Energy Efficiency of Image Transmission in Embedded Linux based Wireless Visual Sensor Network
Abstract
Wireless Visual Sensor Network (WVSN) is a system that consists of visual sensor nodes with an embedded processor. WVSN devices have limited resources of energy, computation capability, memory, and bandwidth. Due to these limitations the implementation of WVSN for large multimedia data, such as images, become a challenging task. Therefore, it is required compressed images prior to transmission. In addition to the limited resources, the system implementation strongly affects the efficiency of the working system. The main contribution of this research is to offer a technical solution of simpler image compression on the WVSN platform. JPEG 2000 is investigated as an alternative compression method to reduce the size of data transfer on WVSN using Embedded Linux as its operating system. Compressed images are transferred to a receiver on communication of IEEE 802.15.4.. This paper shows that the energy consumption for compression and transmission will reduce to only 10.48%, 13.60%, and 17.11% compared to raw image. BER will significantly reduce by implementing image compression. Therefore, it is demonstrated that this model significantly increases energy efficiency, memory utilization efficiency, and data transfer time with acceptable PSNR, compared to uncompressed images.
Keywords
wireless sensor network, Distributed Computation, energy efficiency, Image Compression, Image Transmission
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
N. Sastra, W. Wirawan and G. Hendrantoro, "Energy Efficiency of Image Transmission in Embedded Linux based Wireless Visual Sensor Network," in Journal of Communications Software and Systems, vol. 11, no. 3, pp. 146-154, September 2015, doi: 10.24138/jcomss.v11i3.103
@article{sastra2015energyefficiency,
author = {Nyoman P. Sastra and W Wirawan and Gamantyo Hendrantoro},
title = {Energy Efficiency of Image Transmission in Embedded Linux based Wireless Visual Sensor Network},
journal = {Journal of Communications Software and Systems},
month = {9},
year = {2015},
volume = {11},
number = {3},
pages = {146--154},
doi = {10.24138/jcomss.v11i3.103},
url = {https://doi.org/10.24138/jcomss.v11i3.103}
}