Improved minimum latency aggregation scheduling in wireless sensor networks under the SINR model
Wireless sensor networks are attracting much attention from the world and Minimum Latency Aggregation Scheduling (MLAS) has become one of the most significant fundamental problems in wireless sensor networks. However, there are few results about efficient data aggregation algorithms under the Signal-to-Interference-plus-Noise-Ratio (SINR) model. In this paper, we propose a centralised algorithm to aggregate data from all sources in O(log(2)n) time slots where n is the total number of nodes. To the best of our knowledge, this is the current best result for the problem. This algorithm uses round scheduling, topology construction and non-linear power assignment as the main techniques. We give a detailed proof of correctness, also an aggregation latency analysis of the algorithm as well as the parameter constraints to achieve our result.
minimum latency wireless sensor network sinr model data aggregation algorithm