Distance-aware Hierarchical Data-collecting Path Selection for Mobile Sink in Sparse WSNs

Abstract

A Mobile Sink (MS) is a device that can be used to collect data from sparsely deployed sensor nodes by visiting the sensor nodes in close proximity. Various existing schemes face the problem of bottlenecks during data transmission to the MS as only a few sensor nodes are chosen to transmit data. In this article, we propose the Distance-aware Hierarchical Data-collecting Path Selection (DHDP) algorithm that aims to determine optimal Rendezvous Points (RPs) using the Range bound Hierarchical Agglomerative Clustering (R-HAC) and check the cluster's quality based on Average Silhouette Width (ASW). Further, we exploit Ant Colony Optimization (ACO) to determine the optimal path for the mobile sink to follow. To reduce the energy consumption of sensor nodes, we appoint Collection Agents (CA) to transmit data directly to the mobile sink when the sensor node comes within transmission range. The extensive simulation indicates significant improvements in network lifetime and end-to-end data delivery latency compared to the state-of-the-art methods in sparse networks.