Prediction-Based Event Determination in Underwater Wireless Sensor Networks

Underwater environments may vary gradually even when the occurrence of events is detected. Sensory data may follow a certain trend and are predictable during certain time durations. Taken these into concerns, a prediction mechanism can be adopted for estimate, and data are synchronized by underwater sensor nodes only when variation is beyond pre-specified thresholds. Leveraging predicted data, the coverage and sources of potential events are identified by the sink node, and the evolution of these events is determined accordingly. Evaluation results show the applicability and energy-efficiency of this approach, especially when the variation of network environments follows certain and simple patterns.