Energy-efficient top-k query evaluation and maintenance in wireless sensor networks

Top-k query in a wireless sensor network is to identify k sensors with the highest sensor readings. Since sensors usually are powered by energy-limited batteries, a fundamental problem associated with top-k query evaluation in such a network is to maximize network lifetime, which poses great challenges due to the unique characteristics of sensor networks. In this paper, we first propose a novel filter-based algorithm for top-k query evaluation, which is able to filter out a fractional amount of data from network-wide transmission. We then develop an online algorithm for answering time-dependent top-k queries with different values of k through the dynamic maintenance of a materialized view that consists of historical top-k results. We finally conduct extensive experiments by simulations to evaluate the performance of the proposed algorithms using real sensing data sets. Experimental results show that the proposed algorithms outperform a well known existing algorithm significantly, and the network lifetime delivered by the proposed optimal quantile algorithm is at least 142 % times longer than that by an existing algorithm.