An enhanced approach for energy optimization using protocol based on multi factors

WSN is having widely used application due to its capability to work. Sensors are mainly used for collecting the information from remote areas. But these type of applications also provide a restriction of non-replaceable battery. So once the WSN has been deployed then there should be efficient use of power so that maximum information could be gathered from the surroundings. Many researchers provided this efficiency in form of algorithms. Clustering is one of the methods used for efficient information collection. Clustering method selects some Cluster Heads (CHs) that is responsible to collect the sensed data and transmit it to the sink. User takes the data from the sink node. Inefficient clustering may lead to early node failure, so CHs should be optimal. Here we have proposed an hybrid approach that take some concept of LEACH-C and enhances the base algorithm by providing multi-attribute based CH selection. We have used delay, standard deviation of power needed by CHs, average distance to CHs, average lifetime of CHs, and maximum power required by node. The coordination among these factors optimized the selection process of CHs that is verified by the simulation results.