Aggregate query processing in the presence of duplicates in wireless sensor networks

Abstract Wireless sensor networks (WSNs) have received increasing attention in the past decade. In existing studies for query processing of WSNs, each sensor node measures environmental parameters such as temperature, light and humidity around its location. Instead, in our work, we consider a different type of sensors that detect objects in their sensing regions which may overlap with each other. In WSNs with such sensors, an object may be detected by several sensor nodes and processing of aggregate queries (such as COUNT, SUM and AVERAGE) becomes problematic since an identical object can be considered redundantly. In this paper, we propose efficient algorithms for processing aggregate queries as well as sliding window aggregate queries in the presence of multiply detected events. To perform de-duplication, our proposed algorithms identify potential duplicates among detected events by communicating with other nodes and perform aggregations as early as possible. In addition, we extend our algorithms for aggregate queries to support time-based sliding windows. By extensive performance study with diverse environments, we show that the energy consumptions of our proposed algorithms are much smaller than those of baseline algorithms.