Affiliations 

  • 1 Department of Computer Science and Design, Kongu Engineering College, Erode, Tamil Nadu, India
  • 2 Department of Software Engineering, Jeonbuk National University, Jeonju, Republic of Korea
  • 3 Department of Computing and Information Systems, Sunway University, Malaysia, Kuala Lumpur, Malaysia
PeerJ Comput Sci, 2024;10:e2407.
PMID: 39650484 DOI: 10.7717/peerj-cs.2407

Abstract

Wireless Sensor Networks (WSNs) have paved the way for a wide array of applications, forming the backbone of systems like smart cities. These systems support various functions, including healthcare, environmental monitoring, traffic management, and infrastructure monitoring. WSNs consist of multiple interconnected sensor nodes and a base station, creating a network whose performance is heavily influenced by the placement of sensor nodes. Proper deployment is crucial as it maximizes coverage and minimizes unnecessary energy consumption. Ensuring effective sensor node deployment for optimal coverage and energy efficiency remains a significant research gap in WSNs. This review article focuses on optimization strategies for WSN deployment, addressing key research questions related to coverage maximization and energy-efficient algorithms. A common limitation of existing single-objective algorithms is their focus on optimizing either coverage or energy efficiency, but not both. To address this, the article explores a dual-objective optimization approach, formulated as maximizing coverage Max ∑(i = 1) ^ N Ci and minimizing energy consumption Min ∑(i = 1) ^ N Ei for the sensor nodes, to balance both objectives. The review analyses recent algorithms for WSN deployment, evaluates their performance, and provides a comprehensive comparative analysis, offering directions for future research and making a unique contribution to the literature.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.