Underground WSN Optimization By Sleep, Awake Mode And Genetic Clustering

Abstract

Along with the goals of safe and efficient underground mining operations, reliable communication is a high-stakes problem in the mining industry, which is a tough place to work. Automation through remote and automatic systems has led to improvements in the health and safety of the workplace for workers, the control of operations, the use of energy and money, and the ability to respond to events in real time. In this situation, Wireless Sensor Networks (WSNs) have been used a lot in underground monitoring and communication systems to track workers and tools, watch operations, and keep an eye on the environment. This paper has proposed a model that works in sleep and awake mode to increase the life span of network. Further paper has proposed a modified bio-geographical optimization genetic algorithm for the clustering of the nodes as per energy and distance of nodes. Both of the approach increases the performance of the underground WSN network. Experiment was done on different situation of the WSN and results that proposed model has improved various evaluation parameters values.