A Low Energy Time Based Clustering Technique for Routing in Wireless Sensor Networks

Farzad Omidi-Kashani^1, , Ouadoudi Zytoune^2, , Driss Aboutajdine³ and Seyed Mohammad Ata Sharifi Dalooei⁴

¹Associate Professor of Orthopedic and Spine Surgery, Orthopedic Research Center, Orthopedic Department, Imam Reza Hospital, Mashhad University of Medical Sciences, Mashhad, Iran

²LaRIT lab., Université Ibn tofail, Kénitra, Morocco

³LRIT lab., Faculté des sciences, Rabat, Morocco

⁴Orthopedic Resident, Orthopedic Research Center, Orthopedic Department, Imam Reza Hospital, Mashhad University of Medical Sciences, Mashhad, Iran

Cite this paper:
Farzad Omidi-Kashani, Ouadoudi Zytoune, Driss Aboutajdine and Seyed Mohammad Ata Sharifi Dalooei. A Low Energy Time Based Clustering Technique for Routing in Wireless Sensor Networks. American Journal of Sensor Technology. 2014; 2(1):1-6. doi: 10.12691/ajst-2-1-1

Abstract

A Wireless sensor network (WSN) is a collection of tiny sensor nodes that are deployed to monitor the environment. These sensor nodes have limited capabilities, especially the energy reserve and processing ability. So, the routing protocols design for this kind of networks is a crucial challenge. Because these routing protocols should be simple, energy-efficient, and robust to deal with a very large number of nodes, they should also be self-configurable to node failures and changes of the network topology dynamically. The most proposed routing techniques organize the network in clusters where the sensing area is divided into many sub-areas. This paper presents a new algorithm for clustering in WSN based on the node residual energy compared to the network one and allowing a better partitioning of the network area which enhance the data distortion at the sink by using the best data coding rate at the cluster head. The simulation results show that this algorithm allows network stability extension compared to the most known clustering algorithm.

Keywords:
wireless sensor networks energy efficiency clustering-based algorithm data aggregation data compression

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References:

[1]	I. F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, “A survey on sensor networks,” IEEE Communications Magazine, vol. 40, no. 8, pp. 102-114, 2002.
[2]	Lan Tien Nguyen, Xavier Defago, Razvan Beuran, Yoichi Shinoda, “An Energy Efficient Routing Scheme for Mobile Wireless sensor Networks”, IEEEISWCS 2008, pg. 568-572.
[3]	Juhana Yrjola "Summary of Energy Efficiency Communication Protocol for Wireless Micro Sensor Networks", 13th March 2005.
[4]	Chandrakasan, et al., “Design considerations for distributed micro-sensor systems,” Proc. IEEE 1999 Custom Integrated Circuits Conference (CICC’99), San Diego, CA, USA, May 1999, pp. 279-286.
[5]	D. Estrin, L. Girod, G. Pottie, and M. Srivastava, “Instrumenting the world with wireless sensor networks,” Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2001), Salt Lake City, Utah, USA, May 2001, vol. 4, pp. 2033-2036.
[6]	D. Estrin, R. Govindan, J. Heidemann, and S. Kumar, “Next century challenges: Scalable coordination in sensor networks,” Proc. 5th Annual ACM/IEEE International Conference on Mobile Computing and Networking, Seattle Washington, USA, August 1999, pp. 263-270.
[7]	Jamil Ibriq and Imad mahgoub,“Cluster-Based Routing inWSN: Issues and Challenges” Spects 2004,ISBN, pp. 759-766.
[8]	Yazeed Al-Obaisat and Robin Braun,The Book on “On Wireless Sensor Networks: Architectures, Protocols,Applications and Management”.
[9]	Ki Young Jang,kyung Tae Kim,Hee Yong Youn,“An Energy Efficient Routing Scheme for Wireless Sensor Networks” ,Computational Science and its Application 2007.ICCSA 2007,International Conference on Volume.Issue,26-29 August 2007.
[10]	Quanhong Wang, H. Hassanein, and Takahara, G., “Stochastic Modeling of Distributed, Dynamic, Randomized Clustering Protocols for Wireless Sensor Networks,” Proc. International Conference on Parallel Processing Workshops (ICPPW’04), Montreal, Quebec, Canada, August 2004, pp. 456-463.
[11]	W.R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-efficient Communication Protocol for Wireless Microsensor Networks”, in IEEE Computer Society Proceedings of the Thirty Third Hawaii International Conference on System Sciences (HICSS '00), Washington, DC, USA, Jan. 2000, vol. 8, pp. 8020.
[12]	W.R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “An Application-Specific Protocol Architecture for Wireless Microsensor Networks” in IEEE Transactions on Wireless Communications (October 2002), vol. 1(4), pp. 660-670.
[13]	S. Lindsey and C.S. Raghavendra, “PEGASIS: Powerefficient Gathering in Sensor Information System”, Proceedings IEEE Aerospace Conference, vol. 3, Big Sky, MT, Mar. 2002, pp. 1125-1130.
[14]	A. Manjeshwar and D. P. Agrawal, “TEEN: A Protocol for Enhanced Efficiency in Wireless Sensor Networks”, in the Proceedings of the 1st International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile Computing, San Francisco, CA, April 2001.
[15]	W. Lou, “An Efficient N-to-1 Multipath Routing Protocol in Wireless Sensor Networks”, Proceedings of IEEE MASS05, Washington DC, Nov. 2005, pp. 1-8.
[16]	A. Bestavros G. Smaragdakis, I. Matta. “Sep: A stable election protocol for clustered heterogeneous wireless sensor networks”. In Second International Workshop on Sensor and Actuator Network Protocols and Applications (SANPA 2004), 2004.
[17]	M.W. Wang L. Qing, Q.X. Zhu. “Design of a distributed energy- efficient clustering algorithm for heterogeneous wireless sensor networks”. Computer Communication (Elsevier), 29(12): 2230-2237, 2006.
[18]	A. Manjeshwar and D. P. Agrawal, “APTEEN: A Hybrid Protocol for Efficient Routing and Comprehensive Information Retrieval in Wireless Sensor Networks”, in the Proceedings of the 2nd International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile computing, San Francisco CA, April 2001, pp. 2009-1015.
[19]	I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless Sensor Networks: A Survey,” Computer Networks Journal, vol. 38, no. 4, pp. 393-422, March 2002.
[20]	I. F. Akyildiz, M. C. Vuran and O. B. Akan, “On Exploiting Spatial and Temporal Correlation in Wireless Sensor Networks”. In Proceedings of WiOpt 2004: Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, 2004, pages 71-80.
[21]	H. Chen , H. Mineno and T. Mizuno, “Adaptive data aggregation scheme in clustered wireless sensor networks” Computer Communications (elsevier), 31 (2008) pp. 3579-3585.
[22]	O. Zytoune , Y. fakhri and D. Aboutajdine, “Time Based Clustering Technique for Routing in Wireless Sensor Networks”. International Conference on Multimedia Computing and Systems (ICMCS), 7-9 April 2011. Pages: 1-4.
[23]	R. Cristescu, B. Beferull-Lozano, M. Vetterli. “On Network Correlated Data Gathering,” Twenty-Third Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), 2004, pp. 2571-2582.
[24]	G. L. Stuber, “ Principles of Mobile Communications”, Kluwer Academic Publisher, 2001.
[25]	C. Hua and T. P. Yum, “Data aggregated maximum lifetime routing for wireless sensor networks,” Ad Hoc Networks 6 (2008) pp. 380-392.
[26]	Ganeriwal, S., Kumar, R., Srivastava, M. (2003). “Timing-Sync Protocol for Sensor Networks.”, The First ACM Conference on Embedded Networked Sensor Systems (SenSys), pp. 138-149.
[27]	Tian, Z., Luo, X., Giannakis, G.B., “Cross-layer sensor network synchronization.”, Signals, Systems and Computers. Conference Record of the Thirty-Eighth Asilomar Conference, Volume 1, 7-10, p. 1276 - 1280.
[28]	T. Cover and J. Thomas, “Elements of Information Theory,” Wiley Series in Telecommunications. John Wiley and Sons, Inc., 1991.
[29]	S. Bandyopadhyay, E.J. Coyle, An energy efficient hierarchical clustering algorithm for wireless sensor networks, in: Proceeding of INFOCOM 2003, April 2003.Vol. 3, pp. 1713-1723.