Minimum-latency aggregation scheduling in wireless sensor network

Abstract

Data aggregation is an essential yet time-consuming task in wireless sensor networks. This paper studies the well-known minimum-latency aggregation schedule problem and proposes an energy-efficient distributed scheduling algorithm named Clu-DDAS based on a novel cluster-based aggregation tree. Our approach differs from all the previous schemes where connected dominating sets or maximal independent sets are employed. This paper proves that Clu-DDAS has a latency bound of $4R'+2 \varDelta -2$, where $\varDelta$ is the maximum degree and $R'$ is the inferior network radius which is smaller than the network radius $R$. Our experiments show that Clu-DDAS has an approximate latency upper bound of $4R'+1.085 \varDelta -2$ with increased $\varDelta$. Clu-DDAS has comparable latency as the previously best centralized algorithm, E-PAS, but consumes 78 % less energy as shown by the simulation results. Clu-DDAS outperforms the previously best distributed algorithm, DAS, whose latency bound is $16R'+\varDelta -14$ on both latency and energy consumption. On average, Clu-DDAS transmits 67 % fewer total messages than DAS. The paper also proposes an adaptive strategy for updating the schedule to accommodate dynamic network topology.