Extending the Lifetime of Wireless Sensor Networks Through Adaptive Sleep

In recent years, the use of wireless sensor networks for industrial applications has rapidly increased. However, energy consumption still remains one of the main limitations of this technology. As communication typically accounts for the major power consumption, the activity of the transceiver should be minimized, in order to prolong the network lifetime. To this end, this paper proposes an Adaptive Staggered sLEEp Protocol (ASLEEP) for efficient power management in wireless sensor networks targeted to periodic data acquisition. This protocol dynamically adjusts the sleep schedules of nodes to match the network demands, even in time-varying operating conditions. In addition, it does not require any a priori knowledge of the network topology or traffic pattern. ASLEEP has been extensively studied with simulation. The results obtained show that, under stationary conditions, the protocol effectively reduces the energy consumption of sensor nodes (by dynamically adjusting their duty-cycle to current needs) thus increasing significantly the network lifetime. With respect to similar nonadaptive solutions, it also reduces the average message latency and may increase the delivery ratio. Under time-varying conditions, the protocol is able to adapt the duty-cycle of single nodes to the new operating conditions, while keeping a consistent sleep schedule among sensor nodes. The results presented here are also confirmed by an experimental evaluation in a real testbed.      

基于网格的移动无线传感网生存时间优化算法

为克服陆地静态无线传感网和水下无线传感网因节点能耗分布不均衡而出现的能量空穴问题,和具有单一移动Sink节点的无线传感网数据收集时延过长问题,该文提出基于网格的移动无线传感网生存时间优化算法(Grid-based Lifetime Optimization Algorithm,GLOA)。GLOA算法考虑多个Sink节点的移动,将监测区域分成多个大小相同的网格。根据网格潜能值确定Sink节点移动的锚点,将锚点分配给不同的Sink节点,建立路径选择优化模型并获得Sink节点的最短移动路径,采用移动收集方法或静态收集方法循环收集数据。仿真结果表明:与Ratio_w或TPGF算法相比,GLOA算法能延长网络生存时间,降低和均衡节点能耗。与LOA_SMSN算法相比,GLOA算法能降低数据收集时延。在一定的条件下,比Ratio_w,TPGF和LOA_SMSN算法更优。     

A Survey on Extending the Lifetime for Wireless Sensor Networks in Real-Time Applications

International Journal of Wireless Information Networks - Wireless Sensor Network (WSN) has achieved a great contribution in establishing the recent technological revolution. One of the most...     

无线传感器网络生命周期最大化研究

无线传感器网络中节点很容易因能量的缺失、环境的影响、遭受意外破坏等原因而停止工作,影响整个网络的生命周期,因此网络生命周期最大化成为传感器网络设计的关键.从节点和网络两个方面阐述了延长网络生命周期的一些策略.     

On Prolonging the Lifetime for Wireless Video Sensor Networks

This paper investigates strategies for prolonging the system lifetime for wireless video sensor networks, by adopting a mobile sink and solar-powered video sensors. Issues of tracking moving objects in wireless video sensor networks are studied, and the effectiveness of adopting a mobile sink is evaluated. This paper applies a power-rate-distortion analysis framework, which provides a theoretical fundamental to quantify various properties of wireless video sensor networks. The performance of wireless video sensor networks is evaluated with a mobile sink versus a static sink, under different cluster sizes and number of sensors. Comparisons of network lifetime, tracking error, video distortion, are also covered in this paper. In addition, this paper also evaluates the performance of solar-powered video sensors under an unequal layered clustering topology.     

Maximum Lifetime Target Coverage in Wireless Sensor Networks

Wireless Personal Communications - The challenge in the deployment of wireless sensor networks is to ensure the coverage of targets with high energy efficiency, particularly when coverage and...     

无线传感器网络优化生存时间的动态路由算法

 节能和延长网络生存时间是无线传感器网络研究领域的热点问题.该文综合考虑网络中节点的剩余能量和节点间传输数据的能耗,基于最短路径树算法,通过构造两种不同的权值函数,提出了"比例权值路由算法"(Ratio-W)与"和权值路由算法"(Sum-W).仿真分析表明,所提出的算法可以延长网络生存时间,并使能耗经济有效,比一些已有知名算法更优.     

Maximizing Lifetime for Data Aggregation in Wireless Sensor Networks

This paper studies energy efficient routing for data aggregation in wireless sensor networks. Our goal is to maximize the lifetime of the network, given the energy constraint on each sensor node. Using linear programming (LP) formulation, we model this problem as a multicommodity flow problem, where a commodity represents the data generated from a sensor node and delivered to a base station. A fast approximate algorithm is presented, which is able to compute (1−ε)-approximation to the optimal lifetime for any ε > 0. Then along this baseline, we further study several advanced topics. First, we design an algorithm, which utilizes the unique characteristic of data aggregation, and is proved to reduce the running time of the fastest existing algorithm by a factor of K, K being the number of commodities. Second, we extend our algorithm to accommodate the same problem in the setting of multiple base stations, and study its impact on network lifetime improvement. All algorithms are evaluated through both solid theoretical analysis and extensive simulation results. Yuan Xue received her B.S. in Computer Science from Harbin Institute of Technology, China in 1994 and her M.S. and Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 2002, and 2005. Currently she is an assistant professor at the Department of Electrical Engineering and Computer Science of Vanderbilt University. Her research interests include wireless and sensor networks, mobile systems, and network security. Yi Cui received his B.S. and M.S. degrees in 1997 and 1999, from Department of Computer Science, Tsinghua University, China, and his Ph.D. degree in 2005 from the Department of Computer Science, University of Illinois at Urbana-Champaign. Since then, he has been with the Department of Electrical Engineering and Computer Science at Vanderbilt University, where he is currently an assistant professor. His research interests include overlay network, peer-to-peer system, multimedia system, and wireless sensor network. Klara Nahrstedt (M ' 94) received her A.B., M.Sc degrees in mathematics from the Humboldt University, Berlin, Germany, and Ph.D in computer science from the University of Pennsylvania. She is an associate professor at the University of Illinois at Urbana-Champaign, Computer Science Department where she does research on Quality of Service(QoS)-aware systems with emphasis on end-to-end resource management, routing and middleware issues for distributed multimedia systems. She is the coauthor of the widely used multimedia book ‘Multimedia:Computing, Communications and Applications’ published by Prentice Hall, and the recipient of the Early NSF Career Award, the Junior Xerox Award and the IEEE Communication Society Leonard Abraham Award for Research Achievements, and the Ralph and Catherine Fisher Professorship Chair. Since June 2001 she serves as the editor-in-chief of the ACM/Springer Multimedia System Journal. An erratum to this article is available at .     

On Node Lifetime Problem for Energy-Constrained Wireless Sensor Networks

A fundamental problem in wireless sensor networks is to maximize network lifetime under given energy constraints. In this paper, we study the network lifetime problem by considering not only maximizing the time until the first node fails, but also maximizing the lifetimes for all the nodes in the network, which we define as the Lexicographic Max-Min (LMM) node lifetime problem. The main contributions of this paper are two-fold. First, we develop a polynomial-time algorithm to derive the LMM-optimal node lifetime vector, which effectively circumvents the computational complexity problem associated with an existing state-of-the-art approach, which is exponential. The main ideas in our approach include: (1) a link-based problem formulation, which significantly reduces the problem size in comparison with a flow-based formulation, and (2) an intelligent exploitation of parametric analysis technique, which in most cases determines the minimum set of nodes that use up their energy at each stage using very simple computations. Second, we present a simple (also polynomial-time) algorithm to calculate the flow routing schedule such that the LMM-optimal node lifetime vector can be achieved. Our results in this paper advance the state-of-the-art algorithmic design for network-wide node lifetime problem and facilitate future studies of the network lifetime problem in energy-constrained wireless sensor networks. Y. Thomas Hou obtained his B.E. degree from the City College of New York in 1991, the M.S. degree from Columbia University in 1993, and the Ph.D. degree from Polytechnic University, Brooklyn, New York, in 1998, all in Electrical Engineering. From 1997 to 2002, Dr. Hou was a research scientist and project leader at Fujitsu Laboratories of America, IP Networking Research Department, Sunnyvale, California(Silicon Valley). Since Fall 2002, he has been an Assistant Professor at Virginia Tech, the Bradley Department of Electrical and Computer Engineering, Blacksburg, Virginia. Dr. Hou's research interests are in the algorithmic design and optimization for network systems. His current research focuses on wireless sensor networks and multimedia over wireless ad hoc networks. In recent years, he has worked on scalable architectures, protocols, and implementations for differentiated services Internet; service overlay networking; multimedia streaming over the Internet; and network bandwidth allocation policies and distributed flow control algorithms. He has published extensively in the above areas and is a co-recipient of the 2002 IEEE International Conference on Network Protocols (ICNP) Best Paper Award and the 2001 IEEE Transactions on Circuits and Systems for Video Technology (CSVT) Best Paper Award. He is a member of ACM and a senior member of IEEE. Yi Shi received his B.S. degree from University of Science and Technology of China, Hefei, China, in 1998, a M.S. degree from Institute of Software, Chinese Academy of Science, Beijing, China, in 2001, and a second M.S. degree from Virginia Tech, Blacksburg, VA, in 2003, all in computer science. He is currently working toward his Ph.D. degree in electrical and computer engineering at Virginia Tech. While in undergraduate, he was a recipient of Meritorious Award in International Mathematical Contest in Modeling and 1997 and 1998, respectively. Yi's current research focuses on algorithms and optimization for wireless sensor networks and wireless ad hoc networks. His work has appeared in highly selective international conferences (e.g., ACM MobiCom and MobiHoc). Hanif D. Sherali is the W. Thomas Rice Endowed Chaired Professor of Engineering in the Industrial and Systems Engineering Department at Virginia Polytechnic Institute and State University. His area of research interest is in discrete and continuous optimization, with applications to location, transportation, and engineering design problems. He has published about 200 papers in Operations Research journals, has co-authored four books in this area, and serves on the editorial board of eight journals. He is a member of the National Academy of Engineering.     

Network Lifetime Enhancement of Wireless Sensor Networks Using EFRP Protocol

This paper presents a novel transceiver architecture for in-band full duplex radio. A transceiver for full duplex radio requires a self-interference (SI) canceler to remove the SI occurring from the transmitter to the receiver, and a full duplex transceiver generally has two SI cancelers: one at the analog RF stage and the other at the baseband stage. The output from the SI canceler at the RF stage includes much residual SI, and it decreases the number of bits allocated to the analog baseband signal at the analog-to-digital converter. A 1-tap analog baseband SI canceler that uses a replica signal including only the direct path component of the residual SI has been presented for preventing degradation. However, the architecture cannot remove the SI well due to the high Ricial K-factor. To address the problem, the presented architecture has an SI canceler at the analog baseband stage, and this canceler employs a replica signal that is output from a digital-to-analog converter. Because the replica signal is generated in the digital domain, the architecture can generate a multipath replica signal, and improved performance can be expected. Numerical and theoretical analyses are shown to validate the effectiveness of the presented architecture.

     

一种移动多Sink无线传感器网络监测系统

军事防御、灾害监测与救援等危险/恶劣环境监测是无线传感器网络的典型应用。在此面向危险/恶劣环境监测需求,设计并构建移动多Sink无线传感器网络监测系统,实现环境信息感知、便携式移动指挥、事件定位、移动用户生理监护、多模态（语音、图像、文字等）交互等功能。实验测试结果表明,当网络中存在2个移动Sink节点时,网络平均延时小于100 ms,网络丢包率小于6%,可满足网络实时性要求不高的应用。     

移动无线传感网的生存时间优化算法研究

当sink节点位置固定不变时,分布在sink 节点周围的传感节点很容易成为枢纽节点,因转发较多的数据而过早失效。为解决上述问题,提出移动无线传感网的生存时间优化算法（LOAMWSN）。LOAMWSN算法考虑sink节点的移动,采用减聚类算法确定sink节点移动的锚点,采用最近邻插值法寻找能遍历所有锚点的最短路径近似解,采用分布式非同步Bellman-Ford算法构建sink节点k跳通信范围内的最短路径树。最终,传感节点沿着最短路径树将数据发送给sink节点。仿真结果表明：在节点均匀分布和非均匀分布的无线传感网中,LOAMWSN算法都可以延长网络生存时间、平衡节点能耗,将平均节点能耗保持在较低水平。在一定的条件下,比Ratio_w、TPGF算法更优。     

移动无线传感器网络节点的定位

文中在MCB（Monte—Carlo Localization Boxed）定位算法的基础上提出了一种新的移动无线传感器网络（Mobile Wireless Sensor Networks）节点的定位算法——权重MCB算法。MCB算法在定位过程中,在采样和滤波阶段用到了一阶锚节点和二阶锚节点的位置信息,而没有应用到邻居节点的位置信息。权重MCB在定位过程中不仅用到了一阶锚节点和二阶锚节点的位置信息,还应用到了一阶邻居节点的采样集合里的采样点（即一阶邻居节点的估计位置）,从而改进了定位精度。对比MCB算法,权重MCB算法对定位精度的改进为13％～18％。     

Timing-Based Mobile Sensor Localization in Wireless Sensor and Actor Networks

In this paper, localization problem in wireless sensor and actor networks (WSAN) is addressed. In WSAN, the performance of event detection and tracking highly depends on the exact location information of the events that must be reported along with the event features. Having precise location information of the sensor nodes, actors are able to execute actions more effectively in the region of detected events. In this context, the accurate localization of sensor nodes is essential with respect to the actors. Particularly, the problem becomes much more complicated when the sensor nodes as well as the anchor nodes (actors) are mobile. In order to localize the mobile sensor nodes relative to the actors, a novel Timing-based Mobile Sensor Localization (TMSL) algorithm is introduced. In TMSL, sensor nodes determine their distance from actors by using propagation time and speed of RF signal. In order to determine distance from the actors, actors actively broadcast reference beacons in a pattern of intervals adaptively defined according to the mobility of sensor nodes and the required level of localization accuracy. These reference beacons carry the interval numbers in which they were transmitted. The interval numbers are then used by the sensor nodes to calculate the start time of the beacons locally which is then used to determine the propagation time. TMSL does neither require nor assume any time synchronization among the sensor nodes or with the actors. Performance evaluations clearly show that TMSL is adaptive to velocity of mobile sensor and actor nodes and can be configured according to the required localization accuracy in order to avoid overhead raised due to high velocity.     

Cross-Layer Design for Lifetime Maximization in Interference-Limited Wireless Sensor Networks

We consider the joint optimal design of the physical, medium access control (MAC), and routing layers to maximize the lifetime of energy-constrained wireless sensor networks. The problem of computing lifetime-optimal routing flow, link schedule, and link transmission powers for all active time slots is formulated as a non-linear optimization problem. We first restrict the link schedules to the class of interference-free time division multiple access (TDMA) schedules. In this special case, we formulate the optimization problem as a mixed integerconvex program, which can be solved using standard techniques. Moreover, when the slots lengths are variable, the optimization problem is convex and can be solved efficiently and exactly using interior point methods. For general non-orthogonal link schedules, we propose an iterative algorithm that alternates between adaptive link scheduling and computation of optimal link rates and transmission powers for a fixed link schedule. The performance of this algorithm is compared to other design approaches for several network topologies. The results illustrate the advantages of load balancing, multihop routing, frequency reuse, and interference mitigation in increasing the lifetime of energy-constrained networks. We also briefly discuss computational approaches to extend this algorithm to large networks     

移动无线传感器网络中节点自定位算法研究

移动无线传感器网络(MWSN)是一种全新的信息获取和处理技术,可以在广泛的应用领域内实现复杂的大规模监测和追踪任务,而移动节点的位置信息则是其应用的基础。针对这一特征,文章深入探讨了移动节点自定位算法的研究现状,介绍了移动无线传感器网络节点定位的基本方法,讨论了定位算法的性能评价指标,并对各种算法性能进行了比较,最后指出了算法存在的问题和解决办法。文章认为三维全节点移动的定位算法将成为以后的研究趋势。     

Network Lifetime Maximization for Estimation in Multihop Wireless Sensor Networks

We consider the distributed estimation by a network consisting of a fusion center and a set of sensor nodes, where the goal is to maximize the network lifetime, defined as the estimation task cycles accomplished before the network becomes nonfunctional. In energy-limited wireless sensor networks, both local quantization and multihop transmission are essential to save transmission energy and thus prolong the network lifetime. The network lifetime optimization problem includes three components: i) optimizing source coding at each sensor node, ii) optimizing source throughput of each sensor node, and iii) optimizing multihop routing path. Fortunately, source coding optimization can be decoupled from source throughput and multihop routing path optimization, and is solved by introducing a concept of equivalent 1-bit MSE function. Based on the optimal source coding, the source throughput and multihop routing path optimization is formulated as a linear programming (LP) problem, which suggests a new notion of character-based routing. The proposed algorithm is optimal and the simulation results show that a significant gain is achieved by the proposed algorithm compared with heuristic methods.     

Lifetime Increase for Wireless Sensor Networks Using Cellular Learning Automata

Wireless Personal Communications - With the advent of automation, more and more information is being generated. Thereby, increasingly sensors are being used, featuring increasingly dense networks....     

Lifetime Maximization for Connected Target Coverage in Wireless Sensor Networks

In this paper, we consider the connected target coverage (CTC) problem with the objective of maximizing the network lifetime by scheduling sensors into multiple sets, each of which can maintain both target coverage and connectivity among all the active sensors and the sink. We model the CTC problem as a maximum cover tree (MCT) problem and prove that the MCT problem is NP-Complete. We determine an upper bound on the network lifetime for the MCT problem and then develop a $(1+w)H(mathhat{M})$ approximation algorithm to solve it, where $w$ is an arbitrarily small number, $H(mathhat{M})=sum_{1leq ileqmathhat{M}}(1/i)$ and $mathhat{M}$ is the maximum number of targets in the sensing area of any sensor. As the protocol cost of the approximation algorithm may be high in practice, we develop a faster heuristic algorithm based on the approximation algorithm called Communication Weighted Greedy Cover (CWGC) algorithm and present a distributed implementation of the heuristic algorithm. We study the performance of the approximation algorithm and CWGC algorithm by comparing them with the lifetime upper bound and other basic algorithms that consider the coverage and connectivity problems independently. Simulation results show that the approximation algorithm and CWGC algorithm perform much better than others in terms of the network lifetime and the performance improvement can be up to 45% than the best-known basic algorithm. The lifetime obtained by our algorithms is close to the upper bound. Compared with the approximation algorithm, the CWGC algorithm can achieve a similar performance in terms of the network lifetime with a lower protocol cost.      

Rate Allocation and Network Lifetime Problems for Wireless Sensor Networks

An important performance consideration for wireless sensor networks is the amount of information collected by all the nodes in the network over the course of network lifetime. Since the objective of maximizing the sum of rates of all the nodes in the network can lead to a severe bias in rate allocation among the nodes, we advocate the use of lexicographical max-min (LMM) rate allocation. To calculate the LMM rate allocation vector, we develop a polynomial-time algorithm by exploiting the parametric analysis (PA) technique from linear program (LP), which we call serial LP with parametric analysis (SLP-PA). We show that the SLP-PA can be also employed to address the LMM node lifetime problem much more efficiently than a state-of-the-art algorithm proposed in the literature. More important, we show that there exists an elegant duality relationship between the LMM rate allocation problem and the LMM node lifetime problem. Therefore, it is sufficient to solve only one of the two problems. Important insights can be obtained by inferring duality results for the other problem.