When monitoring the environment with wireless sensor networks, the data sensed by the nodes within event backbone regions can adequately represent the events. As a result, identifying event backbone regions is a key issue for wireless sensor networks. With this aim, we propose a distributed and morphological operation-based data collection algorithm. Inspired by the use of morphological erosion and dilation on binary images, the proposed distributed and morphological operation-based data collection algorithm calculates the structuring neighbors of each node based on the structuring element, and it produces an event-monitoring map of structuring neighbors with less cost and then determines whether to erode or not. The remaining nodes that are not eroded become the event backbone nodes and send their sensing data. Moreover, according to the event backbone regions, the sink can approximately recover the complete event regions by the dilation operation. The algorithm analysis and experimental results show that the proposed algorithm can lead to lower overhead, decrease the amount of transmitted data, prolong the network lifetime, and rapidly recover event regions.

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monitoring the environment binary images dilation algorithm eventmonitoring map of structuring neighbors distributed and morphological operationbased data collection algorithm morphological erosion wireless sensor networks sensing data moreover events identifying event backbone regions

Yalin Nie,Haijun Wang,Yujie Qin,Zeyu Sun,.Distributed and morphological operation-based data collection algorithm. 13 (),.

Yalin Nie,Haijun Wang,Yujie Qin,Zeyu Sun,"Distributed and morphological operation-based data collection algorithm" 13

Yalin Nie,Haijun Wang,Yujie Qin,Zeyu Sun,"Distributed and morphological operation-based data collection algorithm"