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      Energy Efficient Secure Trust Based Clustering Algorithm for Mobile Wireless Sensor Network

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          Abstract

          The main benefit of selecting a suitable node as cluster head (CH) in clustering for wireless mobile sensor networks (MWSNs) is to prolong the network lifetime. But the safe selection of CH is a challenging task by taking security into account. Mostly CH selection algorithms in MWSN do not consider security when selecting CH. We have proposed secure CH selection algorithm by calculating weight of each node to deal with secure selection using minimum energy consumption. The weight of node is a combination of different metrics including trust metric (behaviors of sensor node) which promotes a secure decision of a CH selection; in terms of this, the node will never be a malicious one. The trust metric is definitive and permits the proposed clustering algorithm to keep away from any malignant node in the area to select a CH, even if the rest of the parameters are in its favor. Other metrics of node include waiting time, connectivity degree, and distance among nodes. The selection of CHs is completed utilizing weights of member nodes. The preparatory outcomes acquired through simulation exhibit the adequacy of our proposed scheme as far as average rate of avoiding malicious node as a CH, energy efficiency, and some other performance parameters are concerned.

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          Most cited references11

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          Wireless sensor network survey

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            A survey on clustering algorithms for wireless sensor networks

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              RF Energy Harvesting and Transport for Wireless Sensor Network Applications: Principles and Requirements

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                Author and article information

                Journal
                Journal of Computer Networks and Communications
                Journal of Computer Networks and Communications
                Hindawi Limited
                2090-7141
                2090-715X
                2017
                2017
                : 2017
                :
                : 1-8
                Article
                10.1155/2017/1630673
                7e80d9ff-29a0-4138-bd62-8bca82d5102a
                © 2017

                http://creativecommons.org/licenses/by/4.0/

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