全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Balancing Energy Consumption in Clustered Wireless Sensor Networks

DOI: 10.1155/2013/314732

Full-Text   Cite this paper   Add to My Lib

Abstract:

Clustering in wireless sensor networks is an efficient way to structure and organize the network. It aims at identifying a subset of nodes within the network and binding it to a leader (i.e., cluster head). The leader becomes in charge of specific additional tasks like gathering data from all nodes in its cluster and sending them using a longer range communication to a sink. As a consequence, a cluster head exhausts its battery more quickly than regular nodes. In this paper, we present four variants of BLAC, a novel battery level aware clustering family of schemes. BLAC considers the battery level combined with another metric to elect the cluster-head. The cluster-head role is taken alternately by each node to balance energy consumption. Due to the local nature of the algorithms, keeping the network stable is easier. BLAC aims at maximizing the time with all nodes alive to satisfy the application requirements. Simulation results show that BLAC improves the full network lifetime three times more than the traditional clustering schemes by balancing energy consumption over nodes and still deliveres high data ratio. 1. Introduction Multihop wireless sensor networks (MWNs) consist of sets of mobile wireless nodes without support of any preexisting fixed infrastructure. Such large scale wireless sensor networks offer great application perspectives. Wireless sensors are often tiny devices with hardware constraints (low memory storage, low computational resources) that rely on battery. Sensor networks thus require energy-efficient algorithms to make them work properly in a way that suits their hardware features and application requirements. In this paper, we focus on a given application defined by the ANR BinThatThinks (http://binthatthink.inria.fr) project. The project aims to ease the collect and recycling of waste and reduce its cost through the use of wireless sensors placed on dustbins. Dustbins are also equipped with GPRS chips for long range communications. In this paper, our goal is to propose a novel clustering algorithm for wireless sensor networks in which each sensor node sends its data to its cluster head (potentially through Multihop paths) based on the context of the BinThatThinks project. In this context, cluster heads collect data from all sensors in their cluster and send them through their GPRS link. Since activating the GPRS consumes more energy than peer-to-peer communications (as shown in Table 1, Section 6), each node should take the cluster head role in turn in order to allow the network to be operational as long as possible without too

References

[1]  N. Mitton, B. Sericola, S. Tixeuil, E. Fleury, and I. Guérin Lassous, “Self-stabilization in self-organized wireless multihop networks,” Ad-Hoc and Sensor Wireless Networks, vol. 11, no. 1-2, pp. 1–34, 2011.
[2]  Y. Yao and G. B. Giannakis, “Energy-efficient scheduling for wireless sensor networks,” IEEE Transactions on Communications, vol. 53, no. 8, pp. 1333–1342, 2005.
[3]  A. A. Abbasi and M. Younis, “A survey on clustering algorithms for wireless sensor networks,” Computer Communications, vol. 30, no. 14-15, pp. 2826–2841, 2007.
[4]  D. J. Baker and A. Ephremides, “The architectural organization of a mobile radio network via a distributed algorithm,” IEEE Transactions on Communications, vol. 29, no. 11, pp. 1694–1701, 1981.
[5]  M. Gerla and J. Tzu-Chieh Tsai, “Multicluster, mobile, multimedia radio network,” Wireless Networks, vol. 1, no. 3, pp. 255–265, 1995.
[6]  M. Chatterjee, S. K. Das, and D. Turgut, “WCA: a weighted clustering algorithm for mobile ad hoc networks,” Cluster Computing, vol. 5, 2002.
[7]  C. P. Low, C. Fang, J. M. Ng, and Y. H. Ang, “Efficient Load-Balanced Clustering Algorithms for wireless sensor networks,” Computer Communications, vol. 31, no. 4, pp. 750–759, 2008.
[8]  W. Dali and H. A. Chan, “Clustering algorithm to balance and to reduce power consumptions for homogeneous sensor networks,” in Proceedings of the International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM '07), pp. 2723–2726, September 2007.
[9]  T. Shu, M. Krunz, and S. Vrudhula, “Power balanced coverage-time optimization for clustered wireless sensor networks,” in Proceedings of the 6th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MOBIHOC '05), pp. 111–120, May 2005.
[10]  T. Kaur and J. Baek, “A strategic deployment and cluster-header selection for wireless sensor networks,” IEEE Transactions on Consumer Electronics, vol. 55, no. 4, pp. 1890–1897, 2009.
[11]  X. Min, S. Wei-ren, J. Chang-jiang, and Z. Ying, “Energy efficient clustering algorithm for maximizing lifetime of wireless sensor networks,” International Journal of Electronics and Communications, vol. 64, no. 4, pp. 289–298, 2010.
[12]  N. Dimokas, D. Katsaros, and Y. Manolopoulos, “Energy-efficient distributed clustering in wireless sensor networks,” Journal of Parallel and Distributed Computing, vol. 70, no. 4, pp. 371–383, 2010.
[13]  O. Younis, M. Krunz, and S. Ramasubramanian, “Node clustering in wireless sensor networks: recent developments and deployment challenges,” IEEE Network, vol. 20, no. 3, pp. 20–25, 2006.
[14]  T. Anker, D. Bickson, D. Dolev, and B. Hod, “Efficient clustering for improving network performance in wireless sensor networks,” in Wireless Sensor Networks, R. Verdone, Ed., vol. 4913 of Lecture Notes in Computer Science, pp. 221–236, Springer, Berlin, Germany, 2008.
[15]  O. Buyanjargal and Y. Kwon, “AEEC-Adaptive and Energy Efficient Clustering algorithm for content based wireless sensor networks,” in Proceedings of the 2nd International Conference on Computer Science and Its Applications (CSA '09), December 2009.
[16]  K. Donghyun, W. Yiwei, L. Yingshu, Z. Feng, and D. Ding-Zhu, “Constructing minimum connected dominating sets with bounded diameters in wireless networks,” IEEE Transactions on Parallel and Distributed Systems, vol. 20, no. 2, pp. 147–157, 2009.
[17]  W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-efficient communication protocol for wireless microsensor networks,” in Hawaii International Conference on System Sciences (HICSS '00), 2000.
[18]  N. Nikaein, H. Labiod, and C. Bonnet, “DDR-distributed dynamic routing algorithm for mobile ad hoc networks,” in Workshop on Mobile and Ad Hoc Networking and Computing, 2000.
[19]  N. Mitton, Auto-organisation des réseaux sans fil multi-sauts à grande echelle [Ph.D. thesis], INSA, Lyon, France, 2006.
[20]  G. T. Toussaint, “The relative neighbourhood graph of a finite planar set,” Pattern Recognition, vol. 12, no. 4, pp. 261–268, 1980.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133