Greedy Distributed Minimum-Latency Aggregation Scheduling in Wireless Sensor Networks
Data aggregation is a key technique in Wireless Sensor Networks (WSNs). In this paper, the authors studied the Minimum Latency Aggregation Scheduling (MLAS) problem in which collision-free TDMA based scheduling is produced to minimize aggregation latency. They propose a novel distributed algorithm named GDAS to solve the problem approximately. Unlike previous distributed algorithms which adopt a two-phase method where an aggregation tree is constructed in the first phase, GDAS allows each sensor node to choose its receiver and sending time slot simultaneously in a greedy way. It is further proved that GDAS is effective above existing MAC protocol such as CSMA.