Showing papers on "Key distribution in wireless sensor networks published in 2005"

A survey on routing protocols for wireless sensor networks

Abstract: Recent advances in wireless sensor networks have led to many new protocols specifically designed for sensor networks where energy awareness is an essential consideration. Most of the attention, however, has been given to the routing protocols since they might differ depending on the application and network architecture. This paper surveys recent routing protocols for sensor networks and presents a classification for the various approaches pursued. The three main categories explored in this paper are data-centric, hierarchical and location-based. Each routing protocol is described and discussed under the appropriate category. Moreover, protocols using contemporary methodologies such as network flow and quality of service modeling are also discussed. The paper concludes with open research issues. � 2003 Elsevier B.V. All rights reserved.

Locating the nodes: cooperative localization in wireless sensor networks

Abstract: Accurate and low-cost sensor localization is a critical requirement for the deployment of wireless sensor networks in a wide variety of applications. In cooperative localization, sensors work together in a peer-to-peer manner to make measurements and then forms a map of the network. Various application requirements influence the design of sensor localization systems. In this article, the authors describe the measurement-based statistical models useful to describe time-of-arrival (TOA), angle-of-arrival (AOA), and received-signal-strength (RSS) measurements in wireless sensor networks. Wideband and ultra-wideband (UWB) measurements, and RF and acoustic media are also discussed. Using the models, the authors have shown the calculation of a Cramer-Rao bound (CRB) on the location estimation precision possible for a given set of measurements. The article briefly surveys a large and growing body of sensor localization algorithms. This article is intended to emphasize the basic statistical signal processing background necessary to understand the state-of-the-art and to make progress in the new and largely open areas of sensor network localization research.

Protocols and Architectures for Wireless Sensor Networks

Abstract: Preface. List of Abbreviations. A guide to the book. 1. Introduction. 1.1 The vision of Ambient Intelligence. 1.2 Application examples. 1.3 Types of applications. 1.4 Challenges for WSNs. 1.5 Why are sensor networks different? 1.6 Enabling technologies. PART I: ARCHITECTURES. 2. Single node architecture. 2.1 Hardware components. 2.2 Energy consumption of sensor nodes. 2.3 Operating systems and execution environments. 2.4 Some examples of sensor nodes. 2.5 Conclusion. 3. Network architecture. 3.1 Sensor network scenarios. 3.2 Optimization goals & figures of merit. 3.3 Design principles for WSNs. 3.4 Service interfaces of WSNs. 3.5 Gateway concepts. 3.6 Conclusion. PART II: COMMUNICATION PROTOCOLS. 4. Physical Layer. 4.1 Introduction. 4.2 Wireless channel and communication fundamentals. 4.3 Physical layer & transceiver design considerations in WSNs. 4.4 Further reading. 5. MAC Protocols 133 5.1 Fundamentals of (wireless) MAC protocols. 5.2 Low duty cycle protocols and wakeup concepts. 5.3 Contention-based protocols. 5.4 Schedule-based protocols. 5.5 The IEEE 802.15.4 MAC protocol. 5.6 How about IEEE 802.11 and Bluetooth? 5.7 Further reading. 5.8 Conclusion. 6. Link Layer Protocols. 6.1 Fundamentals: Tasks and requirements. 6.2 Error control. 6.3 Framing. 6.4 Link management. 6.5 Summary. 7. Naming and Addressing. 7.1 Fundamentals. 7.2 Address and name management in wireless sensor networks. 7.3 Assignment of MAC addresses. 7.4 Distributed assignment of locally unique addresses. 7.5 Content-based and geographic addressing. 7.6 Summary. 8. Time Synchronization. 8.1 Introduction to the time synchronization problem. 8.2 Protocols based on sender/receiver synchronization. 8.3 Protocols based on receiver/receiver synchronization. 8.4 Further reading. 9. Localization and Positioning. 9.1 Properties of positioning. 9.2 Possible approaches. 9.3 Mathematical basics for the lateration problem. 9.4 Single-hop localization. 9.5 Positioning in multi-hop environments. 9.6 Impact of anchor placement. 9.7 Further reading. 9.8 Conclusion. 10. Topology control 295 10.1 Motivation and basic ideas. 10.2 Flat network topologies. 10.3 Hierarchical networks by dominating sets. 10.4 Hierarchical networks by clustering. 10.5 Combining hierarchical topologies and power control. 10.6 Adaptive node activity. 10.7 Conclusions. 11. Routing protocols. 11.1 The many faces of forwarding and routing. 11.2 Gossiping and agent-based unicast forwarding. 11.3 Energy-efficient unicast. 11.4 Broadcast and multicast. 11.5 Geographic routing. 11.6 Mobile nodes. 11.7 Conclusions. 12. Data-centric and content-based networking 395. 12.1 Introduction. 12.2 Data-centric routing. 12.3 Data aggregation. 12.4 Data-centric storage. 12.5 Conclusions. 13. Transport Layer and Quality of Service. 13.1 The transport layer and QoS in wireless sensor networks. 13.2 Coverage and deployment. 13.3 Reliable data transport. 13.5 Block delivery. 13.6 Congestion control and rate control. 14. Advanced application support. 14.1 Advanced in-network processing. 14.2 Security. 14.3 Application-specific support. Bibliography. Index.

A survey on wireless mesh networks

Abstract: Wireless mesh networks (WMNs) have emerged as a key technology for next-generation wireless networking. Because of their advantages over other wireless networks, WMNs are undergoing rapid progress and inspiring numerous applications. However, many technical issues still exist in this field. In order to provide a better understanding of the research challenges of WMNs, this article presents a detailed investigation of current state-of-the-art protocols and algorithms for WMNs. Open research issues in all protocol layers are also discussed, with an objective to spark new research interests in this field.

Maintaining Sensing Coverage and Connectivity in Large Sensor Networks.

Abstract: In this paper, we address the issues of maintaining sensing coverage and connectivity by keeping a minimum number of sensor nodes in the active mode in wireless sensor networks. We investigate the relationship between coverage and connectivity by solving the following two sub-problems. First, we prove that if the radio range is at least twice the sensing range, complete coverage of a convex area implies connectivity among the working set of nodes. Second, we derive, under the ideal case in which node density is sufficiently high, a set of optimality conditions under which a subset of working sensor nodes can be chosen for complete coverage. Based on the optimality conditions, we then devise a decentralized density control algorithm, Optimal Geographical Density Control (OGDC), for density control in large scale sensor networks. The OGDC algorithm is fully localized and can maintain coverage as well as connectivity, regardless of the relationship between the radio range and the sensing range. Ns-2 simulations show that OGDC outperforms existing density control algorithms [25, 26, 29] with respect to the number of working nodes needed and network lifetime (with up to 50% improvement), and achieves almost the same coverage as the algorithm with the best result.

Topology Control in Wireless Ad Hoc and Sensor Networks

Abstract: Topology Control (TC) is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption (which is essential to extend the network operational time) and radio interference (with a positive effect on the network traffic carrying capacity). The goal of this technique is to control the topology of the graph representing the communication links between network nodes with the purpose of maintaining some global graph property (e.g., connectivity), while reducing energy consumption and/or interference that are strictly related to the nodes' transmitting range. In this article, we state several problems related to topology control in wireless ad hoc and sensor networks, and we survey state-of-the-art solutions which have been proposed to tackle them. We also outline several directions for further research which we hope will motivate researchers to undertake additional studies in this field.

A pairwise key predistribution scheme for wireless sensor networks

Abstract: To achieve security in wireless sensor networks, it is important to be able to encrypt and authenticate messages sent between sensor nodes. Before doing so, keys for performing encryption and authentication must be agreed upon by the communicating parties. Due to resource constraints, however, achieving key agreement in wireless sensor networks is nontrivial. Many key agreement schemes used in general networks, such as Diffie-Hellman and other public-key based schemes, are not suitable for wireless sensor networks due to the limited computational abilities of the sensor nodes. Predistribution of secret keys for all pairs of nodes is not viable due to the large amount of memory this requires when the network size is large.In this paper, we provide a framework in which to study the security of key predistribution schemes, propose a new key predistribution scheme which substantially improves the resilience of the network compared to previous schemes, and give an in-depth analysis of our scheme in terms of network resilience and associated overhead. Our scheme exhibits a nice threshold property: when the number of compromised nodes is less than the threshold, the probability that communications between any additional nodes are compromised is close to zero. This desirable property lowers the initial payoff of smaller-scale network breaches to an adversary, and makes it necessary for the adversary to attack a large fraction of the network before it can achieve any significant gain.

Z-MAC: a hybrid MAC for wireless sensor networks

Abstract: This paper presents the design, implementation and performance evaluation of a hybrid MAC protocol, called Z-MAC, for wireless sensor networks that combines the strengths of TDMA and CSMA while offsetting their weaknesses Like CSMA, Z-MAC achieves high channel utilization and low-latency under low contention and like TDMA, achieves high channel utilization under high contention and reduces collision among two-hop neighbors at a low cost A distinctive feature of Z-MAC is that its performance is robust to synchronization errors, slot assignment failures and time-varying channel conditions; in the worst case, its performance always falls back to that of CSMA Z-MAC is implemented in TinyOS

Energy-efficient target coverage in wireless sensor networks

Abstract: A critical aspect of applications with wireless sensor networks is network lifetime. Power-constrained wireless sensor networks are usable as long as they can communicate sensed data to a processing node. Sensing and communications consume energy, therefore judicious power management and sensor scheduling can effectively extend network lifetime. To cover a set of targets with known locations when ground access in the remote area is prohibited, one solution is to deploy the sensors remotely, from an aircraft. The lack of precise sensor placement is compensated by a large sensor population deployed in the drop zone, that would improve the probability of target coverage. The data collected from the sensors is sent to a central node (e.g. cluster head) for processing. In this paper we propose un efficient method to extend the sensor network life time by organizing the sensors into a maximal number of set covers that are activated successively. Only the sensors from the current active set are responsible for monitoring all targets and for transmitting the collected data, while all other nodes are in a low-energy sleep mode. By allowing sensors to participate in multiple sets, our problem formulation increases the network lifetime compared with related work [M. Cardei et al], that has the additional requirements of sensor sets being disjoint and operating equal time intervals. In this paper we model the solution as the maximum set covers problem and design two heuristics that efficiently compute the sets, using linear programming and a greedy approach. Simulation results are presented to verify our approaches.

Clock synchronization for wireless sensor networks: a survey

Abstract: Recent advances in micro-electromechanical (MEMS) technology have led to the development of small, low-cost, and low-power sensors Wireless sensor networks (WSNs) are large-scale networks of such sensors, dedicated to observing and monitoring various aspects of the physical world In such networks, data from each sensor is agglomerated using data fusion to form a single meaningful result, which makes time synchronization between sensors highly desirable This paper surveys and evaluates existing clock synchronization protocols based on a palette of factors like precision, accuracy, cost, and complexity The design considerations presented here can help developers either in choosing an existing synchronization protocol or in defining a new protocol that is best suited to the specific needs of a sensor-network application Finally, the survey provides a valuable framework by which designers can compare new and existing synchronization protocols

Consensus Filters for Sensor Networks and Distributed Sensor Fusion

Abstract: Consensus algorithms for networked dynamic systems provide scalable algorithms for sensor fusion in sensor networks. This paper introduces a distributed filter that allows the nodes of a sensor network to track the average of n sensor measurements using an average consensus based distributed filter called consensus filter. This consensus filter plays a crucial role in solving a data fusion problem that allows implementation of a scheme for distributed Kalman filtering in sensor networks. The analysis of the convergence, noise propagation reduction, and ability to track fast signals are provided for consensus filters. As a byproduct, a novel critical phenomenon is found that relates the size of a sensor network to its tracking and sensor fusion capabilities. We characterize this performance limitation as a tracking uncertainty principle. This answers a fundamental question regarding how large a sensor network must be for effective sensor fusion. Moreover, regular networks emerge as efficient topologies for distributed fusion of noisy information. Though, arbitrary overlay networks can be used. Simulation results are provided that demonstrate the effectiveness of consensus filters for distributed sensor fusion.

A centralized energy-efficient routing protocol for wireless sensor networks

Abstract: Wireless sensor networks consist of small battery powered devices with limited energy resources. Once deployed, the small sensor nodes are usually inaccessible to the user, and thus replacement of the energy source is not feasible. Hence, energy efficiency is a key design issue that needs to be enhanced in order to improve the life span of the network. Several network layer protocols have been proposed to improve the effective lifetime of a network with a limited energy supply. In this article we propose a centralized routing protocol called base-station controlled dynamic clustering protocol (BCDCP), which distributes the energy dissipation evenly among all sensor nodes to improve network lifetime and average energy savings. The performance of BCDCP is then compared to clustering-based schemes such as low-energy adaptive clustering hierarchy (LEACH), LEACH-centralized (LEACH-C), and power-efficient gathering in sensor information systems (PEGASIS). Simulation results show that BCDCP reduces overall energy consumption and improves network lifetime over its comparatives.

Improving wireless sensor network lifetime through power aware organization

Abstract: A critical aspect of applications with wireless sensor networks is network lifetime. Battery-powered sensors are usable as long as they can communicate captured data to a processing node. Sensing and communications consume energy, therefore judicious power management and scheduling can effectively extend operational time. To monitor a set of targets with known locations when ground access in the monitored area is prohibited, one solution is to deploy the sensors remotely, from an aircraft. The loss of precise sensor placement would then be compensated by a large sensor population density in the drop zone, that would improve the probability of target coverage. The data collected from the sensors is sent to a central node for processing. In this paper we propose an efficient method to extend the sensor network operational time by organizing the sensors into a maximal number of disjoint set covers that are activated successively. Only the sensors from the current active set are responsible for monitoring all targets and for transmitting the collected data, while nodes from all other sets are in a low-energy sleep mode. In this paper we address the maximum disjoint set covers problem and we design a heuristic that computes the sets. Theoretical analysis and performance evaluation results are presented to verify our approach.

System architecture of a wireless body area sensor network for ubiquitous health monitoring

Abstract: Recent technological advances in sensors, low-power microelectronics and miniaturization, and wireless networking enabled the design and proliferation of wireless sensor networks capable of autonomously monitoring and controlling environments. One of the most promising applications of sensor networks is for human health monitoring. A number of tiny wireless sensors, strategically placed on the human body, create a wireless body area network that can monitor various vital signs, providing real-time feedback to the user and medical personnel. The wireless body area networks promise to revolutionize health monitoring. However, designers of such systems face a number of challenging tasks, as they need to address often quite conflicting requirements for size, operating time, precision, and reliability. In this paper we present hardware and software architecture of a working wireless sensor network system for ambulatory health status monitoring. The system consists of multiple sensor nodes that monitor body motion and heart activity, a network coordinator, and a personal server running on a personal digital assistant or a personal computer.

EECS: an energy efficient clustering scheme in wireless sensor networks

Abstract: Data gathering is a common but critical operation in many applications of wireless sensor networks. Innovative techniques that improve energy efficiency to prolong the network lifetime are highly required. Clustering is an effective topology control approach in wireless sensor networks, which can increase network scalability and lifetime. In this paper, we propose a novel clustering schema EECS for wireless sensor networks, which better suits the periodical data gathering applications. Our approach elects cluster heads with more residual energy through local radio communication while achieving well cluster head distribution; further more it introduces a novel method to balance the load among the cluster heads. Simulation results show that EECS outperforms LEACH significantly with prolonging the network lifetime over 35%.

Establishing pairwise keys in distributed sensor networks

Abstract: Pairwise key establishment is a fundamental security service in sensor networks; it enables sensor nodes to communicate securely with each other using cryptographic techniques. However, due to the resource constraints on sensor nodes, it is not feasible to use traditional key management techniques such as public key cryptography and key distribution center (KDC). A number of key predistribution techniques have been proposed for pairwise key establishment in sensor networks recently. To facilitate the study of novel pairwise key predistribution techniques, this paper develops a general framework for establishing pairwise keys between sensor nodes using bivariate polynomials. This paper then proposes two efficient instantiations of the general framework: a random subset assignment key predistribution scheme, and a hypercube-based key predistribution scheme. The analysis shows that both schemes have a number of nice properties, including high probability, or guarantee to establish pairwise keys, tolerance of node captures, and low storage, communication, and computation overhead. To further reduce the computation at sensor nodes, this paper presents an optimization technique for polynomial evaluation, which is used to compute pairwise keys. This paper also reports the implementation and the performance of the proposed schemes on MICA2 motes running TinyOS, an operating system for networked sensors. The results indicate that the proposed techniques can be applied efficiently in resource-constrained sensor networks.

A Survey of Applications of Wireless Sensors and Wireless Sensor Networks

Abstract: Wireless sensors and wireless sensor networks have come to the forefront of the scientific community recently. This is the consequence of engineering increasingly smaller sized devices, which enable many applications. The use of these sensors and the possibility of organizing them into networks have revealed many research issues and have highlighted new ways to cope with certain problems. In this paper, different applications areas where the use of such sensor networks has been proposed are surveyed

Avrora: scalable sensor network simulation with precise timing

Abstract: Simulation can be an important step in the development of software for wireless sensor networks and has been the subject of intense research in the past decade. While most previous efforts in simulating wireless sensor networks have focused on protocol-level issues utilizing models of the software implementation, a significant challenge remains in precisely measuring time-dependent properties such as radio channel utilization. One promising approach, first demonstrated by ATEMU, is to simulate the behavior of sensor network programs at the machine code level with cycle-accuracy, but poor performance has so far limited its scalability. In this paper we present Avrora, a cycle-accurate instruction-level sensor network simulator which scales to networks of up to 10,000 nodes and performs as much as 20 times faster than previous simulators with equivalent accuracy, handling as many as 25 nodes in real-time. We show how an event queue can enable efficient instruction-level simulation of microcontroller programs and allow the hidden parallelism in finegrained sensor network simulations to be extracted, once two core synchronization problems are identified and solved. Avrora's ability to measure detailed time-critical phenomena can shed new light on design issues for large-scale sensor networks.

On the lifetime of wireless sensor networks

Abstract: We derive a general formula for the lifetime-of wireless sensor networks which holds independently of the underlying network model including network architecture and protocol, data collection initiation, lifetime definition, channel fading characteristics, and energy consumption model. This formula identifies two key parameters at the physical layer that affect the network lifetime: the channel state and the residual energy of sensors. As a result, it provides not only a gauge for performance evaluation of sensor networks but also a guideline for the design of network protocols. Based on this formula, we propose a medium access control protocol that exploits both the channel state information and the residual energy information of individual sensors. Referred to as the max-min approach, this protocol maximizes the minimum residual energy across the network in each data collection.

Wireless Technology in Industrial Networks

Abstract: With the success of wireless technologies in consumer electronics, standard wireless technologies are envisioned for the deployment in industrial environments as well. Industrial applications involving mobile subsystems or just the desire to save cabling make wireless technologies attractive. Nevertheless, these applications often have stringent requirements on reliability and timing. In wired environments, timing and reliability are well catered for by fieldbus systems (which are a mature technology designed to enable communication between digital controllers and the sensors and actuators interfacing to a physical process). When wireless links are included, reliability and timing requirements are significantly more difficult to meet, due to the adverse properties of the radio channels. In this paper, we thus discuss some key issues coming up in wireless fieldbus and wireless industrial communication systems: 1) fundamental problems like achieving timely and reliable transmission despite channel errors; 2) the usage of existing wireless technologies for this specific field of applications; and 3) the creation of hybrid systems in which wireless stations are incorporated into existing wired systems.

Data collection, storage, and retrieval with an underwater sensor network

Abstract: In this paper we present a novel platform for underwater sensor networks to be used for long-term monitoring of coral reefs and fisheries. The sensor network consists of static and mobile underwater sensor nodes. The nodes communicate point-to-point using a novel high-speed optical communication system integrated into the TinyOS stack, and they broadcast using an acoustic protocol integrated in the TinyOS stack. The nodes have a variety of sensing capabilities, including cameras, water temperature, and pressure. The mobile nodes can locate and hover above the static nodes for data muling, and they can perform network maintenance functions such as deployment, relocation, and recovery. In this paper we describe the hardware and software architecture of this underwater sensor network. We then describe the optical and acoustic networking protocols and present experimental networking and data collected in a pool, in rivers, and in the ocean. Finally, we describe our experiments with mobility for data muling in this network.

An energy-efficient unequal clustering mechanism for wireless sensor networks

Abstract: Clustering provides an effective way for prolonging the lifetime of a wireless sensor network. Current clustering algorithms usually utilize two techniques, selecting cluster heads with more residual energy and rotating cluster heads periodically, to distribute the energy consumption among nodes in each cluster and extend the network lifetime. However, they rarely consider the hot spots problem in multihop wireless sensor networks. When cluster heads cooperate with each other to forward their data to the base station, the cluster heads closer to the base station are burdened with heavy relay traffic and tend to die early, leaving areas of the network uncovered and causing network partition. To address the problem, we propose an energy-efficient unequal clustering (EEUC) mechanism for periodical data gathering in wireless sensor networks. It partitions the nodes into clusters of unequal size, and clusters closer to the base station have smaller sizes than those farther away from the base station. Thus cluster heads closer to the base station can preserve some energy for the inter-cluster data forwarding. We also propose an energy-aware multihop routing protocol for the inter-cluster communication. Simulation results show that our unequal clustering mechanism balances the energy consumption well among all sensor nodes and achieves an obvious improvement on the network lifetime

Wireless sensor networks: applications and challenges of ubiquitous sensing

Abstract: Sensor networks offer a powerful combination of distributed sensing, computing and communication. They lend themselves to countless applications and, at the same time, offer numerous challenges due to their peculiarities, primarily the stringent energy constraints to which sensing nodes are typically subjected. The distinguishing traits of sensor networks have a direct impact on the hardware design of the nodes at at least four levels: power source, processor, communication hardware, and sensors. Various hardware platforms have already been designed to test the many ideas spawned by the research community and to implement applications to virtually all fields of science and technology. We are convinced that CAS will be able to provide a substantial contribution to the development of this exciting field.

MoteLab: a wireless sensor network testbed

Abstract: As wireless sensor networks have emerged as a exciting new area of research in computer science, many of the logistical challenges facing those who wish to develop, deploy, and debug applications on realistic large-scale sensor networks have gone unmet. Manually reprogramming nodes, deploying them into the physical environment, and instrumenting them for data gathering is tedious and time-consuming. To address this need we have developed MoteLab, a Web-based sensor network testbed. MoteLab consists of a set of permanently-deployed sensor network nodes connected to a central server which handles re programming and data logging while providing a Web interface for creating and scheduling jobs on the testbed. MoteLab accelerates application deployment by streamlining access to a large, fixed network of real sensor network devices; it accelerates debugging and development by automating data logging, allowing the performance of sensor network software to be evaluated offline Additionally, by providing a Web interface MoteLab allows both local and remote users access to the testbed, and its scheduling and quota system ensure fair sharing. We have developed and deployed MoteLab at Harvard and found ft invaluable for both research and teaching. The MoteLab source is freely available, easy to install, and already in use at several other research institutions. We expect that widespread use of MoteLab will accelerate and improve wireless sensor network research.

Collaborative beamforming for distributed wireless ad hoc sensor networks

Abstract: The performance of collaborative beamforming is analyzed using the theory of random arrays. The statistical average and distribution of the beampattern of randomly generated phased arrays is derived in the framework of wireless ad hoc sensor networks. Each sensor node is assumed to have a single isotropic antenna and nodes in the cluster collaboratively transmit the signal such that the signal in the target direction is coherently added in the far-field region. It is shown that with N sensor nodes uniformly distributed over a disk, the directivity can approach N, provided that the nodes are located sparsely enough. The distribution of the maximum sidelobe peak is also studied. With the application to ad hoc networks in mind, two scenarios (closed-loop and open-loop) are considered. Associated with these scenarios, the effects of phase jitter and location estimation errors on the average beampattern are also analyzed.

The coverage problem in a wireless sensor network

Abstract: One of the fundamental issues in sensor networks is the coverage problem, which reflects howwell a sensor network is monitored or tracked by sensors. In this paper, we formulate this problem as a decision problem, whose goal is to determine whether every point in the service area of the sensor network is covered by at least k sensors, where k is a given parameter. The sensing ranges of sensors can be unit disks or non-unit disks. We present polynomial-time algorithms, in terms of the number of sensors, that can be easily translated to distributed protocols. The result is a generalization of some earlier results where only k =1 is assumed. Applications of the result include determining insufficiently covered areas in a sensor network, enhancing fault-tolerant capability in hostile regions, and conserving energies of redundant sensors in a randomly deployed network. Our solutions can be easily translated to distributed protocols to solve the coverage problem.

Mobility improves coverage of sensor networks

Abstract: Previous work on the coverage of mobile sensor networks focuses on algorithms to reposition sensors in order to achieve a static configuration with an enlarged covered area. In this paper, we study the dynamic aspects of the coverage of a mobile sensor network that depend on the process of sensor movement. As time goes by, a position is more likely to be covered; targets that might never be detected in a stationary sensor network can now be detected by moving sensors. We characterize the area coverage at specific time instants and during time intervals, as well as the time it takes to detect a randomly located stationary target. Our results show that sensor mobility can be exploited to compensate for the lack of sensors and improve network coverage. For mobile targets, we take a game theoretic approach and derive optimal mobility strategies for sensors and targets from their own perspectives.

Prolonging the lifetime of wireless sensor networks via unequal clustering

Abstract: Organizing wireless sensor networks into clusters enables the efficient utilization of the limited energy resources of the deployed sensor nodes However, the problem of unbalanced energy consumption exists, and it is tightly bound to the role and to the location of a particular node in the network If the network is organized into heterogeneous clusters, where some more powerful nodes take on the cluster head role to control network operation, it is important to ensure that energy dissipation of these cluster head nodes is balanced Oftentimes the network is organized into clusters of equal size, but such equal clustering results in an unequal load on the cluster head nodes Instead, we propose an unequal clustering size (UCS) model for network organization, which can lead to more uniform energy dissipation among the cluster head nodes, thus increasing network lifetime Also, we expand this approach to homogeneous sensor networks and show that UCS can lead to more uniform energy dissipation in a homogeneous network as well

Cluster-head election using fuzzy logic for wireless sensor networks

Abstract: Wireless sensor networks (WSNs) present a new generation of real-time embedded systems with limited computation, energy and memory resources that are being used in a wide variety of applications where traditional networking infrastructure is practically infeasible. Appropriate cluster-head node election can drastically reduce the energy consumption and enhance the lifetime of the network. In this paper, a fuzzy logic approach to cluster-head election is proposed based on three descriptors-energy, concentration and centrality. Simulation shows that depending upon network configuration, a substantial increase in network lifetime can be accomplished as compared to probabilistically selecting the nodes as cluster-heads using only local information.