Low-Power Distinct Sum for Wireless Sensor Networks

Continuous monitoring is a major component of many applications in wireless sensor network (WSN). In these applications, to reduce the communication overhead, some form of data summary or aggregation can be performed. However, performing non-trivial in-network data processing such as finding frequent items, Top-K monitoring, and clustering efficiently are challenging in practice.In this paper, we present Low-Power Distinct Sum (LDS), a distributed in-network data aggregation primitive that performs the sum of unique items in WSN. LDS serves as the underlying primitive that can be used to implement many distributed data processing efficiently. To demonstrate LDS’s capabilities, we design and implement a distributed data streaming application with LDS running on Contiki OS. Compared to the baseline algorithm, LDS can reduce the completion time by up to 66%.