on charge redistribution loss in SC-operated WSNs. In this paper, we investigate how SC charge redistribution affects power management in long-term WSN applications, and develop a practical power manager to reduce redistribution loss by scheduling the workload in a way that maintains a relatively balanced voltage between the main branch and the delayed branch of an SC. The manager has low computational complexity and yields considerably smaller charge redistribution loss than other power managers

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Localization of the hazardous gas source plays an important role in the protection of public security, since it can save a lot of time for subsequent rescue works. For gas source localization (GSL), a large number of gas sensor nodes can be rapidly deployed to construct a wireless sensor network (WSN) and cover the whole concerned area. Although least-squares (LS) methods can solve the problem of GSL in WSNs regardless of the distribution of measurement noises, centralized LS methods are not power efficient and robust since they require the gathering and processing of large-scale measurements on a central node. In this paper, we propose a novel distributed method for GSL in WSNs, which is performed on a sequence of sensor nodes successively. Each sensor node in the sequence conducts an individual estimation and a convex combination. The individual estimation is inspired by the LS formulation of the problem of GSL in WSNs. The proposed method is fully distributed and computationally efficient, and it does not rely on the absolute location of the sensor nodes. Extensive simulation results and a set of experimental results demonstrate that the success rate and localization accuracy of the proposed method are generally higher than those of the trust-region-reflective method.

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RF-enabled wireless power transfer and energy harvesting has recently emerged as a promising technique to provision perpetual energy replenishment for low-power wireless networks. The network devices are replenished by the RF energy harvested from the transmission of ambient RF transmitters, which offers a practical and promising solution to enable self-sustainable communications. This paper adopts a stochastic geometry framework based on the Ginibre model to analyze the performance of self-sustainable communications over cellular networks with general fading channels. Specifically, we consider the point-to-point downlink transmission between an access point and a battery-free device in the cellular networks, where the ambient RF transmitters are randomly distributed following a repulsive point process, called Ginibre α-determinantal point process (DPP). Two practical RF energy harvesting receiver architectures, namely time-switching and power-splitting, are investigated. We perform an analytical study on the RF-powered device and derive the expectation of the RF energy harvesting rate, the energy outage probability and the transmission outage probability over Nakagami-m fading channels. These are expressed in terms of so-called Fredholm determinants, which we compute efficiently with modern techniques from numerical analysis. Our analytical results are corroborated by the numerical simulations, and the efficiency of our approximations is demonstrated. In practice, the accurate simulation of any of the Fredholm determinant appearing in the manuscript is a matter of seconds. An interesting finding is that a smaller value of α (corresponding to larger repulsion) yields a better transmission outage performance when the density of the ambient RF transmitters is small. However, it yields a lower transmission outage probability when the density of the ambient RF transmitters is large. We also show analytically that the power-splitting architecture outperfor- s the time-switching architecture in terms of transmission outage performances. Lastly, our analysis provides guidelines for setting the time-switching and power-splitting coefficients at their optimal values.

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Internet of Things (IoT) devices can be equipped with multiple heterogeneous network interfaces. An overwhelmingly large amount of services may demand some or all of these interfaces’ available resources. Herein, we present a precise mathematical formulation of assigning services to interfaces with heterogeneous resources in one or more rounds. For reasonable instance sizes, the presented formulation produces optimal solutions for this computationally hard problem. We prove the NP-Completeness of the problem and develop two algorithms to approximate the optimal solution for big instance sizes. The first algorithm allocates the most demanding service requirements first, considering the average cost of interfaces resources. The second one calculates the demanding resource shares and allocates the most demanding of them first by choosing randomly among equally demanding shares. Finally, we provide simulation results giving insight into services splitting over different interfaces for both cases.

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In the next few years, mobile networks will undergo significant evolutions in order to accommodate the ever-growing load generated by increasingly pervasive smartphones and connected objects. Among those evolutions, cognitive networking upholds a more dynamic management of network resources that adapts to the significant spatiotemporal fluctuations of the mobile demand. Cognitive networking techniques root in the capability of mining large amounts of mobile traffic data collected in the network, so as to understand the current resource utilization in an automated manner. In this paper, we take a first step towards cellular cognitive networks by proposing a framework that analyzes mobile operator data, builds profiles of the typical demand, and identifies unusual situations in network-wide usages. We evaluate our framework on two real-world mobile traffic datasets, and show how it extracts from these a limited number of meaningful mobile demand profiles. In addition, the proposed framework singles out a large number of outlying behaviors in both case studies, which are mapped to social events or technical issues in the network.

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This paper presents a radio frequency (RF)-based location tracking system that improves its performance by eliminating the shadowing caused by the human body of the user being tracked. The presence of such a user will influence the RF signal paths between a body-worn node and the receiving nodes. This influence will vary with the user’s location and orientation and, as a result, will deteriorate the performance regarding location tracking. By using multiple mobile nodes, placed on different parts of a human body, we exploit the fact that the combination of multiple measured signal strengths will show less variation caused by the user’s body. Another method is to compensate explicitly for the influence of the body by using the user’s orientation toward the fixed infrastructure nodes. Both approaches can be independently combined and reduce the influence caused by body shadowing, hereby improving the tracking accuracy. The overall system performance is extensively verified on a building-wide testbed for sensor experiments. The results show a significant improvement in tracking accuracy. The total improvement in mean accuracy is 38.1% when using three mobile nodes instead of one and simultaneously compensating for the user’s orientation.

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With the pervasiveness of mobile devices and the development of wireless communication technique, location-based services (LBS) have made our life more convenient, and the polygons spatial query, which can provide more flexible LBS, has attracted considerable interest recently. However, the flourish of polygons spatial query still faces many challenges including the query information privacy. In this paper, we present an efficient and privacy-preserving polygons spatial query framework for location-based services, called Polaris. With Polaris, the LBS provider outsources the encrypted LBS data to cloud server, and the registered user can query any polygon range to get accurate LBS results without divulging his/her query information to the LBS provider and cloud server. Specifically, an efficient special polygons spatial query algorithm (SPSQ) over ciphertext is constructed, based on an improved homomorphic encryption technology over composite order group. With SPSQ, Polaris can search outsourced encrypted LBS data in cloud server by the encrypted request, and respond the encrypted polygons spatial query results accurately. Detailed security analysis shows that the proposed Polaris can resist various known security threats. In addition, performance evaluations via implementing Polaris on smartphone and workstation with real LBS dataset demonstrate Polaris’ effectiveness in term of real environment.

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Auctions are among the best-known market-based tools to solve the problem of dynamic spectrum redistribution. In recent years, a good number of strategy-proof auction mechanisms have been proposed to improve spectrum utilization and to prevent market manipulation. However, the issue of privacy preservation in spectrum auctions remains open. On the one hand, truthful bidding reveals bidders’ private valuations of the spectrum. On the other hand, coverage/interference areas of the bidders may be revealed to determine conflicts. In this paper, we present PISA, which is a PrIvacy preserving and Strategy-proof Auction mechanism for spectrum allocation. PISA provides protection for both bid privacy and coverage/interference area privacy leveraging a privacy-preserving integer comparison protocol, which is well applicable in other contexts. We not only theoretically prove the privacy-preserving properties of PISA, but also extensively evaluate its performance. Evaluation results show that PISA achieves good spectrum allocation efficiency with light computation and communication overheads.

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This paper presents a coherent scheme to optimize an in-band full-duplex multiple-input-multiple-output (MIMO) relay via beamforming and transmit power allocation in a two-hop single-input-single-output (SISO) link under full channel knowledge and perfect hardware assumptions. First, we derive in closed form the optimal pair of transmit power and receive filter for a fixed transmit filter by unifying the minimum-mean-square-error (MMSE) filtering with the SISO-equivalent power allocation, as an iterative approach is not guaranteed to converge to global optimum. Second, we propose a heuristic algorithm to approximate the optimal transmit filter for a fixed receive filter. Furthermore, we study the well-known null-space projection constraint and derive a singular value decomposition (SVD)-based solution for the arbitrary-rank self-interference channel by generalizing the optimal solution under the assumption of rank-1 self-interference channel. Finally, we combine these solutions into a partially iterative algorithm in order to address the global optimization as our observations justify that some of the aforementioned schemes converge to the optimal solution under certain criteria. The numerical analysis of the proposed iterative algorithm demonstrates close-to-optimal performance relative to the theoretical upper bound of the end-to-end link in terms of maximum achievable throughput.

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Extra connectivity is an important indicator of the robustness of a multiprocessor system in presence of failing processors. The  g -extra conditional diagnosability and the  t/m -diagnosability are two important diagnostic strategies at system-level that can significantly enhance the system’s self-diagnosing capability. The  g -extra conditional diagnosability is defined under the assumption that every component of the system removing a set of faulty vertices has more than  g vertices. The  t/m -diagnosis strategy can detect up to  t faulty processors which might include at most  m misdiagnosed processors, where  m is typically a small integer number.

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The dramatic increase in data rates in wireless networks has caused radio spectrum usage to be an essential and critical issue. Spectrum sharing is widely recognized as an affordable, near-term method to address this issue. This paper first characterizes the new features of spectrum sharing in future wireless networks, including heterogeneity in sharing bands, diversity in sharing patterns, crowd intelligence in sharing devices, and hyperdensification in sharing networks. Then, to harness the benefits of these unique features and promote a vision of spectrum without bounds and networks without borders, this paper introduces a new concept of the Internet of spectrum devices (IoSDs) and develops a cloud-based architecture for IoSD over future wireless networks, with the prime aim of building a bridging network among various spectrum monitoring devices and massive spectrum utilization devices, and enabling a highly efficient spectrum sharing and management paradigm for future wireless networks. Furthermore, this paper presents a systematic tutorial on the key enabling techniques of the IoSD, including big spectrum data analytics, hierarchal spectrum resource optimization, and quality of experience-oriented spectrum service evaluation. In addition, the unresolved research issues are also presented.

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Network control refers to a very large and diverse set of problems including controllability of linear time-invariant dynamical systems, where the objective is to select an appropriate input to steer the network to a desired state. There are many notions of controllability, one of them being structural controllability, which is intimately connected to finding maximum matchings on the underlying network topology. In this work, we study fast, scalable algorithms for finding maximum matchings for a large class of random networks. First, we illustrate that degree distribution random networks are realistic models for real networks in terms of structural controllability. Subsequently, we analyze a popular, fast and practical heuristic due to Karp and Sipser as well as a simplification of it. For both heuristics, we establish asymptotic optimality and provide results concerning the asymptotic size of maximum matchings for an extensive class of random networks

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This paper presents the first study on scheduling for cooperative data dissemination in a hybrid infrastructure-to-vehicle (I2V) and vehicle-to-vehicle (V2V) communication environment. We formulate the novel problem of cooperative data scheduling (CDS). Each vehicle informs the road-side unit (RSU) the list of its current neighboring vehicles and the identifiers of the retrieved and newly requested data. The RSU then selects sender and receiver vehicles and corresponding data for V2V communication, while it simultaneously broadcasts a data item to vehicles that are instructed to tune into the I2V channel. The goal is to maximize the number of vehicles that retrieve their requested data. We prove that CDS is NP-hard by constructing a polynomial-time reduction from the Maximum Weighted Independent Set (MWIS) problem. Scheduling decisions are made by transforming CDS to MWIS and using a greedy method to approximately solve MWIS. We build a simulation model based on realistic traffic and communication characteristics and demonstrate the superiority and scalability of the proposed solution. The proposed model and solution, which are based on the centralized scheduler at the RSU, represent the first known vehicular ad hoc network (VANET) implementation of software defined network (SDN) concept.

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This letter proposes a novel output combining network devised to extend a Doherty power amplifier’s (DPA’s) radio frequency bandwidth (RFBW), while maintaining the proper load modulation, and to ensure its linearizability when driven with intra- and inter-band carrier aggregated (CA) communication signals. Based on the proposed topology, a wideband 20-W DPA was designed and implemented using packaged GaN transistors. Drain efficiency in excess of 48% was recorded at 6 dB back-off over the frequency range of 1.72-2.27 GHz. The DPA prototype was successfully linearized when driven with wideband (up to 160 MHz instantaneous bandwidth) and dual-band (up to 300 MHz carrier separation) modulated stimuli and achieved an average drain efficiency in excess of 45%.

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Phase noise (PHN) and in-phase/quadrature (I/Q) imbalance are two major radio-frequency (RF) impairments in direct-conversion wireless transceivers. Beamforming and orthogonal frequency-division multiplexing (OFDM) schemes have been adopted in broadband wireless standards due to their significant performance gains. In this paper, we analyze the impact of joint I/Q imbalance and PHN on beamforming OFDM direct-conversion transceivers. We derive an exact normalized-mean-square-error expression (NMSE) and examine several special and asymptotic cases to gain insights. One such insight is that, asymptotically, for both large signal-to-noise ratio (SNR) and the beamforming array size, the PHN and I/Q imbalance effects become decoupled.

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Microgrids consist of multiple parallel-connected distributed generation (DG) units with coordinated control strategies, which are able to operate in both grid-connected and islanded mode. Microgrids are attracting more and more attention since they can alleviate the stress of main transmission systems, reduce feeder losses, and improve system power quality. When the islanded microgrids are concerned, it is important to maintain system stability and achieve load power sharing among the multiple parallel-connected DG units. However, the poor active and reactive power sharing problems due to the influence of impedance mismatch of the DG feeders and the different ratings of the DG units are inevitable when the conventional droop control scheme is adopted. Therefore, the adaptive/improved droop control, network-based control methods and cost-based droop schemes are compared and summarized in this paper for active power sharing. Moreover, nonlinear and unbalanced loads could further affect the reactive power sharing when regulating the active power, and it is difficult to share the reactive power accurately only by using the enhanced virtual impedance method. Therefore, the hierarchical control strategies are utilized as supplements of the conventional droop controls and virtual impedance methods. The improved hierarchical control approaches such as the algorithms based on graph theory, multi-agent system, the gain scheduling method and predictive control have been proposed to achieve proper reactive power sharing for islanded microgrids and eliminate the effect of the communication delays on hierarchical control. Finally, the future research trends on islanded microgrids are also discussed in this paper.

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The demand for spectrum resources has increased dramatically with the advent of modern wireless applications. Spectrum sharing, considered as a critical mechanism for 5G networks, is envisioned to address spectrum scarcity issue and achieve high data rate access, and guaranteed the quality of service (QoS). From the licensed network’s perspective, the interference caused by all secondary users (SUs) should be minimized. From secondary networks point of view, there is a need to assign networks to SUs in such a way that overall interference is reduced, enabling the accommodation of a growing number of SUs. This paper presents a network selection and channel allocation mechanism in order to increase revenue by accommodating more SUs and catering to their preferences, while at the same time, respecting the primary network operator’s policies. An optimization problem is formulated in order to minimize accumulated interference incurred to licensed users and the amount that SUs have to pay for using the primary network. The aim is to provide SUs with a specific QoS at a lower price, subject to the interference constraints of each available network with idle channels. Particle swarm optimization and a modified version of the genetic algorithm are used to solve the optimization problem. Finally, this paper is supported by extensive simulation results that illustrate the effectiveness of the proposed methods in finding a near-optimal solution.

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Channel congestion is one of the major challenges for IEEE 802.11p-based vehicular networks. Unless controlled, congestion increases with vehicle density, leading to high packet loss and degraded safety application performance. We study two classes of congestion control algorithms, i.e., reactive state-based and linear adaptive. In this paper, the reactive state-based approach is represented by the decentralized congestion control framework defined in the European Telecommunications Standards Institute. The linear adaptive approach is represented by the LInear MEssage Rate Integrated Control (LIMERIC) algorithm. Both approaches control safety message transmissions as a function of channel load [i.e., channel busy percentage (CBP)]. A reactive state-based approach uses CBP directly, defining an appropriate transmission behavior for each CBP value, e.g., via a table lookup. By contrast, a linear adaptive approach identifies the transmission behavior that drives CBP toward a target channel load. Little is known about the relative performance of these approaches and any existing comparison is limited by incomplete implementations or stability anomalies. To address this, this paper makes three main contributions. First, we study and compare the two aforementioned approaches in terms of channel stability and show that the reactive state-based approach can be subject to major oscillation. Second, we identify the root causes and introduce stable reactive algorithms. Finally, we compare the performance of the stable reactive approach with the linear adaptive approach and the legacy IEEE 802.11p. It is shown that the linear adaptive approach still achieves a higher message throughput for any given vehicle density for the defined performance metrics.

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This paper studies performance modeling of the IEEE 802.11p enhanced distributed channel access (EDCA) mechanism and develops performance models to analyze the access performance of the IEEE 802.11p EDCA mechanism. A 2-D Markov chain is first constructed to model the backoff procedure of an access category (AC) queue and establish a relationship between the transmission probability and collision probability of the AC queue. Then, a 1-D discrete-time Markov chain is constructed to model the contention period of an AC queue and establish another relationship between the transmission probability and collision probability of the AC queue. Unlike most existing work, the 1-D Markov chain is extended to be infinite in modeling the contention period of an AC queue under both saturated and nonsaturated conditions. The two Markov models take into account all major factors that could affect the access performance of the IEEE 802.11p EDCA mechanism, including the saturation condition, standard parameters, backoff counter freezing, and internal collision. Based on the two Markov models, performance models are further derived to describe the relationships between the parameters of an AC queue and the access performance of the AC queue in terms of the transmission probability, collision probability, normalized throughput, and average access delay, respectively. The effectiveness of the performance models are verified through simulation results.

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In this article, we describe a strategy for planning the roadside infrastructure for vehicular networks based on the global behavior of drivers. Instead of relying on the trajectories of all vehicles, our proposal relies on the migration ratios of vehicles between urban regions in order to infer the better locations for deploying the roadside units. By relying on the global behavior of drivers, our strategy does not incur in privacy concerns. Given a set of α available roadside units, our goal is to select those α-better locations for placing the roadside units in order to maximize the number of distinct vehicles experiencing at least one V2I contact opportunity. Our results demonstrate that full knowledge of the vehicle trajectories are not mandatory for achieving a close-to-optimal deployment performance when we intend to maximize the number of distinct vehicles experiencing (at least one) V2I contact opportunities.

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ABSTRACT

In this study, a green vehicular ad-hoc network (VANET) infrastructure is suggested. The main players in such an infrastructure are the road side units (RSUs) which are able to harvest the energy needed for their work from the surrounding environment, especially the solar energy. Such a suggestion permits to install the RSUs in any place without considering the power supply availability and hence, an extensive area is covered by the VANET infrastructure with an improved performance. To achieve this goal, a new distributed power management scheme called duty cycle estimation-event driven duty cycling is suggested and installed locally in the RSUs in order to decrease their power consumption and to extend the lifetime of their batteries. Embedded UBICOM IP2022 network processer platform is adopted to implement the proposed RSU and the detailed design steps are described, while the necessary values of the system components such as the number of solar cell panels, battery cells capacity and so on, are tuned to suit the design goals. The suggested method is compared with other duty cycling methods to show its effectiveness to build a green VANET infrastructure.

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ABSTRACT

This paper is concerned with the problem of vehicular platoon control in vehicular ad hoc networks subject to capacity limitation and random packet dropouts. By introducing binary sequences as the basis of network access scheduling and modeling random packet dropouts as independent Bernoulli processes, we derive a closed-form methodology for vehicular platoon control. In particular, an interesting framework for network access scheduling and platoon control codesign is established based on a set of priority rules for network access control. The resulting platoon control and scheduling algorithm can resolve network access conflicts in vehicular ad hoc networks and guarantee string stability and zero steady-state spacing errors. The effectiveness of the method is demonstrated by numerical simulations and experiments with laboratory-scale Arduino cars.

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ABSTRACT

Secure QoS routing algorithms are a fundamental part of wireless networks that aim to provide services with QoS and security guarantees. In vehicular ad hoc networks (VANETs), vehicles perform routing functions, and at the same time act as end-systems thus routing control messages are transmitted unprotected over wireless channels. The QoS of the entire network could be degraded by an attack on the routing process, and manipulation of the routing control messages. In this paper, we propose a novel secure and reliable multi-constrained QoS aware routing algorithm for VANETs. We employ the ant colony optimisation (ACO) technique to compute feasible routes in VANETs subject to multiple QoS constraints determined by the data traffic type. Moreover, we extend the VANET-oriented evolving graph (VoEG) model to perform plausibility checks on the routing control messages exchanged among vehicles. Simulation results show that the QoS can be guaranteed while applying security mechanisms to ensure a reliable and robust routing service

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ABSTRACT

Vehicular ad hoc networks (VANETs) can efficiently offer safety-related and commercial contents for in-vehicle consumption. In this paper, we analyze the vehicle-to-vehicle (V2V) data dissemination with network coding in two-way road networks, where the vehicles move in opposite directions. In particular, depending on whether the broadcasting coverage areas overlap or not, two-way data dissemination is usually carried out in two phases, namely, the encountering phase and the separated phase. We first derive the probability mass function (pmf) of the dissemination completion time for the encountering disseminators during the encountering phase. The data dissemination velocity in the separated phase is mathematically derived. We prove that, without the help of the data dissemination in their own direction, the vehicles cannot recover all original packets from the opposite direction under a scarce handover condition. Furthermore, the dissemination slope and cache capacity of the vehicles in the proposed model are also analytically presented. Simulation results are provided to confirm the accuracy of the developed analytical results.

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ABSTRACT

In traffic jam or dense vehicle environment, vehicular ad-hoc networks (VANET) can’t meet safety requirement due to serious packet collision. The traditional cellular network solves packet collision, but suffers from long end-to-end delay. 3GPP Long Term Evolution (LTE) overcomes both drawbacks, thus it may be used instead of VANET in some extreme environments. We use Markov models with the dynamic scheduling and semipersistent scheduling (SPS) to evaluate how many idle resources of LTE can be provided for safety services and how safety applications impact on LTE traditional users. Based on the analysis, we propose to reserve the idle radio resources in LTE for vehicular safety services (LTE-V). Additionally, we propose the weighted-fair-queueing (WFQ) algorithm to schedule beacons for safety services using LTE reserved resource. Numerical results verify that the proposed mechanism can significantly improve the reliability of safety application by borrowing limited LTE bandwidth. We also build NS3 simulation platform to verify the effectiveness of the proposed Markov models. Finally, the reliability of applications including cooperation collision warning, slow vehicle indication and rear-end collision warning using DSRC with LTE-V are evaluated. The simulation results demonstrate that the stringent QoS requirement of the above three applications can be satisfied even under heavy traffic.

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ABSTRACT

Constructing intelligent and efficient transportation systems for modern metropolitan areas has become a very important quest for nations possessing metropolitan cities with ever-increasing populations. A new trend is the development of smart vehicles with multiple sensors able to dynamically form a temporary vehicular ad hoc network (VANET) or a vehicular sensor network (VSN). Along with a wireless-enabled roadside unit (RSU) network, drivers in a VSN can efficiently exchange important or urgent traffic information and make driving decisions accordingly. In order to support secure communication and driver privacy for vehicles in a VSN, we develop a new identity-based (ID-based) signature based on the elliptic curve cryptosystem (ECC) and then adopt it to propose a novel conditional privacy-preserving authentication scheme based on our invented ID-based signature. This scheme provides secure authentication process for messages transmitted between vehicles and RSUs. A batch message verification mechanism is also supported by the proposed scheme to increase the message processing throughput of RSUs. To further enhance scheme efficiency, both pairing operation and MapToPoint operation are not applied in the proposed authentication scheme. In comparison with existing pseudo-ID-based authentication solutions for VSN, this paper shows that the proposed scheme has better performance in terms of time consumption.

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ABSTRACT

This paper addresses the issue of selecting routing paths with minimum end-to-end delay (E2ED) for nonsafety applications in urban vehicular ad hoc networks (VANETs). Most existing schemes aim at reducing E2ED via greedy-based techniques (i.e., shortest path, connectivity, or number of hops), which make them prone to the local maximum problem and to data congestion, leading to higher E2ED. As a solution, we propose SCRP, which is a distributed routing protocol that computes E2ED for the entire routing path before sending data messages. To do so, SCRP builds stable backbones on road segments and connects them at intersections via bridge nodes. These nodes assign weights to road segments based on the collected information of delay and connectivity. Routes with the lowest aggregated weights are selected to forward data packets. Simulation results show that SCRP outperforms some of the well-known protocols in literature

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ABSTRACT

Centralized solutions for vehicular traffic re-routing to alleviate congestion suffer from two intrinsic problems: scalability, as the central server has to perform intensive computation and communication with the vehicles in real-time; and privacy, as the drivers have to share their location as well as the origins and destinations of their trips with the server. This article proposes DIVERT, a distributed vehicular re-routing system for congestion avoidance. DIVERT offloads a large part of the rerouting computation at the vehicles, and thus, the re-routing process becomes practical in real-time. To take collaborative rerouting decisions, the vehicles exchange messages over vehicular ad hoc networks. DIVERT is a hybrid system because it still uses a server and Internet communication to determine an accurate global view of the traffic. In addition, DIVERT balances the user privacy with the re-routing effectiveness. The simulation results demonstrate that, compared with a centralized system, the proposed hybrid system increases the user privacy by 92% on average. In terms of average travel time, DIVERT’s performance is slightly less than that of the centralized system, but it still achieves substantial gains compared to the no re-routing case. In addition, DIVERT reduces the CPU and network load on the server by 99.99% and 95%, respectively.

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ABSTRACT

Vehicular ad hoc networks (VANETs) have recently received significant attention in improving traffic safety and efficiency. However, communication trust and user privacy still present practical concerns to the deployment of VANETs, as many existing authentication protocols for VANETs either suffer from the heavy workload of downloading the latest revocation list from a remote authority or cannot allow drivers on the road to decide the trustworthiness of a message when the authentication on messages is anonymous. In this paper, to cope with these challenging concerns, we propose a new authentication protocol for VANETs in a decentralized group model by using a new group signature scheme. With the assistance of the new group signature scheme, the proposed authentication protocol is featured with threshold authentication, efficient revocation, unforgeability, anonymity, and traceability. In addition, the assisting group signature scheme may also be of independent interest, as it is characterized by efficient traceability and message linkability at the same time. Extensive analyses indicate that our proposed threshold anonymous authentication protocol is secure, and the verification of messages among vehicles can be accelerated by using batch message processing techniques.

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ABSTRACT

In this paper, a novel approach for improving vehicular positioning is presented. This method is based on the cooperation of the vehicles by communicating their measured information about their position. This method consists of two steps. In the first step, we introduce our cooperative map matching method. This map matching method uses the V2V communication in a vehicular ad hoc network (VANET) to exchange global positioning system (GPS) information between vehicles. Having a precise road map, vehicles can apply the road constraints of other vehicles in their own map matching process and acquire a significant improvement in their positioning. After that, we have proposed the concept of a dynamic base station DGPS (DDGPS), which is used by vehicles in the second step to generate and broadcast the GPS pseudorange corrections that can be used by newly arrived vehicles to improve their positioning. The DDGPS is a decentralized cooperative method that aims to improve the GPS positioning by estimating and compensating the common error in GPS pseudorange measurements. It can be seen as an extension of DGPS where the base stations are not necessarily static with an exact known position. In the DDGPS method, the pseudorange corrections are estimated based on the receiver’s belief on its positioning and its uncertainty and then broadcasted to other GPS receivers. The performance of the proposed algorithm has been verified with simulations in several realistic scenarios.

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ABSTRACT

Node clustering is a potential approach to improve the scalability of networking protocols in vehicular ad hoc networks (VANETs). High relative vehicle mobility and frequent network topology changes inflict new challenges on maintaining stable clusters. As a result, cluster stability is a crucial measure of the efficiency of clustering algorithms for VANETs. This paper presents a stochastic analysis of the vehicle mobility impact on single-hop cluster stability. A stochastic mobility model is adopted to capture the time variations of intervehicle distances (distance headways). First, we propose a discrete-time lumped Markov chain to model the time variations of a system of distance headways. Second, the first passage time analysis is used to derive probability distributions of the time periods of the invariant cluster-overlap state and cluster membership as measures of cluster stability. Third, queueing theory is utilized to model the limiting behaviors of the numbers of common and unclustered nodes between neighboring clusters. Numerical results are presented to evaluate the proposed models, which demonstrate a close agreement between analytical and simulation results.

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