LiftingWiSe: A Lifting-Based Efficient Data Processing Technique in Wireless Sensor Networks

Abstract

Monitoring thousands of objects which are deployed over large-hard-to-reach areas, is an important application of the wireless sensor networks (WSNs). Such an application requires disseminating a large amount of data within the WSN. This data includes, but is not limited to, the object’s location and the environment conditions at that location. WSNs require efficient data processing and dissemination processes due to the limited storage, processing power, and energy available in the WSN nodes. The aim of this paper is to propose a data processing technique that can work under constrained storage, processing, and energy resource conditions. The proposed technique utilizes the lifting procedure in processing the disseminated data. Lifting is usually used in discrete wavelet transform (DWT) operations. The proposed technique is referred to as LiftingWiSe, which stands for Lifting-based efficient data processing technique for Wireless Sensor Networks. LiftingWiSe has been tested and compared to other relevant techniques from the literature. The test has been conducted via a simulation of the monitored field and the deployed wireless sensor network nodes. The simulation results have been analyzed and discussed.

Keywords

• wireless sensor network (WSN)
• data dissemination
• data compression
• data aggregation
• objects monitoring
• internet of things (IoT)