A swarm intelligence technique to enhance network lifetime in WSN

A Wireless Sensor Network (WSN) is a field of interest for researchers due to its monitoring capability and giving the information which helps in predicting the future scenarios like in health care system, monitoring or tracking etc. Sensor nodes are very small and powerful devices which are continuously sense the data and send it to the base station (Sink) which generates the results based on the details received from sensor nodes. Sensor nodes are battery constrained, they use a lot of energy for transmitting the data and die very quickly. To save the energy of sensor node and make WSN more reliable here authors proposed a clustering mechanism. In clustering mechanism large network divided into small clusters. Each cluster has its own cluster head, cluster members communicate with cluster head and cluster head collects all the data from cluster members and send it to the base station. For cluster formation a noble concept is given called adaptive swarm optimization, here authors worked on best previous position and best global position of nodes. Nodes can changes their position as per their best global position from the previous position and based on this lifetime of overall network can be increased. Nodes death rate is decreased as compared with the existing method.