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Variable duty cycle aware energy efficient clustering strategy for wireless sensor networks

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Abstract

The operational life of the wireless sensor networks (WSNs) primarily depends on the lifespan of individual sensor nodes because in case of the early demise of a node, the data of the certain part of monitoring area will never reach to the base station (BS). Thus the effective utilization of node’s battery energy is a vital issue in WSNs. In this paper, a variable duty cycle technique is introduced for the clustered WSNs. In the proposed technique, initially, the network is partitioned into clusters. The distance centroid of nodes is considered to identify the initial cluster heads (CHs). The successive CHs are identified on the basis of the energy centroid and the distance from the current cluster head (CH). After the formation of clusters, member nodes of the cluster adjust their duty cycles according to the distance from CH and residual energy. In the clustered WSNs, nodes those are in the vicinity of CH consume less energy as compared to the farther nodes since the node's energy depletion in data transmission is related to the distance. Consequently, for the same data transfer rates, the energy consumed by the nodes will be asymmetric, and nodes that are farther from CH completely exhaust their energy earlier than the nearer nodes. In the proposed technique, the farther nodes transmit their data with less duty cycle than the nodes closer to the CH. This technique provides more balanced energy consumption among the nodes. The performance evaluation of the proposed protocol is done using Matlab tool and results are compared with three existing EECPK, MPST and EECA protocols. The simulation results validate that the proposed technique performs better than existing techniques.

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Authors and Affiliations

  1. National Institute of Technology, Hamirpur, Himachal Pradesh, India

    Vinith Chauhan & Surender Soni

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  1. Vinith Chauhan
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  2. Surender Soni
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Correspondence to Vinith Chauhan.

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Chauhan, V., Soni, S. Variable duty cycle aware energy efficient clustering strategy for wireless sensor networks. J Ambient Intell Human Comput 14, 10963–10975 (2023). https://doi.org/10.1007/s12652-022-04363-1

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