Title: A low-complexity DWT module and CRS minimal instruction set computer architecture for wireless visual sensor networks

Authors: Jia Jan Ong; Gerald Ijemaru; Li-Minn Ang; Kah Phooi Seng; Jia Hao Kong; Yee Wan Wong

Addresses: Intel Corporation, Malaysia ' Department of Electrical and Electronics Engineering, Federal University OYE-EKITI, Nigeria ' School of Computing and Mathematics, Charles Sturt University, North Wagga, NSW 2678, Australia ' School of Computing and Mathematics, Charles Sturt University, North Wagga, NSW 2678, Australia ' Faculty of Engineering, Nottingham University, 43200 Semenyih, Malaysia ' Faculty of Engineering, Nottingham University, 43200 Semenyih, Malaysia

Abstract: Transmitting cost, processing complexity and data security are three important elements in wireless visual sensor networks (WVSNs). This paper presents a complete low-complexity processing system that performs data compression, data correction and data encryption. In this system, the discrete wavelet transform (DWT) first decomposes the original image into DWT coefficients to ensure low transmitting cost, then the coefficients are encrypted using the Cauchy Reed Solomon CRS(20,16) coding scheme to ensure data security. A CRS minimal instruction set computer architecture with a DWT filtering module is proposed to perform the compression, encryption and error correction encoding in a low-complexity processing system. The proposed system is then implemented in a field programmable gated array (FPGA) to demonstrate the feasibility of the proposed system for implementation in WVSNs. Results on a Xilinx Spartan FPGA show that the proposed system requires a lower implementation complexity of 2536 slices as compared to other existing systems such as Crypto-Processor (4828 slices) and SPIHT CRS MISC (5017 slices).

Keywords: WVSNs; wireless visual sensor networks; DWT; discrete wavelet transform; Cauchy Reed Solomon; minimal instruction set computer.

DOI: 10.1504/IJAHUC.2019.097628

International Journal of Ad Hoc and Ubiquitous Computing, 2019 Vol.30 No.2, pp.73 - 90

Accepted: 10 Jan 2017
Published online: 04 Feb 2019 *

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