Curve Query Processing in Wireless Sensor Networks

Most existing query processing algorithms for wireless sensor networks (WSNs) can only deal with discrete values. However, since the monitored environment always changes continuously with time, discrete values cannot describe the environment accurately and, hence, may not satisfy a variety of query requirements, such as the queries of the maximal, minimal, and inflection points. It is, therefore, of great interest to introduce new queries capable of processing time-continuous data. This paper investigates curve query processing for WSNs as curve is an effective way to represent continuous sensed data. Specifically, a sensed curve derivation algorithm to support curve query processing in WSNs is first proposed. Then, the aggregation operation is employed as an example to illustrate curve query processing. The corresponding accurate and approximate aggregation algorithms are devised accordingly. We demonstrate that the energy cost of the approximate aggregation algorithm is optimal, provided that the required precision is satisfied. The theoretical analysis and experimental results indicate that the proposed algorithms can achieve high performance in terms of accuracy and energy efficiency.