Sensor node selection for execution of continuous probabilistic queries in wireless sensor networks

Abstract

Due to the error-prone properties of sensors, it is important to use multiple low-cost sensors to improve the reliability of query results. However, using multiple sensors to generate the value for a data item can be expensive, especially in wireless environments where continuous queries are executed. Further, we need to distinguish effectively which sensors are not working properly and discard them from being used. In this paper, we propose a probabilistic approach to decide what sensor nodes to be used to answer a query. In particular, we propose to solve the problem with the aid of continuous probabilistic query (CPQ), which is originally used to manage uncertain data and is associated with a probabilistic guarantee on the query result. Based on the historical data values from the sensor nodes, the query type, and the probabilistic requirement on the query result, we derive a simple method to select an appropriate set of sensors to provide reliable answers. We examine a wide range of common aggregate queries: average, sum, minimum, maximum, and range count query, but we believe our method can be extended to other query types. Our goal is to minimize sensor data aggregation workload in a network environment and at the same time meet the probabilistic requirement of the CPQ.