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Genetic Algorithm based Energy Efficient Data Gathering in Wireless Sensor Networks

T. Sujithra, R. Venkatesan. Published in Artificial Intelligence

International Journal of Applied Information Systems
Year of Publication: 2016
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: T. Sujithra, R. Venkatesan
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  1. T Sujithra and R Venkatesan. Genetic Algorithm based Energy Efficient Data Gathering in Wireless Sensor Networks. International Journal of Applied Information Systems 11(2):1-7, July 2016. URL, DOI BibTeX

    	author = "T. Sujithra and R. Venkatesan",
    	title = "Genetic Algorithm based Energy Efficient Data Gathering in Wireless Sensor Networks",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "July 2016",
    	volume = 11,
    	number = 2,
    	month = "Jul",
    	year = 2016,
    	issn = "2249-0868",
    	pages = "1-7",
    	numpages = 7,
    	url = "",
    	doi = "10.5120/ijais2016451551",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"


In this paper genetic algorithm based energy efficient data gathering approach is proposed to maximize the network lifetime in terms of rounds. The proposed approach has two phases, namely a setup phase and steady state phase. In the setup phase, the cluster formation is done based on the query sent by the base station in a dynamic fashion. The nodes, which satisfy the query are only allowed to participate in the clustering process others go to the sleep mode immediately. In which relay nodes are used as routing element, it collects the aggregated information from the cluster head and transmits to the base station via other relay node in a multi-hop fashion. It balances the network load among the relay nodes. It also reduces the packet loss because of data traffic. From the simulation results, we show that the proposed approach outperforms than the existing protocol in terms of increased network lifetime and decreased energy consumption.


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Multi-hop communication, Cluster centroid, Network lifetime, Cluster head, Relay node, Genetic algorithm.