Prolonging the lifetime of wireless sensor networks by cross-layer interaction

This article presents a cross-layered approach for networking in wireless sensor networks. WSNs differ greatly from traditional ad hoc wireless networks and therefore require the use of new types of network protocols that are energy-efficient to ensure a node lifetime of several years on a single battery and can operate without assistance of central managers in a dynamic network topology. We show that a tightly integrated set of networking protocols is a good solution to reach the target of highly energy-efficient WSNs. Our approach combines medium access organization with routing.     

Prolonging the lifetime of wireless sensor networks by utilizing feedback control

A new algorithm aiming to prolong the lifetime of wireless sensor networks (WSNs) is proposed to balance energy depletion. Using a feedback control combined with a discrete nonlinear programming method to adjust the transmission radii of sensor nodes located in different locations, makes network load redistribution possible and balances energy consumption, further prolongs the lifetime of the entire network. A data distribution model which specific to WSNs with sensor nodes that can adjust transmission radii is proposed to analyze the load spread of the network. This model contributes to predicting and analyzing energy consumption balance effectively. Compared with two other algorithms, dynamic transmission range adjustment and SP, respectively, the experimental results show that the proposed algorithm can lengthen the lifetime of WSNs by up to 22.7 and 27.2 %.     

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.     

Prolonging lifetime for wireless rechargeable sensor networks through sleeping and charging scheduling

Prolonging network lifetime is a fundamental requirement in wireless sensor network (WSN). Existing charging scheduling algorithms suffer from high node redundancy and energy consumption issues. In this paper, we study WSN charging problem from the perspectives of energy conservation combined with energy replenishment scheduling. Firstly, we detect the redundant nodes whose energy is wasted in the network functionality and develop a K‐covering redundant nodes sleeping scheduling algorithm (KRSS) for reducing energy. Secondly, we employed multiple wireless charging vehicles (WCVs) for energy replenishment and optimize the charging scheduling algorithm to prevent any exhaustion of nodes, and we proposed a distance and energy–oriented charging scheduling algorithm (DECS) with multiple WCVs. Simulation experiments are conducted to show the advantages of the proposed KRSS+DECS, confirming that our scheme is capable of removing redundant nodes, lowering node failures, and prolonging network lifetime.     

A myopic mobile sink migration strategy for maximizing lifetime of wireless sensor networks

Network lifetime maximization is challenging particularly for large-scale wireless sensor networks. The sensor nodes near the sink node tend to suffer high energy consumption due to heavy traffic relay operations, becoming vulnerable to energy depletion. The rationale of the sink mobility approach is that as the sink node moves around, such risk of energy depletion at some nodes can be alleviated. In this paper, we first obtain the optimal mobile sink sojourning pattern by solving a linear programming model and then we mathematically analyze why the optimal solution exhibits such sojourning pattern. We use the insights from this analysis to design a simple practical heuristic algorithm for sink mobility, which utilizes only local information. Our heuristic is very different from the existing algorithms which often use the traffic volume as the main decision factor, in that we consider the variance of residual energy of neighboring sensor nodes. The simulation results show that our scheme achieves near-optimal network lifetime even with the relatively low moving speed of the mobile sink.     

On the lifetime of wireless sensor networks

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.     

Reliability and lifetime modeling of wireless sensor nodes

The accuracy of system reliability analysis depends not only on system-level model construction, but also on realistic estimation of failure parameters at the component-level. In this paper, we model and evaluate the reliability and lifetime of a wireless sensor node under three typical working scenarios, contributing toward the accurate reliability analysis of wireless sensor network systems. According to the medium access control (MAC) protocols, the three working scenarios are defined based on the sensor node modes (sleep and active) and the mechanism of alternating between the modes. Reliability and lifetime of wireless sensor nodes under these three scenarios are illustrated and compared through numerical examples.     

Increasing lifetime of wireless sensor networks using controllable mobile cluster heads

In a static wireless sensor network (WSN), sensors close to the base station (BS) run out of energy at a much faster rate than sensors in other parts of the network. This is because the sensor close to the BS always relays the data for other sensors, resulting in an unequal distribution of network residual energy. In this paper, we propose a scheme for enhancing the network lifetime using multiple mobile cluster heads (CHs) that can move in the WSN in a controllable manner. The CH controllably moves toward the energy‐rich sensors or the event area, offering the benefits of maintaining the remaining energy more evenly, or eliminating multihop transmission. Therefore, the proposed scheme increases the network lifetime. We theoretically analyze the energy consumption in our scheme and propose three heuristical mobility strategies. We further study the collaboration among CHs in order to maintain their connectivity to the BS to ensure the delay requirement for real‐time applications. Simulation shows that network lifetime is increased by upto 75% over existing approach by making CHs always move toward a stable equilibrium point. Our connectivity algorithm provides a best case improvement of 40% in transmission delays over existing schemes. Copyright © 2009 John Wiley & Sons, Ltd.     

Maximum lifetime routing in wireless sensor networks

A routing problem in static wireless ad hoc networks is considered as it arises in a rapidly deployed, sensor based, monitoring system known as the wireless sensor network. Information obtained by the monitoring nodes needs to be routed to a set of designated gateway nodes. In these networks, every node is capable of sensing, data processing, and communication, and operates on its limited amount of battery energy consumed mostly in transmission and reception at its radio transceiver. If we assume that the transmitter power level can be adjusted to use the minimum energy required to reach the intended next hop receiver then the energy consumption rate per unit information transmission depends on the choice of the next hop node, i.e., the routing decision. We formulate the routing problem as a linear programming problem, where the objective is to maximize the network lifetime, which is equivalent to the time until the network partition due to battery outage. Two different models are considered for the information-generation processes. One assumes constant rates and the other assumes an arbitrary process. A shortest cost path routing algorithm is proposed which uses link costs that reflect both the communication energy consumption rates and the residual energy levels at the two end nodes. The algorithm is amenable to distributed implementation. Simulation results with both information-generation process models show that the proposed algorithm can achieve network lifetime that is very close to the optimal network lifetime obtained by solving the linear programming problem.     

Analyzing lifetime of energy harvesting underwater wireless sensor nodes

Underwater Wireless Sensor Networks (UWSNs) are utilized to monitor underwater environments that pose many challenges to researchers. One of the key complications of UWSNs is the difficulty of changing node batteries after their energy is depleted. This study aims to diminish the issues related to battery replacement by improving node lifetime. For this goal, three energy harvesting devices (turbine harvester, piezoelectric harvester, and hydrophone harvester) are analyzed to quantitate their impacts on node lifetime. In addition, two different power management schemes (schedule‐driven and event‐driven power management schemes) are combined with energy harvesters for further lifetime improvement. Performance evaluations via simulations show that energy harvesting methods joined by power management schemes can improve node lifetime substantially when actual conditions of Istanbul Bosporus Strait are considered. In this respect, turbine harvester makes the biggest impact and provides lifetime beyond 2000 days for most cases, while piezoelectric harvester can perform the same only for low duty cycle or event arrival values at short transmission ranges.     

无线传感器网络节点的自身定位

无线传感器网络的自身节点的定位对网络来说是非常重要的，传感器节点是随机分布在网络中的，这关系到网络最终的定位精度；节点自身定位的方法从节点的个数主要有单点定位和两个节点的定位，这里提出另一种定位方法，运用三个节点实现传感器网络的节点定位。     

无线传感器网络多汇聚节点分簇算法

为解决大规模无线传感器网络的节点通信效率问题,提出无线传感器网络的一种多汇聚节点分簇算法,针对拥有多个汇聚节点的监控区域,对网络进行层次化管理。算法通过对多种参数的综合考虑后产生簇头,并将传感器节点分配到相应的簇,由此可以有效降低节点的非均匀能耗,减少因能耗较大节点的能量过度衰竭而造成网络可用率下降。仿真结果显示,该算法可以延缓首个死亡节点的发生时间,并能有效延长无线传感器网络的整体可用率。     

Maximizing lifetime of large-scale wireless sensor networks using multi-objective whale optimization algorithm

Telecommunication Systems - The sink nodes in large-scale wireless sensor networks (LSWSNs) are responsible for receiving and processing the collected data from sensor nodes. Identifying the...     

Distributed trajectory design for data gathering using mobile sink in wireless sensor networks

Several studies have demonstrated the benefits of using a mobile sink (MS) to reduce energy consumption resulting from multi-hop data collection using a static sink in wireless sensor networks (WSNs). However, using MS may increase data delivery latency as it needs to visit each sensor node in the network to collect data. This is a critical issue in delay-sensitive applications where all sensed data must be gathered within a given time constraint. In this paper, we propose a distributed data gathering protocol utilizing MS for WSNs. The proposed protocol designs a trajectory for the MS, which minimizes energy consumption and delay. Our protocol operates in four main phases: data sensing, rendezvous point (RP) selection, trajectory design, and data gathering. In data sensing, a number of deployed sensor nodes keep sensing the target field for a specific period of time to capture events. Then, using a cluster-based RP selection algorithm, some sensor nodes are selected to become RPs based on local information. The selected RPs are then used to determine a trajectory for the MS. To do so, we propose three trajectory design algorithms that support different types of applications, namely reduced energy path (REP), reduced delay path (RDP), and delay bound path (DBP). The MS moves through the constructed path to accomplish its data gathering according to an effective scheduling technique that is introduced in this work. We validate the proposed protocol via extensive simulations over several metrics such as energy, delay, and time complexity.     

Distributed lifetime optimization in wireless sensor networks using alternating direction method of multipliers

Due to the limited energy of sensor nodes in wireless sensor networks, extending the network lifetime is a major challenge that can be formulated as an optimization problem. In this paper, we propose a distributed iterative algorithm based on alternating direction method of multipliers with the aim of maximizing sensor network lifetime. The features of this algorithm are the use of local information, low overhead of message passing, low computational complexity, fast convergence, and, consequently, reduced energy consumption. In this study, we present the convergence results and the number of iterations required to achieve the stopping criterion. Furthermore, the impact of problem size (number of sensor nodes) on the solution and constraints violation is studied, and, finally, the proposed algorithm is compared with one of the well‐known subgradient‐based algorithms.     

Data aggregated maximum lifetime routing for wireless sensor networks

In this paper, we present a data aggregated maximum lifetime routing scheme for wireless sensor networks. We address the problem of jointly optimizing data aggregation and routing so that the network lifetime can be maximized. A recursive smoothing method is adopted to overcome the non-differentiability of the objective function. We derive the necessary and sufficient conditions for achieving the optimality of the optimization problem and design a distributed gradient algorithm accordingly. Extensive simulations are carried out to show that the proposed algorithm can significantly reduce the data traffic and improve the network lifetime. The convergence property of the algorithm is studied under various network configurations.     

Network lifetime maximization for time‐sensitive data gathering in wireless sensor networks with a mobile sink

With the advances of more and more mobile sink deployments (e.g., robots and unmanned aerial vehicles), mobile sinks have been demonstrated to play an important role in the prolongation of network lifetime. In this paper, we consider the network lifetime maximization problem for time‐sensitive data gathering, which requires sensing data to be sent to the sink as soon as possible, subject to several constraints on the mobile sink. Because the mobile sink is powered by petrol or electricity, its maximum travel distance per tour is bounded. The mobile sink's maximum moving distance from its current location to the next must also be bounded to minimize data loss. As building a new routing tree rooted at each new location will incur an overhead on energy consumption, the mobile sink must sojourn at each chosen location at least for a certain amount of time. The problem, thus, is to find an optimal sojourn tour for the mobile sink such that the network lifetime is maximized, which is subject to a set of constraints on the mobile sink: its maximum travel distance, the maximum distance of each movement, and the minimum sojourn time at each sojourn location. In this paper, we first formulate this novel multiple‐constrained optimization problem as the distance‐constrained mobile sink problem for time‐sensitive data gathering. We then devise a novel heuristic for it. We finally conduct extensive experiments by simulation to evaluate the performance of the proposed algorithm. The experimental results demonstrate that the performance of the proposed algorithm is very promising, and the solution obtained is fractional of the optimal one. Copyright © 2011 John Wiley & Sons, Ltd.     

Band-based geocasting for mobile sink groups in wireless sensor networks

This paper studies on delivery-guaranteed and effective data dissemination for mobile sink groups in wireless sensor networks. A mobile sink group denotes a set of tightly coupled mobile sinks for team collaborations such as a team of firefighters and a group of solders. The mobile sinks have a group movement feature. They thus randomly move in personal spaces as well as collectively move together as a single entity. To support such group mobility, previous studies provide circle-based protocols determining successive circular areas of a group continuously moving, and then propagate data in the areas by flooding. However, since a group is still moving during decision of each circle, they may cause asynchrony between circles and actual group positions. Eventually, it could harm reachability and energy-efficiency. We therefore propose a novel data dissemination protocol using motion properties of a mobile sink group: slowly varying and streamlike movement. By the slowly varying constraint, the protocol predictively and effectively delivers data to a group through a band of sensor nodes located in front of the streamlike trajectory of the group.     

Determining sink location through Zeroing-In attackers in wireless sensor networks

The viability and success of wireless sensor networks critically hinge on the ability of a small number of sinks to glean sensor data throughout the networks. Thus, the locations of sinks are critically important. In this paper, we examine the sink location privacy problem from both the attack and defense perspectives. First, we examine resource-constrained adversaries who can only eavesdrop the network at their vicinities. To determine the sink location, they can launch a Zeroing-In attack by leveraging the fact that several network metrics are 2-dimensional functions in the plane of the network, and their values minimize at the sink. Thus, determining the sink location is equivalent to finding the minima of those functions. We demonstrate that by obtaining the hop counts or the arrival time of a broadcast packet at a few spots in the network, the adversaries are able to determine the sink location with the accuracy of one radio range, which is sufficient to disable the sink by launching jamming attacks, for example. To cope with the Zeroing-In attacks, we present a directed-walk-based routing scheme and show that the defense strategy is effective in deceiving adversaries at little energy costs.     

EMS: Efficient mobile sink scheduling in wireless sensor networks

Sink scheduling, in the form of scheduling multiple sinks among the available sink sites to relieve the level of traffic burden, is shown to be a promising scheme in wireless sensor networks (WSNs). However, the problem of maximizing the network lifetime via sink scheduling remains quite a challenge since routing issues are tightly coupled. Previous approaches on this topic either suffer from poor performance due to a lack of joint considerations, or are based on relaxed constraints. Therefore, in this paper, we aim to fill in the research blanks. First, we develop a novel notation Placement Pattern (PP) to bound time-varying routes with the placement of sinks. This bounding technique transforms the problem from time domain into pattern domain, and thus, significantly decreases the problem complexity. Then, we formulate this optimization in a pattern-based way and create an efficient Column Generation (CG) based approach to solve it. Simulations not only demonstrate the efficiency of the proposed algorithm but also substantiate the importance of sink mobility for energy-constrained WSNs.