Wireless sensor networks (WSNs) are networks of
autonomous nodes used for monitoring an environment. Devel-
opers of WSNs face challenges that arise from communication
link failures, memory and computational constraints, and limited
energy. Many issues in WSNs are formulated as multidimensional
optimization problems, and approached through bio-inspired
techniques. Particle swarm optimization (PSO) is a simple,
effective and computationally efficient optimization algorithm.
It has been applied to address WSN issues such as optimal
deployment, node localization, clustering and data-aggregation.
This paper outlines issues in WSNs, introduces PSO and discusses
its suitability for WSN applications. It also presents a brief survey
of how PSO is tailored to address these issues.