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.

Keywords:

Localization, maximum likelihood estimation , mobility aware , mobility prediction,

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Competing interests

The authors have no competing interests.

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The authors have no competing interests.