UNDERGROUND WSN OPTIMIZATION BY ARTIFICIAL IMMUNE BASED CLUSTERING AND HIERARCHICAL ROUTING

Abstract

Most of the underground work is highly risky as safety of human and instrument need escape time. For this continuous monitoring of such mines is on demand. As mining networks are temporary hence wireless networks were preferred this increases the dependency of node life. This paper has proposed a underground mines wireless sensor network model that increase the life of network. Sensor nodes were lcustered by the artificial immune genetic algorithm this reduces the energy cost of the distanced node. Further routing of packet is static after clustering and in hierarchical structure, so runtime path calculation get reduces. Both these approaches increases the life span of UWSN. Experiment was done on different nodes conditions and result shows that proposed model has increases the number of rounds and packet counts.

Index Terms— Energy Optimization, Clustering, UWSN, Routing.