Semi-structured and unstructured data aggregation scheduling in wireless sensor networks

This paper focuses on data aggregation scheduling problem in wireless sensor networks (WSNs), to minimize time latency. Prior works on this problem have adopted a structured approach, in which a tree-based structure is used as an input for the scheduling algorithm. As the scheduling performance mainly depends on the supplied aggregation tree, such an approach cannot guarantee optimal performance. To address this problem, we propose approaches based on Semi-structured Topology (DAS-ST) and Unstructured Topology (DAS-UT). The approaches are based on two key design features, which are: (1) simultaneous execution of aggregation tree construction and scheduling, and (2) parent selection criteria that maximize the choices of parents for each node and maximize time slot reuse. We prove that the latency of DAS-ST is upper-bounded by ([2π/arccos(1/1+ϵ)]+4)R+Δ-4, where R is the network radius, Δ is the maximum node degree, and 0.05 <; ϵ ≤ 1. Simulations results show that DAS-UT outperforms DAS-ST and four competitive state-of-the-art aggregation scheduling algorithms in terms of latency and network lifetime.