An energy saving audio compression scheme for wireless multimedia sensor networks using spatio-temporal partial discrete wavelet transform. (November 2015)

• Record Type: Journal Article
• Authors: Banerjee, Rajib; Chatterjee, Sibashis; Das Bit, Sipra
• Is Part Of: Computers & electrical engineering. Volume 48(2015)
• Page Start: 389
• Page End: 404
• Publication Date: 2015-11
• Subjects: Wireless multimedia sensor network -- Compression -- Partial discrete wavelet transform (PDWT) -- Spatio-temporal Partial discrete wavelet transform (STPDWT) -- Spatio-temporal Partial discrete wavelet transform with Encoding (STPDWTE) -- Tree based routing; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2015.09.009
• Languages: English
• ISSNs: 0045-7906

Abstract

Graphical abstract: Highlights: Energy saving data compression for WMSNs with randomly deployed nodes. Energy is primarily saved by exploiting spatial and temporal correlation together. It is further saved by proposing a tree based routing which ensures unidirectional data flow toward the sink. A lossless encoding scheme is proposed to save energy further. Abstract: Due to strict inherent limitations in terms of processing power, storage and bandwidth, data processing is a challenge in the wireless multimedia sensor networks. In this paper, we provide an energy-saving audio data compression technique for such a network using lifting based partial discrete wavelet transform (PDWT). Unlike existing implementation of such a lifting based PDWT, we exploit both spatial and temporal correlation of data together, with an objective to save energy while achieving acceptable signal-to-noise ratio (SNR). We subsequently design a tree based routing scheme and an encoding scheme to be used with the proposed compression scheme with a target to reduce energy further. Finally, the design feasibility along with simulation results, including statistical analysis is presented to evaluate efficacy of the scheme in terms of two conflicting parameters viz. energy consumption and SNR. The comparative results confirm our scheme's supremacy over a few competing schemes.