Abstract
Aim of study is to develop energy efficient mobility prediction based localization algorithm for mobile sensor networks. Mobile sensors are being deployed in the environment like underwater sea monitoring, where they can move to any location to meet coverage requirements. Sensor networks choose to follow data centric approach to track the exact location of the nodes. Location information should be identified for application tasks and network operations. Novel localization algorithms need to be developed for mobile sensor networks with high accuracy and minimal energy consumption. The proposed localization algorithm for mobile sensor networks uses the mobility prediction localization and Mobility Prediction Localization (MPL) algorithm with Maximum Likelihood Estimation (MLE) technique for low and high accuracy respectively. The performance analysis shows that proposed MPL and MPL along with MLE achieve accuracy above 95.5% in the simulated environment. This study also analyses the number of anchor nodes to be deployed to achieve desired level of accuracy. The proposed algorithm uses minimal number of nodes for tracking while rest are in sleep mode for energy saving, thereby increasing lifetime of the nodes.
Highlights
Wireless sensor nodes are tiny, low-power networked sensing devices with limited sensing, processing and communicating capabilities
It clearly shows that mobility prediction with Maximum Likelihood Estimation (MLE) has high accuracy compare to Mobility Prediction Localization (MPL) thereby supports for high accuracy demanding applications
The proposed algorithm eliminates the flaws in the existing work including constant number of samples for localization, periodic location updates to the neighbouring nodes, increased network traffic for frequent location updates, choosing nodes for target localization
Summary
Wireless sensor nodes are tiny, low-power networked sensing devices with limited sensing, processing and communicating capabilities These nodes are deployed in remote areas both densely and randomly for sensing and monitoring environmental changes. A new emerging trend for wireless sensor networks called mobile sensor networks is being used in the environments like underwater sea monitoring, detecting seismic activities, navigating ships and in tracking of objects where sensors can move around in the monitoring area in any direction at any speed. These applications are strictly based on the location, because without location information processing of data will be meaningless. Nodes without location aware device uses range based or range free localization for self-localization
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