Data Aggregation Scheme Using Multiple Mobile Agents in Wireless Sensor Network
Mohamed Younis Mohamed Alzarroug1, Wilson Jeberson2
1Mohamed Younis Mohamed Alzarroug, Research Scholar, Department of Computer Science & I.T, Sam Higginbottom University of Agriculture Technology and Sciences SHUATS, (Uttar Pradesh), India.
2Wilson Jeberson, Professor and Head, Department of Computer Science & I.T, Sam Higginbottom University of Agriculture, Technology and Sciences SHUATS, (Uttar Pradesh), India.
Manuscript received on 18 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 3440-3447 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B15790982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1579.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Wireless Sensor Nodes (WSN) has restricted sensing, communication and computational capabilities, in addition, are mainly operated by means of batteries in a bad atmosphere with the non-replenish-able power sources. As Data aggregation (DA) has more significance in solving the chief limitations of utilizing WSNs, say, the restricted battery life of the powered sensors in addition to short-communication gamut of sensors, it becomes an active research domain today. Effectively gathering data has constantly been the principal significance in WSNs. Regarding the static sink, nodes next to the sink would encompass more loads for routing data, and consequently Mobile Agent (MA) has been commenced. At the moment, the MA could move itself to the sensor nodes (SN) for amassing the data. This MA has made the gathering and aggregation of data possible in a means that is suitable for instantaneous applications. This work proposes an effective DA Scheme in WSN that employs manifold MAs for aggregating data in addition to transferring it to the sink centred on Itinerary planning. This could well be attained by grouping the nodes in clusters as well as planning itineraries effectually amongst cluster heads (CHs) alone. In the proposed DA scheme, itinerary planning is performed utilizing Hybrid Ant Colony Optimization-Genetic Algorithm (ACO-GA). Ultimately, the sink sends the MAs for amassing data as of the CH. Simulation outcome confirms clearly that the proposed work shows high-level performance than the other traditional techniques.
Keywords: Wireless Sensor Network, Data Aggregation, Mobile Agents, Cluster Head, Ant Colony Optimization, Genetic Algorithm, and Itinerary Planning.
Scope of the Article: Wireless ad hoc & Sensor Networks