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DDCD Algorithm based Energy Efficient Clustering for WSNs
Objectives: In Wireless Sensor Networks (WSNs) the nodes are moving in different geographical conditions and the nodes may be left looked after for a long period of time. So to increase the network life time and to reduce the traffic the energy should be conserved. Energy efficient WSNs will lose for a long period time. Methods/Analysis: To increase network lifetime different methods like data aggregation, cluster head, network coding, correlating data set, etc can be used for correlated data environment. These methods are used to calculate to increase the network lifetime. DDCD (Data Density Correlation Degree) algorithm on wireless sensor network is works as a middleware for aggregating data sustained by a more number of nodes within a network. Findings: The problem encountered in the recent past was of the more battery power consumption. Therefore, this paper proposed the efficient and effective mechanism of energy efficient procedures for data aggregation in wireless sensor network and increase the network lifetime. Application/Improvement: The results of the simulation are acceptable showing the DDCD algorithm to have good performance abilities compared to the Weighted-Low Energy Adaptive Clustering Hierarchy and Ant Colony Optimization algorithms. This process is useful where the sensor nodes are densely established.
Clustering Head, Data Aggregation, DDCD, Wireless Sensor Networks (WSNs).
- Yick J, Mukherjee B, Ghosal D. Wireless sensor network survey. Comput Netw. 2008; 52(12):2292–330.
- Zhu C, Zheng C, Shu L, Han G. A survey on coverage and connectivity issues in wireless sensor networks. J Netw Comput Appl. 2012; 35(2):619–32.
- Yuan J, Chen H. The optimized clustering technique based on spatial-correlation in wireless sensor networks. Proc IEEE Youth Conf Inf Comput Telecommun, YC-ICT; 2009 Sep. p. 411–4.
- Vuran MC, Akan OB, Akyildiz IF. Spatiotemporal correlation: Theory and applications for wireless sensor networks. Comput Netw. 2004; 45(3):245–59.
- Ma Y, Guo Y, Tian X, Ghanem M. Distributed clusteringbased aggregation algorithm for spatial correlated sensor networks. IEEE Sensors J. 2011 Mar; 11(3):641–8.
- Vuran MC, Akyildiz IF. Spatial correlation-based collaborative medium access control in wireless sensor networks. IEEE/ACM Trans Netw. 2006 Apr; 14(2):316–29.
- Rajeswari A, Kalaivaani P. Energy efficient routing protocol for wireless sensor networks using spatial correlation based medium access control protocol compared with IEEE 802.11. Proc Int Conf PACC; 2011 Jul. p. 1–6.
- Sivakumar S, Diwakaran S. An energy efficient routing technique to improve the performance of wireless sensor network through adaptive tree based sink relocation. 2014 IEEE International Conference on Computational Intelligence and Computing Research; 2014.
- Al-Karaki JN, Ul-Mustafa R, Kamal AE. Data aggregation and routing in wireless sensor networks: Optimal and heuristic algorithms, Comput Netw. 2009; 53(7):945–60.
- Hua C, Yum TS. Optimal routing and data aggregation for maximizing lifetime of wireless sensor networks. IEEE/ ACM Trans Netw. 2008 Aug; 16(4):892–903.
- Fan G, Jin S. Coverage problem in wireless sensor network: A survey. J Netw. 2010; 5(9):1033–40.
- Kaur J, Gaba GS, Miglani R, Pasricha R. Energy efficient and reliable WSN based on improved leach-R clustering techniques. Indian Journal of Science and Technology. 2015 Jul; 8(16):1–6. DOI: 10.17485/ijst/2015/v8i16/70896.
- Rao Y, Chalapathi Ch, Rani S, Basha SS. Efficient clustering and energy optimization algorithm for WSNs: An approach in environment monitoring system. 2015 International Conference on Innovations in Information Embedded and Communication Systems (ICIIECS); 2015. p. 927–35.
- Okdem S, Karaboga D. Routing in wireless sensor networks using ant colony optimization. Proc 1st NASA/ESA Conf Adapt Hardware Syst; Istanbul. 2006 Jun 15-18. p. 401–4.
- Zhang C. Cluster-based routing algorithms using spatial data correlation for wireless sensor networks. Journal of Communications. 2010 Mar; 5(3):232–8.
- Garey ML, Johnson DS. Computers and intractability: A guide to the theory of NP completeness. San Francisco: W. H. Freeman; 1979.
- Fei Y, Zhan Y, Wang Y. Data density correlation degree clustering method for data aggregation in WSN. IEEE Sensors Journal. 2014; 14(4):1089–98.
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