Minimum-latency aggregation scheduling in wireless sensor network

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 $$4R'+2 \varDelta -2$$ 4 R ′ + 2 Δ - 2 , where $$\varDelta $$ Δ is the maximum degree and $$R'$$ R ′ is the inferior network radius which is smaller than the network radius $$R$$ R . Our experiments show that Clu-DDAS has an approximate latency upper bound of $$4R'+1.085 \varDelta -2$$ 4 R ′ + 1.085 Δ - 2 with increased $$\varDelta $$ Δ . 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 $$16R'+\varDelta -14$$ 16 R ′ + Δ - 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.