Computational Intelligence in Wireless Sensor Network

EasyChair Preprint 4951

Abstract

The wireless sensor networks (WSNs) are event-monitoring and data collecting devices which are tightly distributed, lightweight nodes deployed in large number to monitor the environment or system. They are generally deployed for periodic reporting and event detection in an environment. WSN faces many challenges like design and deployment of sensor nodes, mobility and topology changes, localization and physical distribution, clustering, data aggregation, security, and quality of service management. An intelligent-based approach works more efficiently as sensor nodes are deployed in dynamic environments. Computational intelligence provides autonomous behavior, flexibility, robustness against topology changes, communication failures. The most common computational intelligence (CI) paradigms such as fuzzy systems, artificial neural networks, evolutionary algorithm, swarm intelligence, and artificial immune systems are explored in this paper.

Keyphrases: Computational Intelligence, Fuzzy Logic, Reinforcement Learning, Wireless Sensor Networks, neural networks

@booklet{EasyChair:4951,
  author    = {Pranesh Nanoskar and Pradnya Mhatre},
  title     = {Computational Intelligence in Wireless Sensor Network},
  howpublished = {EasyChair Preprint 4951},
  year      = {EasyChair, 2021}}