Wireless Sensor Network: Applications, Challenges, and Algorithms

Wireless sensor network (WSN) is a collection of sensor nodes that distributed in an arbitrary manner to solve a particular problem. The position of the node is predefined and based on random nature. Each node directly or indirectly connected with the base station (BS). BS is used to control and manages all sensor nodes. WSN is used in several applications such as disaster management, entertainment, education, environment monitoring. Although the applications of WSN increase rapidly in the modern era, it has several limitations such as limited energy capacity of the nodes, shortage memory capacity of the nodes as well as limited computational capacity. These limitations cause frequently changing the infrastructure of the WSN which has high complexity, and it causes the failure of the current operation. Hence, to overcome these problems several nature-inspired algorithms are designed such as swarm optimization, ant colony optimization, particle swarm optimization, Africa buffalo optimization, genetic algorithm, teaching-learning based optimization, etc. The basic aim of these optimizations is to solve several conflicting objectives of the WSN efficiently in terms of some parameters.