EECDC: An energy Efficient and Coverage-Aware Distributed Clustering Protocol for Wireless Sensor Networks
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2018 by IJETT Journal|
|Year of Publication : 2018|
|Authors : A. Maizate, S. Aouad
|DOI : 10.14445/22315381/IJETT-V62P203|
MLA Style: A. Maizate, S. Aouad "EECDC: An energy Efficient and Coverage-Aware Distributed Clustering Protocol for Wireless Sensor Networks" International Journal of Engineering Trends and Technology 62.1 (2018): 10-14.
APA Style:A. Maizate, S. Aouad (2018). EECDC: An energy Efficient and Coverage-Aware Distributed Clustering Protocol for Wireless Sensor Networks. International Journal of Engineering Trends and Technology, 62(1), 10-14.
Despite the developments of a few years wireless sensor networks, several constraints continue to limit their development and degrade the performance of their applications and services. Due to their limited power and signal range, some or all of the sensors may stop functioning, leading to the deterioration of network functionality such as monitoring, detection and data transfer. These networks require robust wireless communication protocols that are energy efficient. Thus, it is a challenge for the self organization protocols to provide network survivability and redundancy features. In this paper, we present a novel clustering algorithm called EECDC (An energy efficient and coverage-aware distributed clustering protocol for wireless sensor networks), which aims to improve the applications performance and the quality of service (QoS) by exploiting geometry techniques. Better coverage, energy efficiency, minimum traffic from nodes to base station, balanced energy consumption are the main features of EECDC to improve life time of WSN. Simulation results confirm that EECDC is effective in prolonging the network lifetime as well as in improving the network coverage.
 Abbasi AA, Younis M. A survey on clustering algorithms for wireless sensor networks. Comput Commun 2007;30:2826–41.
 Anastasi G, Conti M, Di Francesco M, Passarella A. Energy conservation in wireless sensor networks: a survey. Ad Hoc Netw 2009;7:537–68.
 Akyildiz IF, Su W, Sankarasubramaniam Y, Cayirci E. Wireless sensor networks: a survey. Comput Netw 2002;38:393–422.
 Ali, Ahmad, et al. "Enhancement of RWSN Lifetime via Firework Clustering Algorithm Validated by ANN." Information 9.3 (2018): 60.
 Agrawal, Deepika, and Sudhakar Pandey. "FUCA: Fuzzy based unequal clustering algorithm to prolong the lifetime of wireless sensor networks." International Journal of Communication Systems 31.2 (2018).
 Asif, Mohd, and Harjit Singh. "A Review on Design and Analysis of Lifetime Efficient Protocol in Distributed Clustering of WSN." International Journal of Engineering Science 17137 (2018).
 Mohammad M. Hasan and Jason P. Jue, “Survivable SelfOrganization for Prolonged Lifetime in Wireless Sensor Networks,” International Journal of Distributed Sensor Networks, Volume 2011, pp. 1-11, 2011.
 Maizate, A., El Kamoun, N., A new metric based cluster head selection technique for prolonged lifetime in wireless sensor networks, (2013) International Journal on Communications Antenna and Propagation (IRECAP), 3 (4), pp. 227-236.
 Al-Tabbakh, Shahinaz M., and Eman Shaaban. "Energy Aware Autonomous Deployment for Mobile Wireless Sensor Networks: Cellular Automata Approach." International Conference on Applied Physics, System Science and Computers. Springer, Cham, 2017.
 Jabbar, Sohail, et al. "Designing an Energy-Aware Mechanism for Lifetime Improvement of Wireless Sensor Networks: a Comprehensive Study." Mobile Networks and Applications(2018): 1-14.
 Heinzelman W,Chandrakasan A,Balakrishnan H. Energy-efficient Communication Protocol for Wireless Sensor Networks[C]//Proceeding of the Hawaii International Conference System Sciences,Hawaii,January 2000.
 D. Curren, “A survey of simulation in sensor networks,” 2006, http://www.cs.binghamton.edu/kang/teaching/cs580s/.
 G. Chen, J. Branch, M. Pflug, L. Zhu, and B. Szymanski, “SENSE: a wireless sensor network simulator,” in Advances in Pervasive Computing and Networking, chapter 13, Kluwer Academic, Boston,Mass, USA, 2004.
Wireless Sensor Network; Self-Organization; ClusterHead; Clustering; energyefficiency; network coverage.