Cluster head shuffling based global optimization using elephant herd optimization (EHO) approach - Sharad, Er; Shiwani, Savita; Suroliya, Manish (International Journal of Engineering and Technology, 2018)
Wireless Sensors are susceptible from frequent energy decay which leads to the reduction of lifetime of entire network scenario. Such energy loss occurring in the sensor nodes are addressed and worked out by number of researchers using number of methods including Low-energy adaptive clustering hierarchy (LEACH) and its number of variants. Despite of enormous variants of LEACH, there is still huge scope of research because of increasing use of sensor nodes in assorted scenarios. The development of energy aware wireless sensor networks is in research from a long time because of the increasing issues related to lesser lifetime of nodes in the wireless environment. The traditional lifetime of wireless nodes even in smart grids is 835 days while the other wireless nodes die in maximum 30 days. Many times, the battery time of wireless sensor nodes is very few days which is a costly affair. It is difficult and cost consuming to redeploy the wireless nodes to reform the network and cost of clustering. In this research work, a novel and performance aware approach Elephant Herd Optimization based Cluster Head Selection is developed and implemented so that the optimization level can be improved. The nature inspired soft computing approaches are prominently used for global optimization and reduction of error factors from existing results and that is the key focus in this research work.