Spatial and Temporal Multi-Aggregation for State-Based Sensor Data in Wireless Sensor Networks

Sensor nodes are thrown to remote environments for deployment and constitute a multi-hop sensor network over a wide range of area. Users hardly have global information on the distribution of sensor nodes. Hence, when users request state-based sensor readings such as temperature and humidity in an arbitrary area, networks may suffer unpredictable heavy traffic. This problem needs data aggregation to comply with user requirements and manage overlapped aggregation trees of multiple users efficiently. In this paper, spatial and temporal multiple aggregation (STMA) is proposed to minimize energy consumption and traffic load when a single or multiple users gather state-based sensor data from varions subareas through multi-hop paths. Spatial aggregation builds the aggregation tree with an optimal intermediary between a target area and a sink. The broadcast nature of wireless communication is exploited to build the aggregation tree in the confined area. Temporal aggregation uses the interval so that users obtain an appropriate amount of data they need without suffering excess traffic. The performance of STMA is evaluated in terras of energy consumption and area-to-sink delay in the simulation based on real parameters of Berkeley's MICA motes.