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1.
In an energy‐constrained wireless sensor networks (WSNs), clustering is found to be an effective strategy to minimize the energy depletion of sensor nodes. In clustered WSNs, network is partitioned into set of clusters, each having a coordinator called cluster head (CH), which collects data from its cluster members and forwards it to the base station (BS) via other CHs. Clustered WSNs often suffer from the hot spot problem where CHs closer to the BS die much early because of high energy consumption contributed by the data forwarding load. Such death of nodes results coverage holes in the network very early. In most applications of WSNs, coverage preservation of the target area is a primary measure of quality of service. Considering the energy limitation of sensors, most of the clustering algorithms designed for WSNs focus on energy efficiency while ignoring the coverage requirement. In this paper, we propose a distributed clustering algorithm that uses fuzzy logic to establish a trade‐off between the energy efficiency and coverage requirement. This algorithm considers both energy and coverage parameters during cluster formation to maximize the coverage preservation of target area. Further, to deal with hot spot problem, it forms unequal sized clusters such that more CHs are available closer to BS to share the high data forwarding load. The performance of the proposed clustering algorithm is compared with some of the well‐known existing algorithms under different network scenarios. The simulation results validate the superiority of our algorithm in network lifetime, coverage preservation, and energy efficiency. 相似文献
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LI LI DONG Shu-song WEN Xiang-mingInstitute of Continuing Education School Beijing University of Posts Telecommunications Beijing China 《中国邮电高校学报(英文版)》2006,13(3):71-75
~~An energy efficient clustering routing algorithm for wireless sensor networks1. Mainwaring A, Polastre J, Szewczyk R, et al. Wireless sensor networks for habitat monitoring. Proceedings of the ACM International Workshop on Wireless Sensor Networks and A… 相似文献
3.
Clustering provides an effective way to prolong the lifetime of wireless sensor networks.One of the major issues of a clustering protocol is selecting an optimal group of sensor nodes as the cluster heads to divide the network.Another is the mode of inter-cluster communication.In this paper,an energy-balanced unequal clustering(EBUC)protocol is proposed and evaluated.By using the particle swarm optimization(PSO)algorithm,EBUC partitions all nodes into clusters of unequal size,in which the clusters closer to the base station have smaller size.The cluster heads of these clusters can preserve some more energy for the inter-cluster relay traffic and the 'hot-spots' problem can be avoided.For inter-cluster communication,EBUC adopts an energy-aware multihop routing to reduce the energy consumption of the cluster heads.Simulation results demonstrate that the protocol can efficiently decrease the dead speed of the nodes and prolong the network lifetime. 相似文献
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Underwater wireless sensor network (UWSN) is a network made up of underwater sensor nodes, anchor nodes, surface sink nodes or surface stations, and the offshore sink node. Energy consumption, limited bandwidth, propagation delay, high bit error rate, stability, scalability, and network lifetime are the key challenges related to underwater wireless sensor networks. Clustering is used to mitigate these issues. In this work, fuzzy-based unequal clustering protocol (FBUCP) is proposed that does cluster head selection using fuzzy logic as it can deal with the uncertainties of the harsh atmosphere in the water. Cluster heads are selected using linguistic input variables like distance to the surface sink node, residual energy, and node density and linguistic output variables like cluster head advertisement radius and rank of underwater sensor nodes. Unequal clustering is used to have an unequal size of the cluster which deals with the problem of excess energy usage of the underwater sensor nodes near the surface sink node, called the hot spot problem. Data gathered by the cluster heads are transmitted to the surface sink node using neighboring cluster heads in the direction of the surface sink node. Dijkstra's shortest path algorithm is used for multi-hop and inter-cluster routing. The FBUCP is compared with the LEACH-UWSN, CDBR, and FBCA protocols for underwater wireless sensor networks. A comparative analysis shows that in first node dies, the FBUCP is up to 80% better, has 64.86% more network lifetime, has 91% more number of packets transmitted to the surface sink node, and is up to 58.81% more energy efficient than LEACH-UWSN, CDBR, and FBCA. 相似文献
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Clustering provides an effective method 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 spot problem in multihop 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 heavier relay traffic and tend to die much faster,
leaving areas of the network uncovered and causing network partitions. To mitigate the hot spot problem, we propose an Unequal
Cluster-based Routing (UCR) protocol. It groups the nodes into clusters of unequal sizes. Cluster heads closer to the base
station have smaller cluster sizes than those farther from the base station, thus they can preserve some energy for the inter-cluster
data forwarding. A greedy geographic and energy-aware routing protocol is designed for the inter-cluster communication, which
considers the tradeoff between the energy cost of relay paths and the residual energy of relay nodes. Simulation results show
that UCR mitigates the hot spot problem and achieves an obvious improvement on the network lifetime.
Guihai Chen obtained his B.S. degree from Nanjing University, M. Engineering from Southeast University, and PhD from University of Hong
Kong. He visited Kyushu Institute of Technology, Japan in 1998 as a research fellow, and University of Queensland, Australia
in 2000 as a visiting professor. During September 2001 to August 2003, he was a visiting professor at Wayne State University.
He is now a full professor and deputy chair of Department of Computer Science, Nanjing University. Prof. Chen has published
more than 100 papers in peer-reviewed journals and refereed conference proceedings in the areas of wireless sensor networks,
high-performance computer architecture, peer-to-peer computing and performance evaluation. He has also served on technical
program committees of numerous international conferences. He is a member of the IEEE Computer Society.
Chengfa Li was born 1981 and obtained his Bachelor’s Degree in mathematics in 2003 and his Masters Degree in computer science in 2006,
both from Nanjing University, China. He is now a system programmer at Lucent Technologies Nanjing Telecommunication Corporation.
His research interests include wireless ad hoc and sensor networks.
Mao Ye was born in 1981 and obtained his Bachelor’s Degree in computer science from Nanjing University, China, in 2004. He served
as a research assistant At City University of Hong Kong from September 2005 to August 2006. He is now a PhD candidate with
research interests in wireless networks, mobile computing, and distributed systems.
Jie Wu is a professor in the Department of Computer Science and Engineering at Florida Atlantic University. He has published more
than 300 papers in various journal and conference proceedings. His research interests are in the areas of mobile computing,
routing protocols, fault-tolerant computing, and interconnection networks. Dr. Wu serves as an associate editor for the IEEE
Transactions on Parallel and Distributed Systems and several other international journals. He served as an IEEE Computer Society
Distinguished Visitor and is currently the chair of the IEEE Technical Committee on Distributed Processing (TCDP). He is a
member of the ACM, a senior member of the IEEE, and a member of the IEEE Computer Society. 相似文献
6.
Minimising energy consumption has always been an issue of crucial importance in sensor networks. Most of the energy is consumed in data transmission from sensor nodes to the base station due to the long distance of nodes from the base station. In the recent past, a number of researchers have proposed that clustering is an efficient way of reducing the energy consumption during data transmission and enhancing the lifetime of wireless sensor networks. Many algorithms have been already proposed for cluster head selection. In this work, we analyse and compare the lifetime of the network with three different fuzzy-based approaches of cluster head selection. The three strong parameters which play an important role in lifetime enhancement – energy, centrality and node density – are considered for cluster head selection in our proposed fuzzy approaches. In the first approach, energy and centrality are considered simultaneously in a fuzzy system to select the cluster heads. In the second approach, energy and node density have been taken in a fuzzy system to select the cluster heads. In the third approach, node density and centrality are considered simultaneously by a fuzzy system to select the cluster heads. Simulation results of these fuzzy logic-based approaches show that all the three approaches are superior to the Low-Energy Adaptive Clustering Hierarchy (LEACH). Simulation results also show that the energy-centrality-based fuzzy clustering scheme gives best performance among all the three fuzzy-based algorithms and it enhances the lifetime of wireless sensor networks by a significant amount. 相似文献
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FUCA: Fuzzy‐based unequal clustering algorithm to prolong the lifetime of wireless sensor networks 下载免费PDF全文
Wireless sensor network comprises billions of nodes that work collaboratively, gather data, and transmit to the sink. “Energy hole” or “hotspot” problem is a phenomenon in which nodes near to the sink die prematurely, which causes the network partition. This is because of the imbalance of the consumption of energy by the nodes in wireless sensor networks. This decreases the network's lifetime. Unequal clustering is a technique to cope up with this issue. In this paper, an algorithm, “fuzzy‐based unequal clustering algorithm,” is proposed to prolong the lifetime of the network. This protocol forms unequal clusters. This is to balance the energy consumption. Cluster head selection is done through fuzzy logic approach. Input variables are the distance to base station, residual energy, and density. Competition radius and rank are the two output fuzzy variables. Mamdani method is employed for fuzzy inference. The protocol is compared with well‐known algorithms, like low‐energy adaptive clustering hierarchy, energy‐aware unequal clustering fuzzy, multi‐objective fuzzy clustering algorithm, and fuzzy‐based unequal clustering under different network scenarios. In all the scenarios, the proposed protocol performs better. It extends the lifetime of the network as compared with its counterparts. 相似文献
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Michael Chien‐Chun Hung Kate Ching‐Ju Lin Cheng‐Fu Chou Chih‐Cheng Hsu 《Wireless Communications and Mobile Computing》2013,13(8):760-773
The utilization of limited energy in wireless sensor networks (WSNs) is the critical concern, whereas the effectiveness of routing mechanisms substantially influence energy usage. We notice that two common issues in existing specific routing schemes for WSNs are that (i) a path may traverse through a specific set of sensors, draining out their energy quickly and (ii) packet retransmissions over unreliable links may consume energy significantly. In this paper, we develop an energy‐efficient routing scheme (called EFFORT) to maximize the amount of data gathered in WSNs before the end of network lifetime. By exploiting two natural advantages of opportunistic routing, that is, the path diversity and the improvement of transmission reliability, we propose a new metric that enables each sensor to determine a suitable set of forwarders as well as their relay priorities. We then present EFFORT, a routing protocol that utilizes energy efficiently and prolongs network lifetime based on the proposed routing metric. Simulation results show that EFFORT significantly outperforms other routing protocols. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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DUCR: Distributed unequal cluster‐based routing algorithm for heterogeneous wireless sensor networks
Designing energy efficient communication protocols for wireless sensor networks (WSNs) to conserve the sensors' energy is one of the prime concerns. Clustering in WSNs significantly reduces the energy consumption in which the nodes are organized in clusters, each having a cluster head (CH). The CHs collect data from their cluster members and transmit it to the base station via a single or multihop communication. The main issue in such mechanism is how to associate the nodes to CHs and how to route the data of CHs so that the overall load on CHs are balanced. Since the sensor nodes operate autonomously, the methods designed for WSNs should be of distributed nature, i.e., each node should run it using its local information only. Considering these issues, we propose a distributed multiobjective‐based clustering method to assign a sensor node to appropriate CH so that the load is balanced. We also propose an energy‐efficient routing algorithm to balance the relay load among the CHs. In case any CH dies, we propose a recovery strategy for its cluster members. All our proposed methods are completely distributed in nature. Simulation results demonstrate the efficiency of the proposed algorithm in terms of energy consumption and hence prolonging the network lifetime. We compare the performance of the proposed algorithm with some existing algorithms in terms of number of alive nodes, network lifetime, energy efficiency, and energy population. 相似文献
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Abdul Wahid Sungwon Lee Dongkyun Kim 《International Journal of Communication Systems》2014,27(10):2048-2062
Recently, underwater wireless sensor networks (UWSNs) have attracted much research attention to support various applications for pollution monitoring, tsunami warnings, offshore exploration, tactical surveillance, etc. However, because of the peculiar characteristics of UWSNs, designing communication protocols for UWSNs is a challenging task. Particularly, designing a routing protocol is of the most importance for successful data transmissions between sensors and the sink. In this paper, we propose a reliable and energy‐efficient routing protocol, named R‐ERP2R (Reliable Energy‐efficient Routing Protocol based on physical distance and residual energy). The main idea behind R‐ERP2R is to utilize physical distance as a routing metric and to balance energy consumption among sensors. Furthermore, during the selection of forwarding nodes, link quality towards the forwarding nodes is also considered to provide reliability and the residual energy of the forwarding nodes to prolong network lifetime. Using the NS‐2 simulator, R‐ERP2R is compared against a well‐known routing protocol (i.e. depth‐based routing) in terms of network lifetime, energy consumption, end‐to‐end delay and delivery ratio. The simulation results proved that R‐ERP2R performs better in UWSNs.Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
13.
基于认知的无线传感器网络抗干扰路由算法 总被引:2,自引:0,他引:2
针对无线传感器网络受Wi—Fi等异构系统干扰日益严重的问题,在引入基于簇的动态多信道组网策略的基础上,综合考虑频谱受干扰程度、信道切换代价、节点剩余能量等因素,提出了一种认知频谱干扰的能量有效的路由(CSIEE)算法。仿真结果表明,该路由与EEPA,AODV,AODV—EA路由相比,有效地节约了传感器节点能量,延长了网络生命周期。 相似文献
14.
Considering severe resources constraints and security threat hierarchical routing protocol algorithm. The proposed routing of wireless sensor networks (WSN), the article proposed a novel protocol algorithm can adopt suitable routing technology for the nodes according to the distance of nodes to the base station, density of nodes distribution, and residual energy of nodes. Comparing the proposed routing protocol algorithm with simple direction diffusion routing technology, cluster-based routing mechanisms, and simple hierarchical routing protocol algorithm through comprehensive analysis and simulation in terms of the energy usage, packet latency, and security in the presence of node protocol algorithm is more efficient for wireless sensor networks. compromise attacks, the results show that the proposed routing 相似文献
15.
无线传感器网络(WSN)具有的能量有限,其能量利用效率的高低直接影响着网络的生命周期.为了提高无线传感器网络的能量利用效率,提出了一种能量感知非均匀成簇路由优化算法(Energy Awareness Unequal Clustering Routing Optimization Algorithm,EUCR).该算法通过节点在网络中所处的位置确定各节点的邻居节点,并以局部能量选举簇头,各簇头根据其邻居节点构建非均匀分簇网络.同时该算法在路由阶段考虑了簇头的剩余能量和转发代价.仿真结果表明,EUCR算法能有效提高网络的能量利用效率,并延长网络的生命周期. 相似文献
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Chu‐Fu Wang Jen‐Wen Ding Chun‐Chia Lee 《Wireless Communications and Mobile Computing》2010,10(2):171-187
Energy allocation problems and routing problems are both important research issues in the wireless sensor network (WSN) field. The former usually aims at considering how to allocate a certain number of sensor devices in a sensing region to form a WSN so that the objective function value (e.g., the network connectivity or the network lifetime) of the constructed network is optimized. For the message routing problem in WSNs, researchers tend to consider how to find an energy conservable message transmission routing scheme for notifying the supervisor of the WSN when an event occurs. Till now, many solutions have been proposed for the above two categories of optimization problems. However, unifying the above two network optimization problems to maximize the network lifetime, to the best of our knowledge, still lacks related research. This paper considers a joint optimization problem for energy allocation and energy‐aware routing called the joint optimization of energy allocation and routing problem (JOEARP) for a hierarchical cluster‐based WSN. We propose an exact algorithm to provide the optimum solution for the JOEARP. The simulation results show that this solution performed better in prolonging the network lifetime of a WSN in a real situation, compared to other compositions of conventional energy allocation schemes with some known routing algorithms. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
19.
随着网络负载增加,经典的TPGF( Two-Phase geographic Greedy Forwarding)算法难以找到节点分离路径,会导致网络吞吐量、投递率以及端到端时延性能下降。此外,当网络拓扑变动不大时, TPGF中每条路径所包含节点要消耗比其他节点更多的能量,会导致其过快死亡,从而影响网络性能。为此,将联合网络编码技术引入 TPGF,提出一种编码与能量感知的 TPGF 路由算法( NE-TPGF)。该算法综合考虑节点的地理位置、编码机会、剩余能量等因素,同时利用联合网络编码技术进一步扩展编码结构,充分利用网络编码优势来建立相对最优的传输路径。仿真结果表明, NE-TPGF能够增加编码机会,提高网络吞吐量和投递率,降低端到端时延,并且还有利于减少和平衡节点的能量消耗。 相似文献
20.
Fuzzy chessboard clustering and artificial bee colony routing method for energy‐efficient heterogeneous wireless sensor networks 下载免费PDF全文
I. S. AlShawi L. Yan W. Pan B. Luo 《International Journal of Communication Systems》2014,27(12):3581-3599
Energy is an extremely critical resource for battery‐powered wireless sensor networks (WSNs), thus making energy‐efficient protocol design a key challenging problem. However, uneven energy consumption is an inherent problem in WSNs caused by multi‐hop routing and many‐to‐one traffic pattern among sensors. In this paper, we therefore propose a new clustering method called fuzzy chessboard clustering (FFC), which is capable to overcome the bottleneck problem and addressing the uneven energy consumption problem in heterogeneous WSNs. We also propose an energy‐efficient routing method called artificial bee colony routing method (ABCRM) to find the optimal routing path for the heterogeneous WSNs. ABCRM seeks to investigate the problems of balancing energy consumption and maximization of network lifetime. To demonstrate the effectiveness of FCC‐ABCRM in terms of lessening end‐to‐end delay, balancing energy consumption, and maximization of heterogeneous network lifetime, we compare our method with three approaches namely, chessboard clustering approach, PEGASIS, and LEACH. Simulation results show that the network lifetime achieved by FCC‐ABCRM could be increased by nearly 25%, 45%, and 60% more than that obtained by chessboard clustering, PEGASIS, and LEACH, respectively. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献