A Dominating Set Based Data Gathering in Wireless Sensor Network using Fuzzy Logic and ACO

Abstract

In the recent furtherance of MEMS technologies such as high speed processor with memory, and other radio technology, it entitled a wireless sensor networks to collect useful information from the remote hazardous area such as dense forest, deep sea floor etc. The collected data is accumulated and then transmitted to Base Station for further processing to take necessary actions. Wireless sensor network subsist of inexpensive with restrained battery power henceforth it is essential to take up a competent data acquisition and aggregation technique to attain enlarge network lifetime. In Hierarchical Routing Protocol (HRP) some node transmits sensed data to the Base Station (BS) which is more energy intensive task while others are engaged in local communications which provides an unbalanced network. So it is important to distribute the load evenly. In this paper we propose a novel energy efficient data gathering method coined as Fuzzy-DS-ACO in which Fuzzy C Means (FCM) is used to divide sensor nodes into clusters. Data redundancy is another problem in HRP as multiple nodes gathered data from the same area. A dominating Set (DS) for each cluster is found and ACO is used to form cluster chain. ACL for each cluster chain is elected depending on surplus energy of nodes and immediacy to the BS by using Fuzzy Logic system. An upper level chain is constructed among CL's using the same ACO and consequently a Super Leader (SL) is selected which sends aggregated data to BS directly. Simulation results show that Fuzzy-DS-ACO surpasses LEACH, LEACH-C, PEGASIS and DFCP in terms of total lifespan of network and load balancing alongside it provides good percentage coverage of the deployment area. It is shown that results are also statistically significant.