Showing papers in "Wireless Networks in 2015"

A survey of millimeter wave communications (mmWave) for 5G: opportunities and challenges

Abstract: With the explosive growth of mobile data demand, the fifth generation (5G) mobile network would exploit the enormous amount of spectrum in the millimeter wave (mmWave) bands to greatly increase communication capacity. There are fundamental differences between mmWave communications and existing other communication systems, in terms of high propagation loss, directivity, and sensitivity to blockage. These characteristics of mmWave communications pose several challenges to fully exploit the potential of mmWave communications, including integrated circuits and system design, interference management, spatial reuse, anti-blockage, and dynamics control. To address these challenges, we carry out a survey of existing solutions and standards, and propose design guidelines in architectures and protocols for mmWave communications. We also discuss the potential applications of mmWave communications in the 5G network, including the small cell access, the cellular access, and the wireless backhaul. Finally, we discuss relevant open research issues including the new physical layer technology, software-defined network architecture, measurements of network state information, efficient control mechanisms, and heterogeneous networking, which should be further investigated to facilitate the deployment of mmWave communication systems in the future 5G networks.

A secure authentication scheme for VANETs with batch verification

Abstract: Vehicular Ad-hoc Networks (VANETs) will start becoming deployed within the next decade. Among other benefits, it is expected that VANETs will support applications and services targeting the increase of safety on the road, and assist in improving the efficiency of the road transportation network. However, several serious challenges remain to be solved before efficient and secure VANET technology becomes available, one of them been efficient authentication of messages in a VANET. In this paper, we analyse a recent authentication scheme for VANETs introduced by Lee et al. Unfortunately this scheme is vulnerable to the impersonation attack so that a malicious user can generate a valid signature on behalf of the other vehicles. Based on the attack, we propose an improved scheme and introduce a simulation expressing the efficiency of the proposed scheme.

Survey on channel reciprocity based key establishment techniques for wireless systems

Abstract: Channel reciprocity based key establishment techniques have attracted more and more attention from the wireless security research community for its easy implementation, low computational requirement, and small energy consumption. The basic idea of these techniques is to establish a shared key by utilizing the wireless channel reciprocity, i.e., the transmitter and receiver of one wireless link can observe the same channel simultaneously. In this survey, we reviewed different types of existing techniques based on (1) how they quantize the wireless channel reciprocity into binary bits to form a secret key; (2) how they handle communication errors to achieve the key agreement between the transmitter and the receiver; and (3) the feasibility and security issues related to these techniques. This survey attempts to summarize the emerging research on channel reciprocity based key establishment, which may provide insights for us to identify wireless security problems and propose comprehensive defenses.

A distributed algorithm for energy efficient and fault tolerant routing in wireless sensor networks

Abstract: Energy conservation and fault tolerance are the most two important challenging issues for the development of large scale wireless sensor networks (WSNs). Failure of cluster heads in a cluster based WSN is more catastrophic as they are responsible not only for data aggregation and transmission of the aggregated data to the base station but also relaying data for multi-hop communication. Therefore, a routing algorithm in WSNs should be energy aware as well as fault tolerant. In this paper, we present a distributed energy efficient and fault tolerant routing algorithm for WSNs. The algorithm selects next-hop cluster head in energy efficient manner in the data routing phase and carefully restores the connectivity of the neighbours of a cluster head in case of its failure. The algorithm is tested extensively by considering several scenarios of WSN. The experimental results are compared with the existing algorithms in terms of several metrics to show the effectiveness of the proposed algorithm.

Li-Fi: Light fidelity-a survey

Abstract: Visible light communication (VLC), which uses a vast unregulated and free light spectrum, has emerged to be a viable solution to overcome the spectrum crisis of radio frequency. Light fidelity (Li-Fi) is an optical networked communication in the subset of VLC to offload the mobile data traffics which offers many advantages at indoor scenario. In this article, we survey the key technologies for realizing Li-Fi and present the sate-of-the-art on each aspect, such as: indoor optical wireless channel model, the VLC modulation techniques with user satisfaction, OFDM in VLC, optical MIMO, optical spatial modulation, multiple user access, resource allocation, interference management and hybrid Li-Fi schemes. Some challenges and future work that need to be solved in the area are also described.

Performance modeling and analysis of IEEE 802.11 DCF based fair channel access for vehicle-to-roadside communication in a non-saturated state

Abstract: This paper considers the fair access problem in vehicular ad hoc networks and develops analytical models for analyzing the performance of an IEEE 802.11 distributed coordination function based fair channel access protocol in a non-saturated state. We first derive the relationship between the transmission probability and the minimum contention window size of a vehicle, and the relationship between the velocity and the minimum contention window size of a vehicle in a non-saturated state. Based on the analytical model, the minimum contention window size of a vehicle for a given velocity can be determined in order to achieve fair access among different vehicles. Moreover, an analytical model is also developed for analyzing the throughput performance of the fair channel access protocol in a non-saturated state. The effectiveness of the analytical models is justified through simulation results.

Performance evaluation of MADM-based methods for network selection in a multimedia wireless environment

Abstract: As mobile devices have become more affordable, easy to use and powerful, the number of mobile users and their bandwidth demands have experienced a significant growth. Considering the rising popularity of power hungry applications (e.g., multimedia), battery power capacity is an important concern--as upgrades are not keeping up with the advances in other technologies (e.g., central processing unit and memory). Mobile users now demand better power and battery management techniques to prolong their mobile battery performance. This, together with the need for green information communications technology, provides motivation for researchers to develop energy efficient techniques to reduce the power consumption in next-generation wireless networks while meeting user's quality expectations. This paper conducts a realistic performance evaluation of a number of widely used multi attribute decision making (MADM)-based methods for network selection that aim at keeping the mobile users Always Best Connected anywhere and anytime. The main trade-off parameters considered include energy efficiency and user perceived quality levels for multimedia streaming. The energy consumption is modeled using real experimental results for an android mobile device. Similarly, the multimedia quality function was modeled using real user data, combined with a qualitative study to determine the resulting mean opinion scores. The performance analysis shows that the weighted multiplicative method (MEW) finds a better energy-quality trade-off for users in a heterogeneous wireless environment in comparison with three other MADM solutions.

Impact of static trajectories on localization in wireless sensor networks

Abstract: A Wireless Sensor Network (WSN) consists of many sensors that communicate wirelessly to monitor a physical region. Location information is critical essential and indispensable for many applications of WSNs. A promising solution for localizing statically deployed sensors is to benefit from mobile location-aware nodes called beacons. However, the essential problem is to find the optimum path that the mobile beacon should travel in order to improve localization accuracy, time and success as well as energy efficiency. In this paper, we evaluate the performance of five mobile beacon trajectories; Random Way Point, Scan, Hilbert, Circles and Localization algorithm with a Mobile Anchor node based on Trilateration (LMAT) based on three different localization techniques such as Weighted Centroid Localization and trilateration with time priority and accuracy priority. This evaluation aims to find effective and essential properties that the trajectory should have. Our simulations show that a random movement cannot guarantee the performance of localization. The results also show the efficiency of LMAT regarding accuracy, success and collinearity while the Hilbert space filling curve has lower energy consumption. Circles path planning can help to localize unknown sensors faster than others at the expense of lower localization precision.

A sequence number based bait detection scheme to thwart grayhole attack in mobile ad hoc networks

Abstract: Wireless shared medium, randomly moving nodes and multi-hop architecture make mobile ad hoc networks vulnerable to various network layer threats. Grayhole attack is such a prominent network layer threat, in which a malevolent node attempts to establish a bogus route passing through itself and performs packet forwarding misbehavior by dropping a subset of the received data packets in order to degrade the network performance. In this paper, we address this issue by proposing a heuristic approach, referred to as sequence number based bait detection scheme, which attempts to isolate malevolent nodes during route discovery process. The mechanism is incorporated with ad hoc on-demand distance vector routing protocol. Performance of the proposed scheme is compared with an existing scheme under three grayhole adversary models adopting distinct mode of operations. Simulation results under various network parameters depict that the proposed scheme improves network performance depending upon the mode of operations of the adversaries.

DeepSleep: IEEE 802.11 enhancement for energy-harvesting machine-to-machine communications

Abstract: As future Machine-to-Machine (M2M) communications aim at supporting wireless networks with large coverage range and a huge number of devices without human intervention, energy-efficient protocol design for M2M communications networks becomes notably significant. The emerging energy harvesting technology, allowing devices to harvest energy from external sources automatically without human intervention, is promisingly applied to M2M communications networks, which can therefore operate permanently. However, currently available IEEE 802.11 protocols do not consider supporting energy-harvesting devices efficiently. Our research focuses effort in enhancing IEEE 802.11 power saving mode (PSM) with widely-deployed numerous devices powered by energy-harvesting modules so as to realize an energy-efficient M2M communications network. We propose DeepSleep with the aim of improving energy-efficiency and reducing the overall outage probability, application layer loss rate and collision probability. The effectiveness of DeepSleep is demonstrated by NS-2 platform. An analytical model is provided to select DeepSleep parameters. Applying DeepSleep, an energy-harvesting device can have less energy wastage on idle listening and overhearing, and have a higher channel access priority when waking up from a relatively longer period of sleeping. In addition, the channel access fairness is considered in DeepSleep design. In addition, all devices benefit when DeepSleep and 802.11 PSM co-exist in the network, which implies DeepSleep has potential to be deployed in existing WLANs.

A group-based security protocol for machine-type communications in LTE-advanced

Abstract: Machine-type communication (MTC) takes advantage of millions of devices being connected to each other in sensing our environment. A third-generation partnership project has been actively considering MTC as an enabler for ubiquitous computing and context-aware services. Until recently, we have not yet known how to productively manage the signaling traffic from these MTC devices because authentication requirements may impose such large signaling loads that they overwhelm the radio access of 4G cellular networks. This paper proposes the design of an efficient security protocol for MTC. This protocol is designed to be compatible with the incumbent system by being composed of only symmetric cryptography. Efficiency is attained by aggregating many authentication requests into a single one. The security and performance of the new design are evaluated via formal verification and theoretical analysis. Implementation of the proposed protocol in a real LTE-A network is provided through a feasibility analysis undertaken to prove the practicability of the protocol. Based on these evaluations, we contend that the proposed protocol is practical in terms of security and performance for MTC in LTE-Advanced.

When D2D communication improves group oriented services in beyond 4G networks

Abstract: The design of effective radio resource management policies for group-oriented services in beyond-4G networks is attracting the interest of the research community. Along this line, this paper analyzes some novel approaches that take advantages of the Device to Device (D2D) communication paradigm with the aim of improving the session quality experienced by mobile users in terms of delay and energy consumption. The basic idea is to enable receivers with a bad cellular link from the evolved Node B (eNodeB) to receive the multicast service through another mobile device located in proximity over a direct link. Two schemes are proposed that exploit different radio technologies to enable nearby multicast subscribers to establish direct local links, either Long Term Evolution-Advanced (LTE-A) or Wi-Fi Direct. The effectiveness of the proposed solutions is demonstrated through a comprehensive simulative analysis and compared with traditional techniques that only exploit point-to-multipoint communication from the eNodeB to all the group members not taking advantages of the multi-user diversity or alternative network technologies to serve the multicast users.

Context aware adaptive fuzzy based QoS routing scheme for streaming services over MANETs

Abstract: The need for an adaptive with support for context service aware Quality of Service routing scheme is always a major research challenge. The complexities of Mobile Ad hoc Networks are well surveyed, but traditional routing protocols do not focus on the context aware nature of services, which is highly required for dynamic change in service requirements. Context Aware Adaptive Fuzzy (COAAF) is a `context aware' protocol, which is adaptive for variable services and network traffic intensity. The behaviour of streaming services is found to be highly variable; hence, fuzzy approach is adopted. COAAF is simulated over NS-2 and its performance analyzed in comparison with AODV, DYMO and GPSR routing schemes.

Interference alignment with delayed channel state information and dynamic AR-model channel prediction in wireless networks

Abstract: Interference alignment (IA) is a promising technique that can effectively eliminate the interferences in multiuser wireless networks. However, it requires highly accurate channel state information (CSI) of the whole network at all the transmitters and receivers. In practical wireless systems, it is difficult to obtain the perfect knowledge of a dynamic channel. Particularly, the CSI at transmitters used in IA is usually delayed through feedback, which will dramatically affect the performance of IA. In this paper, the performance of IA with delayed CSI is studied. The expressions of the average signal to interference plus noise ratio and sum rate of IA networks with delayed CSI are established. To alleviate the influence of delayed CSI, an IA scheme based on dynamic autoregressive (AR)-model channel prediction is proposed, in which the parameters of AR mode are updated frequently. The CSI of the next time instant is predicted using the present and past CSI in the proposed scheme to improve the performance of IA networks. Two key factors of the scheme, window length and refresh rate are analyzed in detail. Simulation results are presented to show that the proposed IA scheme based on channel prediction can significantly improve its performance with delayed CSI.

An optimization algorithm for the minimum k-connected m-dominating set problem in wireless sensor networks

Abstract: In wireless sensor networks (WSNs), virtual backbone has been proposed as the routing infra-structure and connected dominating set has been widely adopted as virtual backbone. However, since the sensors in WSNs are prone to failures, recent studies suggest that it is also important to maintain a certain degree of redundancy in the backbone. To construct a robust backbone, so called k-connected m-dominating set has been proposed. In this research, we propose an integer programming formulation and an optimal algorithm for the minimum k-connected m-dominating set problem. To the best of our knowledge, this is the first integer programming formulation for the problem, and extensive computational results show that our optimal algorithm is capable of finding a solution within a reasonable amount of time.

Distributed multi chain compressive sensing based routing algorithm for wireless sensor networks

Abstract: In wireless sensor networking applications, collecting sensed data and relaying it to the base station in an energy efficient manner is of paramount importance. It follows that power management and energy-efficient communication techniques become necessary to maximize network lifetime for wireless sensor networks (WSNs). In this paper, our objective is to distribute energy consumption evenly and maximize the network lifetime by utilizing data aggregation and in-network compression technique. We mainly focus on the combined problem of data routing with data aggregation during routing such that minimizing the number of packets to transmit and achieve our objective. We propose a multi chain routing algorithm executed with compressive sensing for data aggregating in WSNs. We show that by using our compressive sensing based routing algorithm significant reduction in data traffic can be achieved, resulting in power saving and thus prolong the network lifetime.

Approximating geographic routing using coverage tree heuristics for wireless network

Abstract: Geographic routing scheme (such as Greedy perimeter stateless routing) makes use of location information to forward packets greedily Nodes need to keep only this location information in stateless routing When the greedy forwarding fails, routing switches to perimeter forwarding based on either planar graph (GG and RNG) or cross link detection protocol approaches However, it has drawback in terms of cost and computational overheads We propose a coverage-tree heuristic based routing instead of face routing in geographic routing schemes when greedy forwarding fails We prove that the coverage tree based routing problem is NP hard by reduction using minimum rooted spanning tree of depth 2 (RST 2) We also show that coverage-tree based geographic routing problem is APX hard and not approximable with a factor of $$1/2(1-\in ) \ln n$$1/2(1-?)lnn for any fixed $$\in > 0$$?>0 unless $$NP\subseteq DTIME(n^{\log \log n})$$NP⊆DTIME(nloglogn) Our proposed scheme of coverage-tree heuristics based geographic routing is $$(1+\ln m)$$(1+lnm)-approximation algorithm, a polynomial time algorithm using minimum distance topology knowledge On performance comparison using simulation, our proposed scheme outperforms with the competitive schemes in term of success rate, network overhead and success rate against varying node density

Multi-objective network planning optimization algorithm: human exposure, power consumption, cost, and capacity

Abstract: Due to the huge popularity of wireless networks, future designs will not only consider the provided capacity, but also the induced exposure, the corresponding power consumption, and the economic cost. As these requirements are contradictory, it is not straightforward to design optimal wireless networks. Those contradicting demands have to satisfy certain requirements in practice. In this paper, a combination of two algorithms, a genetic algorithm and a quasi-particle swarm optimization, is developed, yielding a novel hybrid algorithm that generates further optimizations of indoor wireless network planning solutions, which is named hybrid indoor genetic optimization algorithm. The algorithm is compared with a heuristic network planner and composite differential evolution algorithm for three scenarios and two different environments. Results show that our hybrid-algorithm is effective for optimization of wireless networks which satisfy four demands: maximum coverage for a user-defined capacity, minimum power consumption, minimal cost, and minimal human exposure.

A multi-hop heterogeneous cluster-based optimization algorithm for wireless sensor networks

Abstract: With the growth of different design goals and application requirements, wireless sensor networks (WSNs) have been increasingly popular for a wide variety of purposes, e.g., image formation of a target field, intrusion detection, surveillance and environmental monitoring. In this paper, a multi-hop heterogeneous cluster-based optimization algorithm (MHCOA) for WSNs is proposed. The motivation to MHCOA for WSNs is that several higher energy sensor nodes act as cluster heads, which are deployed artificially, while some low energy sensor nodes act as cluster members, which are deployed randomly. In order to realize monitoring task, we complete three major works in this paper. First, MHCOA calculates the number of cluster heads and communication radius of low energy sensor nodes; Second, it finishes monitoring task through data packets transmission with higher energy nodes acting as cluster heads in the form of multi-hop heterogeneous WSNs; Finally, simulation results show that compared to its peers in heterogeneous WSNs, MHCOA reduces the number of cluster heads, which saves the network average energy by up to 16.7 % and extends the network life by up to 38 %, while with less end-to-end delay.

An RSSI-based localization algorithm for outliers suppression in wireless sensor networks

Abstract: Node localization technology is one of the most important technologies in wireless sensor networks. Due to the advantages of saving and convenience, received signal strength indication (RSSI) technology is widely taken to measure the distance between the sensor nodes, and then trilateral localization algorithm which is one of the classic algorithms can calculate the position result quickly. However, the result always comes with an irregularly wide error. Environment, temperature and electromagnetism are generally considered the interference factors, which have been widely researched. From another angle, this study focuses on the error of the algorithm itself, and discusses the stability of equations. A trilateral localization algorithm for outliers suppression is proposed. Through a large number of simulation, it is demonstrated that the proposed algorithm has a good performance than classic trilateral algorithm based-on the nearest three anchor nodes. A significant meaning of this research is that the deepest source of gross errors has been found when we use classic trilateral algorithm.

SPEED-MAC: speedy and energy efficient data delivery MAC protocol for real-time sensor network applications

Abstract: Although existing wakeup scheduling techniques suggest end-to-end delay guarantees for real-time applications, their fixed wakeup schedules may not meet such constraints when multiple sensors compete for the event delivery at the same time. In this paper we propose a new MAC protocol called SPEED-MAC that can provide real-time delay guarantees with much lower energy consumption for both single-source and multi-source events. The main ideas underlying the protocol are twofold. First, we introduce a novel wakeup technique called signaling wakeup, which is small only enough to detect the event occurrence. By employing the signaling wakeup we can minimize the event report latency as well as the idle listening. Second, to resolve the collisions and contentions incurred by multi-source events, the protocol employs adaptive wakeup that combines static scheduling with contention-based media access control depending on the type of traffic. The result of our analytic evaluation confirms that SPEED-MAC can provide real-time delay guarantees even for a large-scale network assuming a low event rate. We have implemented SPEED-MAC on both NS-2 and MICA2 platforms, and evaluated both the energy and the network performance of the protocol for various scenarios including multi-source, multi-sink, source-to-sink, sink-to-source, multi-cast and broadcast traffic. Our experimentation results show that SPEED-MAC can achieve an order of magnitude energy savings while providing near optimal latency compared to the existing solutions.

Kuiper test and autoregressive model-based approach for wireless sensor network fault diagnosis

Abstract: Wireless sensor networks (WSNs) have recently received increasing attention in the areas of defense and civil applications of sensor networks. Automatic WSN fault detection and diagnosis is essential to assure system's reliability. Proactive WSNs fault diagnosis approaches use embedded functions scanning sensor node periodically for monitoring the health condition of WSNs. But this approach may speed up the depletion of limited energy in each sensor node. Thus, there is an increasing interest in using passive diagnosis approach. In this paper, WSN anomaly detection model based on autoregressive (AR) model and Kuiper test-based passive diagnosis is proposed. First, AR model with optimal order is developed based on the normal working condition of WSNs using Akaike information criterion. The AR model then acts as a filter to process the future incoming signal from different unknown conditions. A health indicator based on Kuiper test, which is used to test the similarity between the training error of normal condition and residual of test conditions, is derived for indicating the health conditions of WSN. In this study, synthetic WSNs data under different cases/conditions were generated and used for validating the approach. Experimental results show that the proposed approach could differentiate WSNs normal conditions from faulty conditions. At last, the overall results presented in this paper demonstrate that our approach is effective for performing WSNs anomalies detection.

Bandwidth-aware routing and admission control for efficient video streaming over MANETs

Abstract: In this paper, we develop and evaluate an adaptive self-configurable routing framework that can deal with dynamic nature of mobile ad hoc networks and provides quality-of-service (QoS) guarantees for efficient video streaming. Proposed framework mainly consists of two major components. Firstly, it is a reactive bandwidth-aware node-disjoint multipath routing protocol which determines routes based on the specified bandwidth requirements of the requesting application. The second component of the framework is a session admission control (SAC) process that permits or denies a session to enter into the network based on the current availability of network bandwidth. We also propose methods to handle QoS violations caused by network mobility and congestion by keeping backup routes, performing local route recovery, avoiding routing through short-lived low quality links and periodic monitoring of the active transmission routes. To verify our proposed algorithms, the network with H.264/SVC encoded video traces which are generated from real-time video traffic is used for modeling the behaviour of the source nodes. It has been observed that reactively discovered and maintained routes on the basis of the most recent information about network topology and available resources can significantly improve the admission decision accuracy of SAC process, in turn improving the quality of received video traffic significantly.

iTCP: an intelligent TCP with neural network based end-to-end congestion control for ad-hoc multi-hop wireless mesh networks

Abstract: Maintaining the performance of reliable transport protocols, such as transmission control protocol (TCP), over wireless mesh networks (WMNs) is a challenging problem due to the unique characteristics of data transmission over WMNs. The unique characteristics include multi-hop communication over lossy and non-deterministic wireless mediums, data transmission in the absence of a base station, similar traffic patterns over neighboring mesh nodes, etc. One of the reasons for the poor performance of conventional TCP variants over WMNs is that the congestion control mechanisms in conventional TCP variants do not explicitly account for these unique characteristics. To address this problem, this paper proposes a novel artificial intelligence based congestion control technique for reliable data transfer over WMNs. The synergy with artificial intelligence is established by exploiting a carefully designed neural network (NN) in the congestion control mechanism. We analyze the proposed NN based congestion control technique in detail and incorporate it into TCP to create a new variant that we name as intelligent TCP or iTCP. We evaluate the performance of iTCP using both ns-2 simulations and real testbed experiments. Our evaluation results demonstrate that our proposed congestion control technique exhibits a significant improvement in total network throughput and average energy consumption per transmitted bit compared to the congestion control techniques used in other TCP variants.

Internet connectivity for mobile ad hoc network: a survey based study

Abstract: Mobile ad hoc network (MANET) is a collection of wireless mobile nodes forming a temporary network without the aid of any established infrastructure or centralized administration. MANETs have become increasingly significant in recent years due to their potential applications. From a technological point of view, the realization of this vision still requires a large number of challenges to be solved related to devices, protocols, applications and services. The drawbacks of MANETs are the limited number of services and applications, limited wireless coverage, limited bandwidth and battery power, and dynamic network topology. The growth of the Internet services and applications and the trend in the fourth generation (4G) wireless networks to all-IP networks have led to an increasing demand for enabling MANET nodes to connect to the Internet and use its services and applications. These kinds of networks are named as hybrid MANETs which can be deployed quickly and easily. The main objective of this paper is to introduce an overview of the different challenges and solutions for MANET---Internet integration. It will also introduce a solid analysis of the most significant proposals by describing their functionality, characteristics, and drawbacks. Summary of features of existing hybrid integration approaches for integration is presented. This survey concludes with further points for investigation.

Exploiting online and offline activity-based metrics for opportunistic forwarding

Abstract: Opportunistic networks are challenged wireless networks of handheld mobile devices that use contact opportunities to allow users to communicate without network infrastructure.The highly dynamic nature of these networks requires efficient forwarding mechanisms as disconnections are frequent and an end-to-end communication paradigm is not applicable. Consequently, many existing routing protocols for opportunistic networks make use of social behavior characteristics to perform hop-by-hop routing and select an appropriate relay node. Social network information is commonly extracted from encounters detected between mobile devices. However, Internet added online social interaction techniques which reflect user's online behavior and are not based on physical meetings. In this paper we present a social-based forwarding strategy for opportunistic networks that exploits both offline and online user's social network information. By proposing a model of dynamic online social network that uses information extracted from offline and online user behavior, we show that routing centrality metrics combining node centrality extracted from the dynamic online social network and centrality extracted from the social network detected through encounters between mobile devices are able to improve delivery ratio and even reduce the number of message replicas to be injected into the network.

A prediction-based clustering algorithm for tracking targets in quantized areas for wireless sensor networks

Abstract: Target tracking is an important application of sensor networks, particularly interesting for ecology applications related to wildlife monitoring. In this context, understanding the territorial occupation of animals is fundamental for understanding their habits. In this work, we propose the PRATIQUE--a prediction-based clustering algorithm for tracking targets considering a discrete sensor field divided into cells. This approach is based on two hierarchical levels: static clusters at the first level and dynamic clusters at the second level. This hybrid scheme reduces the cost of communication and ensures that all data generated by an event be delivered to a single node. We use Kalman, Alpha-Beta, or Particle Filters in order to predict the target's position. Prediction is used to prepare the set of nodes that will detect the next event, thereby reducing the message overhead during the tracking task. Results show that prediction errors are close to one cell.

Multi-criteria based multipath OLSR for battery and queue-aware routing in multi-hop ad hoc wireless networks

Abstract: The unbalanced distribution of load among nodes is a critical issue of routing in multi-hop ad hoc wireless networks. The multipath OLSR (MP-OLSR) routing protocol offers an effective solution to the problem by providing multiple paths to the destination. However, in this protocol, there is no simultaneous consideration for energy and QoS metrics to measure the quality of links during route computation. Thus, the failure of node caused by battery depletion restricts its ability to relay packets and degrades the QoS performance of the MP-OLSR. In this paper, we propose a Multipath Battery and Queue Aware-OLSR (MBQA-OLSR) for energy efficient and load-aware routing, to conserve energy, balance load, and improve QoS performance. This was achieved by introducing a new Multi-Criteria Node Rank metric (MCNR), which comprises three node's metrics related to energy and QoS, namely: residual battery, idle time, and queue length, to measure the quality of links between nodes based on a new link cost function, and therefore, selecting the most efficient and reliable paths to the destination. Additionally, an Energy Aware Multi-Point Relay (EA-MPR) mechanism was exploited in the MBQA-OLSR, to select the MPR set, to optimize the topological information flooding according to energy resources and nodes status. The MBQA-OLSR was evaluated under various simulation environments and the results demonstrate its superiority compared with original schemes. It achieved a packet delivery ratio gain up to 54.4 % and significantly reduced the end-to-end delay, number of dead nodes and the energy cost per packet in dense static networks.

Exploring an energy-efficient DTN framework supporting disaster management services in post disaster relief operation

Abstract: In recent years, several investigations have been made on "challenged network" [also known as, delay tolerant network (DTN)] architectures highlighting their advantages and disadvantages. In spite of its inherent shortcomings of unreliability and delay, smart-phone based opportunistic network is gaining immense popularity in the research community due to its applicability in different adverse and extreme communication scenarios where traditional communication infrastructure is either unavailable or incapacitated for a long time. Considerable research has been conducted till date to design efficient network architecture for emergency data dissemination in intermittently connected/challenged networks. Different architectures (ranging from flat to multi-tier) are proposed for implementing opportunistic DTN keeping in view of specific application requirements. However, very few of these proposed architectures have been examined from the perspective of a post disaster communication. Moreover, most DTN architectures are designed by aiming towards increasing delivery probability and reducing latency and as a whole, maximizing network throughput; with very little emphasis on its energy efficiency. The impact of different mobility patterns on existing DTN routing algorithms with respect to data dissemination and energy consumption has also not been studied so far. Our objective, in this paper, is to investigate the impact of different mobility patterns on existing DTN routing protocols and existing DTN architectures and subsequently, come up with a suitable energy efficient DTN framework combining suitable architecture and routing protocol that may be used to offer different disaster management services during post-disaster relief operation. We have done an extensive simulation on ONE simulator with different categories of well-known existing DTN architectures, mobility models, DTN routing protocols to study the network performance in terms of delivery probability, energy efficiency and overhead ratio. Based on the simulation results, we have tried to figure out a suitable combination of energy efficient architecture, mobility model and routing protocol that fits well in the post disaster communication scenario.

Scheduling algorithms for extending directional sensor network lifetime

Abstract: Recently, directional sensor networks that are composed of a large number of directional sensors have attracted a great deal of attention. The main issues associated with the directional sensors are limited battery power and restricted sensing angle. Therefore, monitoring all the targets in a given area and, at the same time, maximizing the network lifetime has remained a challenge. As sensors are often densely deployed, a promising approach to conserve the energy of directional sensors is developing efficient scheduling algorithms. These algorithms partition the sensor directions into multiple cover sets each of which is able to monitor all the targets. The problem of constructing the maximum number of cover sets has been modeled as the multiple directional cover sets (MDCS), which has been proved to be an NP-complete problem. In this study, we design two new scheduling algorithms, a greedy-based algorithm and a learning automata (LA)-based algorithm, in order to solve the MDCS problem. In order to evaluate the performance of the proposed algorithms, several experiments were conducted. The obtained results demonstrated the efficiency of both algorithms in terms of extending the network lifetime. Simulation results also revealed that the LA-based algorithm was more successful compared to the greedy-based one in terms of prolonging network lifetime.