Mobile Sink Path Optimization for Data Gathering Using Neural Networks in WSN

Wireless sensor networks are being used for various applications for collection of heterogeneous data. Hotspot problem is major issue of concern that affects the connectivity of entire network along with decreasing lifetime of network. The focus in this paper is lies on optimizing the path followed by the mobile sink for collection of data. The proposed work aims at reducing the hotspot problem and increasing the lifetime. A trained neural network is used to select the best route to be followed by mobile sink. In the proposed work, the stop points are identified which allow the communication between the nodes and the movable sink. The experimental results of the work carried out show that tour length of the sink is greatly reduced and the network lifetime (number of rounds) is increased. Increased lifetime also handles the problem of hotspots.