Data Aggregation in Wireless Sensor Networks Using Firefly Algorithm

The challenging issue of data aggregation in wireless sensor networks (WSNs) is of high significance for reducing network overhead and traffic. The majority of transmitted data by sensor nodes is repetitious and doing processes on them in many cases leads to increased power consumption and reduced network lifetime. Hence, sensor nodes should use such a pattern for data transmission which minimizes duplicate data. However, in cluster based WSN, cluster heads (CHs) consume more energy due to aggregating the data from cluster member nodes and transmitting the aggregated data to the sink. Therefore, the proper selection of CHs plays vital role for prolonging the lifetime of WSNs. In WSNs, cluster head selection is an optimization problem which is NP-hard. In this paper, using firefly algorithm, we proposed a method for aggregating data in WSNs. In the proposed method, sensor nodes are divided into several areas by using clustering. In each cluster, nodes are periodically active and inactive. Criteria such as energy and distance are taken into consideration for selecting active nodes. In this way, nodes with more remaining energy and more distance will be selected as active nodes. Simulation results, conducted in MATLAB 2016a, revealed that the proposed method was able to enhance quality of service parameters more than low energy adaptive clustering hierarchy and shuffled frog algorithm methods.