Authors:
Md. Shamim Hossain,Md. Ibrahim Abdullah,Md. Martuza Ahamad,Md. Alamgir Hossain,Md. Shohidul Islam,DOI NO:
https://doi.org/10.26782/jmcms.2020.01.00020Keywords:
Wireless Sensor Networks,Clustering Algorithm,Cluster Head,Energy-efficiency,Residual Energy,LEACH,Abstract
Wireless sensor nodes have deployed with limited energy sources. The lifetime of a node usually depends on its energy source. The main challenging design issue of the wireless sensor network is to prolong the network lifetime and prevent connectivity degradation by developing an energy-efficient routing protocol. Many research works are done to extend the network lifetime, but still, it is a problem because of the impossibility of recharging. In this paper, we present a hierarchical clustering technique for wireless sensor network called Clustering with Residual Energy and Neighbors (CREN). It is based on two basic parameters, e.g., number of neighbors of a node and its residual energy. We use these properties as a weighted factor to elect a node as a cluster head. A well-known method, LEACH had a high performance in energy saving and the quality of services in the wireless sensor network. Like Low-Energy Adaptive Clustering Hierarchy (LEACH), CREN rotates the cluster head among the sensor nodes to balance the energy consumption. The simulation result shows the proposed technique achieves much higher performance and energy efficiency than LEACH.Refference:
I. A. John, and K. V. Babu (2017). Two Phase Dynamic Method for Clustering Head Selection in Wireless Sensor Network for Internet of Things Applications, pp: 1228-1232, IEEE WiSPNET conference.
II. C. Li, M. Ye, G. Chen, J. Wu (2005). An energy-efficient unequal clustering mechanism forwireless sensor networks, Proceedings of the 2nd IEEE international conference on mobile ad-hoc and sensor systems (MASS’05).
III. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. (2002). A survey on sensor networks, IEEE Communications Magazine, 40(8):102–14.
IV. G. H. Raghunandan, Dr. A. S. Rani,S. Y. Nanditha, G. Swathi (2017). Hierarchical Agglomerative Clustering based Algorithm for Overall Efficiency of Wireless Sensor Network, pp: 1290-1293, International Conference on Intelligent Instrumentation and Control Technologies (ICICICT), IEEE.
V. Huamei Qi, Fengqi Liu, Tailong Xiao , and Jiang Su (2018). A Robust and Energy-Efficient Weighted Clustering Algorithm on Mobile Ad Hoc Sensor Networks, MDPI,Algorithms, 11, 116; doi:10.3390/a11080116. J. Mech. Cont.& Math. Sci., Vol.-15, No.-1, January (2020) pp 263-274
Copyright reserved © J. Mech. Cont.& Math. Sci.
Md. Shamim Hossain et al
274
VI. H. S. Lee, K. T. Kim, H. Y. Youn (2006). A new cluster head selection
scheme for long lifetimeof wireless sensor networks, Lecture Notes in
Computer Science, 3983, 519–528.
VII. H. Ayadi, A. Zouinkhi, T. Val, A. van den Bossche, and M. N. Abdelkrim,
“Network Lifetime Management in Wireless Sensor Network,” IEEE Sensors
Journal, 2018.
VIII. K. Akkaya, M. Younis (2004). A survey on Routing Protocols for Wireless
Sensor Networks, Computer Networks (Elsevier) Journal.
IX. K. Akkaya, M. Demirbas, R.S. Aygun (2006). The impact of data
aggregation on the performance of wireless sensor networks: a survey, Wiley
Journal of Wireless Communications and Mobile Computing.
X. O. Younis, S. Fahmay, “HEED: a hybrid, energy-efficient,
distributedclustering approach for ad hoc sensor networks”, IEEE
Transactions on Mobile Computing 3 (4), pp. 366–379, 2004.
XI. S. Selvakennedy, S. Sinnappan, Y. Shang, “A biologically-inspired clustering
protocol for wireless sensor networks”,Computer Communications, 30, pp.
2786–2801, 2007.
XII. S. K. M. Yendamuri, A. Singh, Dr. J. P. Priyadarsini M (2018). An Improved
Three-Layer Clustering Hierarchy for Wireless Sensor Networks: A Proposed
Framework, 9th ICCCNT2018, July 10-12, 2018, IISC, Bengaluru, India.
XIII. T. Gao, R. C. Jin, J. Y. Song, T. B. Xu · Li D. Wang (2010). Energy-Efficient
Cluster Head Selection Scheme Based on Multiple Criteria Decision Making
for Wireless Sensor Networks, Wireless Personal Communication, Springer.
XIV. T. Shu, M. Krunz, S. Vrudhula (2005). “Power balanced coverage-time
optimization for clustered wireless sensor networks”, in Proceedings of ACM
MobiHoc’05, pp. 111–120.
XV. W. Heinzelman, A. Chandrakasan, and H. Balakrishnan (2000). Energyefficient
communication protocol for wireless sensor networks, in the
Proceeding of the Hawaii International Conference System Sciences, Hawaii.
XVI. Z. Cheng, L. Hongbing and H. Yi (2018). Mechanism of immune system
based topology control clustering algorithm in wireless sensor networks,
IEEE.