An AI Approach to Locate Cluster Centre in Wireless Sensor Networks
Sandhya R, Nallasamy Sengottaiyan
DOI: http://dx.doi.org/10.15439/2017R58
Citation: Proceedings of the Second International Conference on Research in Intelligent and Computing in Engineering, Vijender Kumar Solanki, Vijay Bhasker Semwal, Rubén González Crespo, Vishwanath Bijalwan (eds). ACSIS, Vol. 10, pages 289–292 (2017)
Abstract. Wireless sensor networks, which consist of a immense number of sensor nodes have emerged as an inevitable, effective and important technology in tele-communication field. Sensor nodes can be deployed in any harsh environment for health monitoring, industrial monitoring, structural analysis, detecting intruders etc. Since it works in battery, the major challenge is to improve the lifetime of sensor node by effectively reducing energy consumption. Otherwise, it is very difficult to frequently replace the sensor nodes. For this, many routing protocols have been proposed in which cluster based routing protocol plays a vital role. In cluster based routing protocol, entire WSN network is divided into several groups or clusters. Then for each cluster a cluster head (CH) is selected. Sensors sense the data and forward it to their corresponding CH where the entire data of that cluster get aggregated and transmitted to base station (BS). The clustering technique offers more benefit than existing flat based routing protocols since the data is transmitted via CH rather than directly by each sensor nodes. Thus the selection of CH is very important. Here we proposed a method named firefly based nearest neighbor chain algorithm to select the centre of cluster based on which CH selection can be done.
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