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An energy-aware clustering and two-level routing method in wireless sensor networks

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Wireless sensor networks (WSN) are consisted of several sensor nodes scattered in an area to gather data from their ambient environment and send it to base station (BS). The energy of nodes in WSNs is limited. One of the most significant issues in WSNs is reducing the energy consumption of nodes, which leads to increased network lifetime. One method to reduce energy consumption in WSNs is energy-efficient routing. In energy-efficient routing, gathered data is sent to the sink in a way to save the energy of nodes. This paper proposed a cluster-based two-level routing method. In the proposed method, we seek to improve packet delivery rate and reduce energy consumption through clustering, selecting backup cluster head (BCH), layering cluster heads (CH), and dividing each cluster into four sections. The method is consisted of two phases. In the first phase, CHs and BCHs are selected, and nodes are clustered based on their residual energy, distance to BS, and centrality. To perform intra-cluster routing, each cluster is divided into four sections so that nodes directly deliver their data to CH or through the most proper node in their sections. To perform inter-cluster routing, CHs are layered based on their distance to BS. Since CHs are layered, the source CH selects the next hop from CHs in the upper layer based on their residual energy and distance to BS. The proposed method has been simulated by NS-2 software and compared with CFPT (Yarinezhad and Hashemi in J Syst Softw 155:145–161, 2019), FBCFP (Thangaramya et al. in Comput Netw 151:211–223, 2019) and DFCR (Azharuddin et al. in Comput Electr Eng, 41:177–190, 2015) methods. The results reveal that the proposed method leads to reduced end-to-end delay, number of total hops, energy consumption as well as increased packet delivery rate and network lifetime.

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Correspondence to Hamid Barati.

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Mosavifard, A., Barati, H. An energy-aware clustering and two-level routing method in wireless sensor networks. Computing 102, 1653–1671 (2020). https://doi.org/10.1007/s00607-020-00817-6

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