Novel Fitness Function for SCE Algorithm Based Energy Efficiency in WSN
Amruta Lipare, Damodar Reddy Edla · 2018
In wireless sensor networks, the efficient use of energy is a very crucial job since the sensor nodes are operated with limited source of battery power. Sensor nodes sense and gather data like temperature, humidity etc. from the environment and send this data to the base station. To do all these operations energy of sensor node is consumed. To resolve these issue, gateways with more battery constraints are used; still we need to mitigate the power consumption of gateways to improve the network lifetime. Balancing the load of data helps to balance the energy consumption of gateways as well. Therefore, in this paper we focus on energy efficiency with load balancing. We use Shuffled Complex Evolution (SCE) algorithm with some improvements to address this problem. Two genetic operators namely crossover and mutation have been added in order to produce healthy off-springs with energy efficient load balancing. We also designed a new fitness function for measuring the quality of solution in terms of load balancing obtained by Improved SCE (ISCE) algorithm. The experimental results for ISCE performs better when compared with some existing algorithms in terms of energy consumption, load balancing, heavy loaded sensor nodes, the fitness values of the solutions and network lifetime parameters.