BINOCULAR

Abstract

Recent advances in hardware technology facilitate applications requiring a large number of sensor devices, where each sensor device has computational, storage, and communication capabilities. However these sensors are subject to certain constraints such as limited power, high communication cost, low computation capability, presence of noise in readings and low bandwidth. Since sensor devices are powered by ordinary batteries, power is a limiting resource in sensor networks and power consumption is dominated by communication. In order to reduce power consumption, we propose to use a linear model of temporal, spatial and spatio-temporal correlations among sensor readings. With this model, readings of all sensors can be estimated using the readings of a few sensors by using linear observers and multiple queries can be answered more efficiently. Since a small set of sensors are accessed for query processing, communication is significantly reduced. Furthermore, the proposed technique can also be beneficial at filtering out the noise which directly affects the accuracy of query results.