CCPT: Compression and Correctness-Preserving Top-$k$ Query for Wireless Sensor Networks

Abstract

Data query and energy saving in wireless sensor networks (WSNs) are prominent topics that have been widely studied. Compressive sensing (CS) is a computationally inefficient technique used for conserving communication energy and storage space in WSNs. An intuitive approach to remedy this inefficiency is to preserve data obtained after CS in a compressed domain. However, this would limit the utility of stored data because it would be difficult to query compressed data within WSNs. In this paper, we applied CS to sensing nodes. The proposed method can compress sensing data and stores compressed data only on storage nodes. Hence, the communication and space overhead are both reduced significantly. Moreover, querists are allowed to send a Top- $k$ query to the storage nodes. The nodes can apply adaptive compressed data reduction to retrieve the required data pertaining to the $k$ ranks from the compressed domain and can return query results ( QR s) to the querists. A link-neighborhood technology is provided to querists for ensuring the correctness of QR s, thus avoiding destruction of data due to noise interference or man-in-the-middle attacks. To the best of author’s knowledge, this is the first study that allows storage nodes to process a CS-based Top- $k$ query and allows querists to verify the correctness of the QR s.