Genetic Algorithm with a New Fitness Function to Enhance WSN lifetime

Deploying and maintaining wireless sensor networks (WSN) in remote places like volcano eruption, battle field, nuclear reactors and dense forest areas is pretty difficult or even sometimes impossible. Therefore there is a need to make a WSN which can function for long duration of time. Lifetime enhancement of WSN is a critical issue to be addressed before its being deployed in such remote areas. Since battery implanted on sensors has got very less power, efficient usage of the power can enhance the life of WSN. One of the solutions is designing proper scheduling of sensors using SET-K covers. Dividing the total sensors into N-groups where each group meets the constraint of full cover can enhance life of WSN by N times. However, dividing the total sensors into maximum number of N groups is called as K-cover problem which considered as NP-complete. In this paper, a methodology is proposed based on genetic algorithm with a new fitness function and a new operator called reconfiguration operator, which utilizes less number of sensors to define the set K-cover for scheduling the sensors.