Optimal rendezvous points selection and mobile sink trajectory construction for data collection in WSNs

Autor: Chandra Sekhara Rao Annavarapu, Bala Gangadhara Gutam, Yu-Chen Hu, Praveen Kumar Donta
Rok vydání: 2021
Předmět:
Zdroj: Journal of Ambient Intelligence and Humanized Computing. 14:7147-7158
ISSN: 1868-5145
1868-5137
DOI: 10.1007/s12652-021-03566-2
Popis: In wireless sensor networks (WSNs), the energy-hole or hotspot problem is an important, challenging issue because it isolates some nodes from the sink. The hotspot problem is addressed by introducing a mobile sink, where the mobile sink traverse in the WSN, collects the data from rendezvous points (RPs) instead of visiting each sensor node. But, selecting the best set of RPs and mobile sink trajectories is challenging in the WSNs. In this context, this paper proposes an optimal RP and trajectory construction (ORPSTC) for the mobile sink in WSNs for data collection. Initially, we apply the minimum spanning tree-based clustering approach for RP selection. In this stage, an RP is identified from each partition, whereas other nodes can transmit the data to RP. Next, we construct a trajectory for mobile sink among all the RPs, including the sink node using a computational geometric method. It results in a near-optimal route with minimal computational resources. Further, we also apply the RP re-selection and virtual RP selection strategy to balance the energy among the SNs. We simulate and evaluate the proposed ORPSTC and existing approaches, and the proposed work outperforms among them.
Databáze: OpenAIRE
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