PROJECT TITLE :

Curve Query Processing in Wireless Sensor Networks

ABSTRACT:

Most existing question processing algorithms for wireless sensor networks (WSNs) can only accommodate discrete values. But, since the monitored setting continuously changes continuously with time, discrete values cannot describe the environment accurately and, hence, could not satisfy a selection of query necessities, such as the queries of the maximal, minimal, and inflection points. It's, so, of great interest to introduce new queries capable of processing time-continuous knowledge. This paper investigates curve question processing for WSNs as curve is a good way to represent continuous sensed knowledge. Specifically, a sensed curve derivation algorithm to support curve question processing in WSNs is first proposed. Then, the aggregation operation is used for example to illustrate curve question processing. The corresponding accurate and approximate aggregation algorithms are devised accordingly. We demonstrate that the energy value of the approximate aggregation algorithm is optimal, on condition 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.