| Summary: | Minimum-Latency Aggregation Scheduling is a significant problem in wireless sensor networks. The key challenge is to find an effective solution to aggregate data from all sensors to the sink with minimum aggregation latency. In this article, we propose a novel data aggregation scheduling algorithm under the physical interference model. First, the algorithm partitions the network into square cells according to the communication range of a sensor. Second, a node is selected randomly as the aggregated node to receive the data from the other nodes in the same cell. Finally, a data aggregation tree, which consists of multiple disjoint paths, is constructed to aggregate data from all aggregated nodes to the sink. We empirically proved that the delay of the aggregation schedule generated by our algorithm is ( K +1) 2 Δ− K −1+2λ time-slots at most, where K is a constant depending on the sensors transmitting power, the signal-to-interference-plus-noise-ratio threshold, and the path-loss exponent; Δ represents the maximal number of nodes in a cell; and λ denotes the number of cells at a row/column in a square network area. Simulation results also show that our algorithm achieves lower average latency than the previous works.
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