Object monitoring by prediction and localisation of nodes by using Ant Colony Optimization in Sensor Networks

Wireless sensor network (WSN) consists of tiny sensor nodes with sensing, computation and wireless communication capabilities. Now days, it is finding wide applicability and increasing deployment, as it enables reliable monitoring and analysis of environment. The design of routing protocols for WSN is influenced by many challenging factors like fault tolerance, energy efficiency, scalability, latency, power consumption and network topology. Mobile Sensor Networks (MSN) is networks composed of a large number of wireless devices having sensing, processing, communication, and movement capabilities. In WSN, the coverage of the large area can be improved by the moving the sensor nodes. Coverage in a wireless sensor network can be thought of as how well the wireless sensor network is able to monitor a particular field of interest. In this paper the problem of object monitoring in Mobile Sensor Networks can be identified. The proposed system consists of estimating the position of nodes and then the estimated positions are used to predict the location of nodes. Once the object is determined, the mobile node moves to cover the particular object. If the Target cannot be defined then the set of new nodes are located and each node is assigned a position to minimize the total travelled distance. The estimation and prediction of nodes are done by Interval Theory and the Relocation of Nodes is done by using Ant Colony Optimization. ACO is the Localization of Sensor Nodes which Tracks the Targets. In this proposed paper the simulation results are compared to object monitoring methods considered for networks with static nodes.