DEDV: A Data Collection Method for Mobile Sink Based on Dynamic Estimation of Data Value in WSN

Applying mobile sink to collect data in wireless sensor networks can avoid the energy hole problem and lengthen the networks' life time. Current related researches have achieved significant improvements on reducing the data collection latency in the scenario where the mobile sink has enough or limited energy. However, it will lead to waste of network resource if not taking the spatial and temporal correlation of data into consideration during the collection because of the high similarity and low quality in the collected data. In this paper, we first propose a method named Dynamic Estimation of Data Value (DEDV) to estimate the value of data stored in the nodes dynamically. Furthermore, we define a heuristic method that drives the mobile sink to collect data from the nodes to maximize the value of the collected data in a power-limited mobile sink scenario. Both simulation and experiments results show that our method can achieve at most over 85% of the theoretical maximum data value determined by the OPT model.