Abstract

Wireless sensor networks (WSNs) are a family of wireless networks that usually operate with irreplaceable batteries. The energy sources limitation raises the need for designing specific protocols to prolong the operational lifetime of such networks. These protocols are responsible for messages exchanging through the wireless communications medium from the sensors to the base station (sink node). Therefore, the determination of the optimal location of the sink node becomes crucial to assure both the prolongation of the network's operation and the quality of the provided services. This paper proposes a novel algorithm based on a Particle Swarm Optimization (PSO) approach for designing an energy-aware topology control protocol. The deliverable of the algorithm is the optimal sink node location within a deployment area. The proposed objective function is based on a number of topology control protocol's characteristics such as numbers of neighbors per node, the nodes’ residual energy, and how they are far from the center of the deployment area. The simulation results show that the proposed algorithm reveals significant effectiveness to both topology construction and maintenance phases of a topology control protocol in terms of the number of active nodes, the topology construction time, the number of topology reconstructions, and the operational network's lifetime.

Highlights

  • The increasing needs for ubiquitous devices to interact with the physical world have developed the importance of wireless sensor networks (WSNs) in a number of applications

  • This paper proposes an energy-aware sink node localization algorithm for a topology control protocol using a Particle Swarm Optimization technique

  • The results cannot be generalized to different deployment scenarios, the experiments of uniform distribution of nodes within the deployment area show that the sink node Particle Swarm Optimization (PSO)-based localization algorithm needs shorter time to construct a topology than the basic topology protocol (BTP)

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Summary

Introduction

The increasing needs for ubiquitous devices to interact with the physical world have developed the importance of wireless sensor networks (WSNs) in a number of applications. These applications may include military [1], remote environmental monitoring [2], smart road monitoring [3], and remote patient monitoring [4] applications. The major challenges attached with such applications are related to the wireless sensor networks’ limitations, where a sensor node has a limited energy source, a small memory footprint, and low computational capability processor.

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