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Localized Energy Efficient Detection and Tracking of Dynamic Phenomena

Dynamic phenomena such as oil spills, mud flow, diffusion or leakage of gases in the environment are characterized by non-deterministic variations in shape, size and direction of motion. Due to the absence of any well defined model for tracking their dynamics, the detection and tracking of such phenomena through Wireless Sensor Networks (WSNs) is very challenging. Most of the existing works consider static phenomena with certain shapes, only few of them study dynamic phenomena. However, existing works studying dynamic phenomena mainly concentrate on reducing the communication overheads and neglect the energy consumed in sensing, which result in higher energy consumption and shorter network lifetime. In this paper, we propose a novel protocol for detection and tracking dynamic phenomena through WSNs, with an objective to minimize the resource usage and energy consumption. We also propose a robust localized clustering method, which helps in reducing the network traffic generated by the information packets destined to a Centralized Query Processor (CQP). The experimental results show that, in comparison to the existing work, our protocol consumes 90% less energy and generates 65% less network traffic.