Duty cycle learning algorithm (DCLA) for IEEE 802.15.4 beacon-enabled wireless sensor networks

The current specification of the IEEE 802.15.4 standard for beacon-enabled wireless sensor networks does not define how the fraction of the time that wireless nodes are active, known as the duty cycle, needs to be configured in order to achieve the optimal network performance in all traffic conditions. The work presented here proposes a duty cycle learning algorithm (DCLA) that adapts the duty cycle during run time without the need of human intervention in order to minimise power consumption while balancing probability of successful data delivery and delay constraints of the application. Running on coordinator devices, DCLA collects network statistics during each active duration to estimate the incoming traffic. Then, at each beacon interval uses the reinforcement learning (RL) framework as the method for learning the best duty cycle. Our approach eliminates the necessity for manually (re-)configuring the nodes duty cycle for the specific requirements of each network deployment. This presents the advantage of greatly reducing the time and cost of the wireless sensor network deployment, operation and management phases. DCLA has low memory and processing requirements making it suitable for typical wireless sensor platforms. Simulations show that DCLA achieves the best overall performance for either constant and event-based traffic when compared with existing IEEE 802.15.4 duty cycle adaptation schemes.     

Localized algorithms for coverage boundary detection in wireless sensor networks

Connected coverage, which reflects how well a target field is monitored under the base station, is the most important performance metric used to measure the quality of surveillance that wireless sensor networks (WSNs) can provide. To facilitate the measurement of this metric, we propose two novel algorithms for individual sensor nodes to identify whether they are on the coverage boundary, i.e., the boundary of a coverage hole or network partition. Our algorithms are based on two novel computational geometric techniques called localized Voronoi and neighbor embracing polygons. Compared to previous work, our algorithms can be applied to WSNs of arbitrary topologies. The algorithms are fully distributed in the sense that only the minimal position information of one-hop neighbors and a limited number of simple local computations are needed, and thus are of high scalability and energy efficiency. We show the correctness and efficiency of our algorithms by theoretical proofs and extensive simulations. Chi Zhang received the B.E. and M.E. degrees in Electrical Engineering from Huazhong University of Science and Technology, Wuhan, China, in July 1999 and January 2002, respectively. Since September 2004, he has been working towards the Ph.D. degree in the Department of Electrical and Computer Engineering at the University of Florida, Gainesville, Florida, USA. His research interests are network and distributed system security, wireless networking, and mobile computing, with emphasis on mobile ad hoc networks, wireless sensor networks, wireless mesh networks, and heterogeneous wired/wireless networks. Yanchao Zhang received the B.E. degree in computer communications from Nanjing University of Posts and Telecommunications, Nanjing, China, in July 1999, the M.E. degree in computer applications from Beijing University of Posts and Telecommunications, Beijing, China, in April 2002, and the Ph.D. degree in electrical and computer engineering from the University of Florida, Gainesville, in August 2006. Since September 2006, he has been an Assistant Professor in the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark. His research interest include wireless and Internet security, wireless networking, and mobile computing. He is a member of the IEEE and ACM. Yuguang Fang received the BS and MS degrees in Mathematics from Qufu Normal University, Qufu, Shandong, China, in 1984 and 1987, respectively, a Ph.D. degree in Systems and Control Engineering from Department of Systems, Control and Industrial Engineering at Case Western Reserve University, Cleveland, Ohio, in January 1994, and a Ph.D. degree in Electrical Engineering from Department of Electrical and Computer Engineering at Boston University, Massachusetts, in May 1997. From 1987 to 1988, he held research and teaching position in both Department of Mathematics and the Institute of Automation at Qufu Normal University. From September 1989 to December 1993, he was a teaching/research assistant in Department of Systems, Control and Industrial Engineering at Case Western Reserve University, where he held a research associate position from January 1994 to May 1994. He held a post-doctoral position in Department of Electrical and Computer Engineering at Boston University from June 1994 to August 1995. From September 1995 to May 1997, he was a research assistant in Department of Electrical and Computer Engineering at Boston University. From June 1997 to July 1998, he was a Visiting Assistant Professor in Department of Electrical Engineering at the University of Texas at Dallas. From July 1998 to May 2000, he was an Assistant Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology, Newark, New Jersey. In May 2000, he joined the Department of Electrical and Computer Engineering at University of Florida, Gainesville, Florida, where he got early promotion to Associate Professor with tenure in August 2003, and to Full Professor in August 2005. His research interests span many areas including wireless networks, mobile computing, mobile communications, wireless security, automatic control, and neural networks. He has published over one hundred and fifty (150) papers in refereed professional journals and conferences. He received the National Science Foundation Faculty Early Career Award in 2001 and the Office of Naval Research Young Investigator Award in 2002. He also received the 2001 CAST Academic Award. He is listed in Marquis Who’s Who in Science and Engineering, Who’s Who in America and Who’s Who in World. Dr. Fang has actively engaged in many professional activities. He is a senior member of the IEEE and a member of the ACM. He is an Editor for IEEE Transactions on Communications, an Editor for IEEE Transactions on Wireless Communications, an Editor for IEEE Transactions on Mobile Computing, an Editor for ACM Wireless Networks, and an Editor for IEEE Wireless Communications. He was an Editor for IEEE Journal on Selected Areas in Communications:Wireless Communications Series, an Area Editor for ACM Mobile Computing and Communications Review, an Editor for Wiley International Journal on Wireless Communications and Mobile Computing, and Feature Editor for Scanning the Literature in IEEE Personal Communications. He has also actively involved with many professional conferences such as ACM MobiCom’02 (Committee Co-Chair for Student Travel Award), MobiCom’01, IEEE INFOCOM’06, INFOCOM’05 (Vice-Chair for Technical Program Committee), INFOCOM’04, INFOCOM’03, INFOCOM’00, INFOCOM’98, IEEE WCNC’04, WCNC’02, WCNC’00 Technical Program Vice-Chair), WCNC’99, IEEE Globecom’04 (Symposium Co-Chair), Globecom’02, and International Conference on Computer Communications and Networking (IC3N) (Technical Program Vice-Chair).     

MST-based clustering topology control algorithm for wireless sensor networks

In this paper, we propose a novel clustering topology control algorithm named Minimum Spanning Tree (MST)-based Clustering Topology Control (MCTC) for Wireless Sensor Networks (WSNs), which uses a hybrid approach to adjust sensor nodes’ transmission power in two-tiered hierarchical WSNs. MCTC algorithm employs a one-hop Maximum Energy &; Minimum Distance (MEMD) clustering algorithm to decide clustering status. Each cluster exchanges information between its own Cluster Members (CMs) locally and then deliveries information to the Cluster Head (CH). Moreover, CHs exchange information between CH and CH and afterwards transmits aggregated information to the base station finally. The intra-cluster topology control scheme uses MST to decide CMs’ transmission radius, similarly, the inter-cluster topology control scheme applies MST to decide CHs’ transmission radius. Since the intra-cluster topology control is a full distributed approach and the inter-cluster topology control is a pure centralized approach performed by the base station, therefore, MCTC algorithm belongs to one kind of hybrid clustering topology control algorithms and can obtain scalability topology and strong connectivity guarantees simultaneously. As a result, the network topology will be reduced by MCTC algorithm so that network energy efficiency will be improved. The simulation results verify that MCTC outperforms traditional topology control schemes such as LMST, DRNG and MEMD at the aspects of average node’s degree, average node’s power radius and network lifetime, respectively.     

An efficient UE cluster head selection algorithm in wireless sensor networks and cellular networks

Wireless Sensor Networks (WSNs) have been applied in many different areas. Energy efficient algorithms and protocols have become one of the most challenging issues for WSN. Many researchers focused on developing energy efficient clustering algorithms for WSN, but less research has been concerned in the mobile User Equipment (UE) acting as a Cluster Head (CH) for data transmission between cellular networks and WSNs. In this paper, we propose a cellular-assisted UE CH selection algorithm for the WSN, which considers several parameters to choose the optimal UE gateway CH. We analyze the energy cost of data transmission from a sensor node to the next node or gateway and calculate the whole system energy cost for a WSN. Simulation results show that better system performance, in terms of system energy cost and WSNs life time, can be achieved by using interactive optimization with cellular networks.     

InRout - A QoS aware route selection algorithm for industrial wireless sensor networks

Wireless sensor networks are a key enabling technology for industrial monitoring applications where the use of wireless infrastructure allows high adaptivity and low cost in terms of installation and retrofitting. To facilitate the move from the current wired designs to wireless designs, concerns regarding reliability must be satisfied. Current standardization efforts for industrial wireless systems lack specification on efficient routing protocols that mitigate reliability concerns. Consequently, this work presents the InRout route selection algorithm, where local information is shared among neighbouring nodes to enable efficient, distributed route selection while satisfying industrial application requirements and considering sensor node resource limitations. Route selection is described as a multi-armed bandit task and uses Q-learning techniques to obtain the best available solution with low overhead. A performance comparison with existing approaches demonstrates the benefits of the InRout algorithm, which satisfies typical quality of service requirements for industrial monitoring applications while considering sensor node resources. Simulation results show that InRout can provide gains ranging from 4% to 60% in the number of successfully delivered packets when compared to current approaches with much lower control overhead.     

QoS evaluation of energy-efficient ML-MAC protocol for wireless sensor networks

Power management is an important issue in wireless sensor networks (WSNs) because wireless sensor nodes are usually battery powered, and an efficient use of the available battery power becomes an important concern specially for those applications where the system is expected to operate for long durations. This necessity for energy efficient operation of a WSN has prompted the development of new protocols in all layers of the communication stack. If the radio transceiver is the most power consuming component of a typical sensor node, large gains can be achieved at the link layer where the medium access control (MAC) protocol controls the usage of the radio transceiver unit.     

FP-MAC: A distributed MAC algorithm for 802.15.4-like wireless sensor networks

In this paper we focus on the problems of high latency and low throughput arising from the periodic operation of MAC protocols for wireless sensor networks. In order to meet both design criteria we propose an energy-efficient, low delay, fast-periodic MAC algorithm, namely FP-MAC, that is exclusively designed for 802.15.4-like networks utilizing in full the standard’s physical layer. Our proposal relies on the short periodic communication operation of the nodes comprising the WSN. This is achieved by decreasing the actions that a node needs to perform at the start of every communication period and by incorporating a variable radio-on operation. Moreover, the algorithm introduces differences in nodes’ scheduling to further reduce delay. Local synchronization and the crucial task of determining the proper timing for transmission and reception of data is achieved through the periodic broadcast of special synchronization frames at the beginning of each on-period. FP-MAC is evaluated and compared to S-MAC and T-MAC through extensive simulations, showing a significant improvement in terms of low energy consumption and average MAC delay.     

Energy Efficient Non-uniform Clustering Division Scheme in Wireless Sensor Networks

Wireless sensor networks can be used to monitor the interested region by multi-hop communication. Since sensor nodes are equipped with energy-limited batteries, energy conservation in such networks is of paramount importance in order to prolong the network lifetime. In this paper, considering the constrained radio range of node, we propose an energy efficient clustering division scheme from the viewpoint of energy consumption. The difference between our scheme and previous schemes is that ours is a non-uniform clustering hierarchy. With the algorithm that is proposed by this paper, we can divide the cluster into multiple non-uniform concentric rings and obtain the optimal thickness of each ring. Motivated by the derived results, every sensor node can adjust its radio range for transmission. Our extensive simulation results indicate that the proposed non-uniform clustering division scheme outperforms the conventional uniform clustering division schemes in terms of energy consumption and lifetime. The future research that should be explored is also discussed finally.

Energy balanced data propagation in wireless sensor networks

We study the problem of energy-balanced data propagation in wireless sensor networks. The energy balance property guarantees that the average per sensor energy dissipation is the same for all sensors in the network, during the entire execution of the data propagation protocol. This property is important since it prolongs the network’:s lifetime by avoiding early energy depletion of sensors. We propose a new algorithm that in each step decides whether to propagate data one-hop towards the final destination (the sink), or to send data directly to the sink. This randomized choice balances the (cheap) one-hop transimssions with the direct transimissions to the sink, which are more expensive but “bypass” the sensors lying close to the sink. Note that, in most protocols, these close to the sink sensors tend to be overused and die out early. By a detailed analysis we precisely estimate the probabilities for each propagation choice in order to guarantee energy balance. The needed estimation can easily be performed by current sensors using simple to obtain information. Under some assumptions, we also derive a closed form for these probabilities. The fact (shown by our analysis) that direct (expensive) transmissions to the sink are needed only rarely, shows that our protocol, besides energy-balanced, is also energy efficient. This work has been partially supported by the IST/FET/GC Programme of the European Union under contract numbers IST-2001-33135 (CRESCCO) and 6FP 001907 (DELIS). A perliminary version of the work appeared in WMAN 2004 [11]. Charilaos Efthymiou graduated form the Computer Engineering and Informatics Department (CEID) of the University of Patras, Greece. He received his MSc from the same department with advisor in S. Nikoletseas. He currently continuous his Ph.D studies in CEID with advisor L. Kirousis. His research interest include Probabilistic Techniques and Random Graphs, Randomized Algorithms in Computationally Hard Problems, Stochastic Processes and its Applications to Computer Science. Dr. Sotiris Nikoletseas is currently a Senior Researcher and Managing Director of Research Unit 1 (“Foundations of Computer Science, Relevant Technologies and Applications”) at the Computer Technology Institute (CTI), Patras, Greece and also a Lecturer at the Computer Engineering and Informatics Department of Patras University, Greece. His research interests include Probabilistic Techniques and Random Graphs, Average Case Analysis of Graph Algorithms and Randomized Algorithms, Fundamental Issues in Parallel and Distributed Computing, Approximate Solutions to Computationally Hard Problems. He has published scientific articles in major international conferences and journals and has co-authored (with Paul Spirakis) a book on Probabilistic Techniques. He has been invited speaker in important international scientific events and Universities. He has been a referee for the Theoretical Computer Science (TCS) Journal and important international conferences (ESA, ICALP). He has participated in many EU funded R&D projects (ESPRIT/ALCOM-IT, ESPRIT/GEPPCOM). He currently participates in 6 Fifth Framework projects: ALCOM-FT, ASPIS, UNIVERSAL, EICSTES (IST), ARACNE, AMORE (IMPROVING). Jose Rolim is Full Professor at the Department of Computer Science of the University of Geneva where he leads the Theoretical Computer Science and Sensor Lab (TCSensor Lab). He received his Ph.D. degree in Computer Science at the University of California, Los Angeles working together with Prof. S. Greibach. He has published several articles on the areas of distributed systems, randomization and computational complexity and leads two major projects on the area of Power Aware Computing and Games and Complexity, financed by the Swiss National Science Foundation. Prof. Rolim participates in the editorial board of several journals and conferences and he is the Steering Committee Chair and General Chair of the IEEE Distributed Computing Conference in Sensor Systems.     

Location and calculation-free node-scheduling schemes in large wireless sensor networks

In wireless sensor networks that consist of a large number of low-power, short-lived, unreliable sensors, one of the main design challenges is to obtain long system lifetime without sacrificing system original performance (sensing coverage and sensing reliability). To solve this problem, one of the potential approaches is to identify redundant nodes at the sensing interface and then assign them an off-duty operation mode that has lower energy consumption than the normal on-duty mode. In our previous work [J. Wireless Commun. Mobile Comput. 3 (2003) 271; Processing of ACM Wireless Sensor Network and Application Workshop 2002, September 2002], we proposed a node-scheduling scheme, which can provide a 100% sensing coverage preservation capability. This, however, requires each node to be aware of its own and its neighbors’ location information. Also, in that scheme, each node has to do accurate geometrical calculation to determine whether to take an off-duty status. In this paper, we propose and study several alternative node-scheduling schemes, which cannot completely preserve the original system coverage, but are nonetheless light-weighted and flexible compared with the previous one. Our simulation results compare these schemes with the previous one and demonstrate their effectiveness.     

A local dynamic cluster self-organization algorithm in wireless sensor networks for rainfall monitoring

Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring, which could be controlled deployment. Delivery delay and cross-cluster calculation leads to information inaccuracy by the existing dynamic collaborative self-organization algorithm in WSNs. In this letter, a Local Dynamic Cluster Self-organization algorithm (LDCS) is proposed for the large-scale regional and moving target monitoring in RM-WSNs. The algorithm utilizes the resource-rich node in WSNs as the cluster head, which processes target information obtained by sensor nodes in cluster. The cluster head shifts with the target moving in chance and re-groups a new cluster. The target information acquisition is limited in the dynamic cluster, which can reduce information across-clusters transfer delay and improve the real-time of information acquisition. The simulation results show that, LDCS can not only relieve the problem of “too frequent leader switches” in IDSQ, also make full use of the history monitoring information of target and continuous monitoring of sensor nodes that failed in DCS.     

Aging analysis in large-scale wireless sensor networks

Most research on the lifetime of wireless sensor networks has focused primarily on the energy depletion of the very first node. In this study, we analyze the entire aging process of the sensor network in a periodic data gathering application. In sparse node deployments, it is observed that the existence of multiple alternate paths to a sink leads to a power law relation between connectivity to a sink and hop levels, where the probability of connection to a sink decreases in proportion to the hop level with an exponent, when device failures occur over time. Then, we provide distance-level analysis for the dense deployment case by taking into account the re-construction of a data gathering tree and workload shift caused by the energy depletion of nodes with larger workload. Extensive simulation results obtained with a realistic wireless link model are compared to our analytical results. Finally, we show through an analysis of the aging of first-hop nodes that increasing node density with a fixed radio range does not affect the network disconnection time.     

A lightweight intrusion detection framework for wireless sensor networks

In recent years, Wireless Sensor Networks (WSNs) have demonstrated successful applications for both civil and military tasks. However, sensor networks are susceptible to multiple types of attacks because they are randomly deployed in open and unprotected environments. It is necessary to utilize effective mechanisms to protect sensor networks against multiple types of attacks on routing protocols. In this paper, we propose a lightweight intrusion detection framework integrated for clustered sensor networks. Furthermore, we provide algorithms to minimize the triggered intrusion modules in clustered WSNs by using an over‐hearing mechanism to reduce the sending alert packets. Our scheme can prevent most routing attacks on sensor networks. In in‐depth simulation, the proposed scheme shows less energy consumption in intrusion detection than other schemes. Copyright © 2009 John Wiley & Sons, Ltd.     

A dual-mode energy efficient encryption protocol for wireless sensor networks

This paper presents a novel link-layer encryption protocol for wireless sensor networks. The protocol design aims to reduce energy consumption by reducing security related communication overhead. This is done by merging security related data of consecutive packets. The merging (or combining packets) based on simple mathematical operations helps to reduce energy consumption by eliminating the requirement to send security related fields in headers and trailers. We name our protocol as the Compact Security Protocol referred to as C-Sec. In addition to energy savings, the C-Sec protocol also includes a unique security feature of hiding the packet header information. This feature makes it more difficult to trace the flow of wireless communication, and helps to minimize the cost of defending against replay attacks. We performed rigorous testing of the C-Sec protocol and compared it with well-known protocols including TinySec, MiniSec, SNEP and Zigbee. Our performance evaluation demonstrates that the C-Sec protocol outperforms other protocols in terms of energy savings. We also evaluated our protocol with respect to other performance metrics including queuing delay and error probability.     

Relay sensor placement in wireless sensor networks

This paper addresses the following relay sensor placement problem: given the set of duty sensors in the plane and the upper bound of the transmission range, compute the minimum number of relay sensors such that the induced topology by all sensors is globally connected. This problem is motivated by practically considering the tradeoff among performance, lifetime, and cost when designing sensor networks. In our study, this problem is modelled by a NP-hard network optimization problem named Steiner Minimum Tree with Minimum number of Steiner Points and bounded edge length (SMT-MSP). In this paper, we propose two approximate algorithms, and conduct detailed performance analysis. The first algorithm has a performance ratio of 3 and the second has a performance ratio of 2.5. Xiuzhen Cheng is an Assistant Professor in the Department of Computer Science at the George Washington University. She received her MS and PhD degrees in Computer Science from the University of Minnesota - Twin Cities in 2000 and 2002, respectively. Her current research interests include Wireless and Mobile Computing, Sensor Networks, Wireless Security, Statistical Pattern Recognition, Approximation Algorithm Design and Analysis, and Computational Medicine. She is an editor for the International Journal on Ad Hoc and Ubiquitous Computing and the International Journal of Sensor Networks. Dr. Cheng is a member of IEEE and ACM. She received the National Science Foundation CAREER Award in 2004. Ding-Zhu Du received his M.S. degree in 1982 from Institute of Applied Mathematics, Chinese Academy of Sciences, and his Ph.D. degree in 1985 from the University of California at Santa Barbara. He worked at Mathematical Sciences Research Institutea, Berkeley in 1985-86, at MIT in 1986-87, and at Princeton University in 1990-91. He was an associate-professor/professor at Department of Computer Science and Engineering, University of Minnesota in 1991-2005, a professor at City University of Hong Kong in 1998-1999, a research professor at Institute of Applied Mathematics, Chinese Academy of Sciences in 1987-2002, and a Program Director at National Science Foundation of USA in 2002-2005. Currently, he is a professor at Department of Computer Science, University of Texas at Dallas and the Dean of Science at Xi’an Jiaotong University. His research interests include design and analysis of algorithms for combinatorial optimization problems in communication networks and bioinformatics. He has published more than 140 journal papers and 10 written books. He is the editor-in-chief of Journal of Combinatorial Optimization and book series on Network Theory and Applications. He is also in editorial boards of more than 15 journals. Lusheng Wang received his PhD degree from McMaster University in 1995. He is an associate professor at City University of Hong Kong. His research interests include networks, algorithms and Bioinformatics. He is a member of IEEE and IEEE Computer Society. Baogang Xu received his PhD degree from Shandong University in 1997. He is a professor at Nanjing Normal University. His research interests include graph theory and algorithms on graphs.     

Connected sensor cover for area information coverage in wireless sensor networks

Coverage is an important issue in wireless sensor networks (WSNs) and is often used to measure how well a sensor field is monitored by the deployed sensors. If the area covered by a sensor can also be covered by some other sensors, this sensor can go into an energy‐saving sleep state without sacrificing the coverage requirement. In this paper, we study the problem of how to select active sensors with the constraints that the selected active sensors can provide complete field coverage and are completely connected. We propose to use the notion of information coverage, which is based on estimation theory to exploit the collaborative nature of WSNs, instead of using the conventional definition of coverage. Owing to the use of information coverage, a point that is not within the sensing disk of any sensor can still be considered to be covered without loss of estimation reliability. We propose a heuristic to approximately solve our problem. The basic idea is to grow a connected sensor tree to maximize the profit from the covered points of the selected sensors in each step. Simulations are used to validate the effectiveness of the proposed algorithm and the results illustrate that the number of active sensors to provide area coverage can be greatly reduced by using the notion of information coverage compared with that by using the conventional definition of coverage. Copyright © 2008 John Wiley & Sons, Ltd.     

TinyPEDS: Tiny persistent encrypted data storage in asynchronous wireless sensor networks

In wireless sensor networks there is a need to securely store monitored data in a distributed way whenever it is either not desired or simply not possible to transmit regional volatile information to an authorised recipient in real-time. In particular, for wireless sensor network applications with an asynchronous character, the wireless sensor network itself needs to store the monitored data. Since nodes may disappear over time, a replicated and read-protected, but yet space- and energy-efficient, data storage is mandatory. In this work we provide and analyse an approach for a tiny Persistent Encrypted Data Storage (tinyPEDS) of the environmental fingerprint for asynchronous wireless sensor networks. Even if parts of the network are exhausted, restoring rules ensure that, with a high probability, environmental information from past is still available.     

Energy-efficient collaborative target tracking algorithm using cost-reference particle filtering in wireless acoustic sensor networks

Target tracking is one of the most important applications of wireless sensor networks. Optimized computation and energy dissipation are critical requirements to save the limited resource of sensor nodes. A new robust and energy-efficient collaborative target tracking framework is proposed in this article. After a target is detected, only one active cluster is responsible for the tracking task at each time step. The tracking algorithm is distributed by passing the sensing and computation operations from one cluster to another. An event-driven cluster reforming scheme is also proposed for balancing energy consumption among nodes. Observations from three cluster members are chosen and a new class of particle filter termed cost-reference particle filter (CRPF) is introduced to estimate the target motion at the cluster head. This CRPF method is quite robust for wireless sensor network tracking applications because it drops the strong assumptions of knowing the probability distributions of the system process and observation noises. In simulation experiments, the performance of the proposed collaborative target tracking algorithm is evaluated by the metrics of tracking precision and network energy consumption.     

Energy-efficiency clustering protocol in wireless sensor networks

The conventional clustering method has the unique potential to be the framework for power-conserving ad hoc networks. In this environment, studies on energy-efficient strategies such as sleeping mode and redirection have been reported, and recently some have even been adopted by some standards like Bluetooth and IEEE 802.11. However, consider wireless sensor networks. The devices employed are power-limited in nature, introducing the conventional clustering approach to the sensor networks provides a unique challenge due to the fact that cluster-heads, which are communication centers by default, tend to be heavily utilized and thus drained of their battery power rapidly. In this paper, we introduce a re-clustering strategy and a redirection scheme for cluster-based wireless sensor networks in order to address the power-conserving issues in such networks, while maintaining the merits of a clustering approach. Based on a practical energy model, simulation results show that the improved clustering method can obtain a longer lifetime when compared with the conventional clustering method.     

Controlled sink mobility for prolonging wireless sensor networks lifetime

This paper demonstrates the advantages of using controlled mobility in wireless sensor networks (WSNs) for increasing their lifetime, i.e., the period of time the network is able to provide its intended functionalities. More specifically, for WSNs that comprise a large number of statically placed sensor nodes transmitting data to a collection point (the sink), we show that by controlling the sink movements we can obtain remarkable lifetime improvements. In order to determine sink movements, we first define a Mixed Integer Linear Programming (MILP) analytical model whose solution determines those sink routes that maximize network lifetime. Our contribution expands further by defining the first heuristics for controlled sink movements that are fully distributed and localized. Our Greedy Maximum Residual Energy (GMRE) heuristic moves the sink from its current location to a new site as if drawn toward the area where nodes have the highest residual energy. We also introduce a simple distributed mobility scheme (Random Movement or RM) according to which the sink moves uncontrolled and randomly throughout the network. The different mobility schemes are compared through extensive ns2-based simulations in networks with different nodes deployment, data routing protocols, and constraints on the sink movements. In all considered scenarios, we observe that moving the sink always increases network lifetime. In particular, our experiments show that controlling the mobility of the sink leads to remarkable improvements, which are as high as sixfold compared to having the sink statically (and optimally) placed, and as high as twofold compared to uncontrolled mobility. Stefano Basagni holds a Ph.D. in electrical engineering from the University of Texas at Dallas (December 2001) and a Ph.D. in computer science from the University of Milano, Italy (May 1998). He received his B.Sc. degree in computer science from the University of Pisa, Italy, in 1991. Since Winter 2002 he is on faculty at the Department of Electrical and Computer Engineering at Northeastern University, in Boston, MA. From August 2000 to January 2002 he was professor of computer science at the Department of Computer Science of the Erik Jonsson School of Engineering and Computer Science, The University of Texas at Dallas. Dr. Basagni’s current research interests concern research and implementation aspects of mobile networks and wireless communications systems, Bluetooth and sensor networking, definition and performance evaluation of network protocols and theoretical and practical aspects of distributed algorithms. Dr. Basagni has published over four dozens of referred technical papers and book chapters. He is also co-editor of two books. Dr. Basagni served as a guest editor of the special issue of the Journal on Special Topics in Mobile Networking and Applications (MONET) on Multipoint Communication in Wireless Mobile Networks, of the special issue on mobile ad hoc networks of the Wiley’s Interscience’s Wireless Communications & Mobile Networks journal, and of the Elsevier’s journal Algorithmica on algorithmic aspects of mobile computing and communications. Dr. Basagni serves as a member of the editorial board and of the technical program committee of ACM and IEEE journals and international conferences. He is a senior member of the ACM (including the ACM SIGMOBILE), senior member of the IEEE (Computer and Communication societies), and member of ASEE (American Society for Engineering Education). Alessio Carosi received the M.S. degree “summa cum laude” in Computer Science in 2004 from Rome University “La Sapienza.” He is currently a Ph.D. candidate in Computer Science at Rome University “La Sapienza.” His research interests include protocols for ad hoc and sensor networks, underwater systems and delay tolerant networking. Emanuel Melachrinoudis received the Ph.D. degree in industrial engineering and operations research from the University of Massachusetts, Amherst, MA. He is currently the Director of Industrial Engineering and Associate Chairman of the Department of Mechanical and Industrial Engineering at Northeastern University, Boston, MA. His research interests are in the areas of network optimization and multiple criteria optimization with applications to telecommunication networks, distribution networks, location and routing. He is a member of the Editorial Board of the International Journal of Operational Research. He has published in journals such as Management Science, Transportation Science, Networks, European Journal of Operational Research, Naval Research Logistics and IIE Transactions. Chiara Petrioli received the Laurea degree “summa cum laude” in computer science in 1993, and the Ph.D. degree in computer engineering in 1998, both from Rome University “La Sapienza,” Italy. She is currently Associate Professor with the Computer Science Department at Rome University “La Sapienza.” Her current work focuses on ad hoc and sensor networks, Delay Tolerant Networks, Personal Area Networks, Energy-conserving protocols, QoS in IP networks and Content Delivery Networks where she contributed around sixty papers published in prominent international journals and conferences. Prior to Rome University she was research associate at Politecnico di Milano and was working with the Italian Space agency (ASI) and Alenia Spazio. Dr. Petrioli was guest editor of the special issue on “Energy-conserving protocols in wireless Networks” of the ACM/Kluwer Journal on Special Topics in Mobile Networking and Applications (ACM MONET) and is associate editor of IEEE Transactions on Vehicular Technology, the ACM/Kluwer Wireless Networks journal, the Wiley InterScience Wireless Communications & Mobile Computing journal and the Elsevier Ad Hoc Networks journal. She has served in the organizing committee and technical program committee of several leading conferences in the area of networking and mobile computing including ACM Mobicom, ACM Mobihoc, IEEE ICC,IEEE Globecom. She is member of the steering committee of ACM Sensys and of the international conference on Mobile and Ubiquitous Systems: Networking and Services (Mobiquitous) and serves as member of the ACM SIGMOBILE executive committee. Dr. Petrioli was a Fulbright scholar. She is a senior member of IEEE and a member of ACM. Z. Maria Wang received her Bachelor degree in Electrical Engineering with the highest honor from Beijing Institute of Light Industry in China, her M.S. degree in Industrial Engineering/Operations Research from Dalhousie University, Canada and her Ph.D. in Industrial Engineering/Operations Research from Northeastern University, Boston. She served as a R&D Analyst for General Dynamics. Currently MS. Wang serves as an Optimization Analyst with Nomis Solutions, Inc.