Image Compression Analysis in Torrent Based Wireless Sensor Network

Author Name(s): Bhushan N Mahajan, Dr Prof. Anjali. R. Mahajan, Prof A. Thomas
Author Email: bnmahajan78@gmail.com

Abstract

Image compression can be achieved efficiently using Wavelet transformation concept in wireless sensor network. Torrent based architecture can be plugged successfully in wireless sensor network. The results are analyzed in this study and outcome of experiment is stated with respect to performance parameters. Wavelet is a template to record changes those occur in real-world data or signals. These changes may occur abruptly, smoothly or frequently. In other words, Wavelet represents a slowly altering contrast or brightness. Images have some smooth and abrupt regions in one specific place and the scanning proceeds in any of the direction, these regions are interrupted by abrupt changes in color or brightness or contrast. It results in gathering the most interesting part of the image data. One can categorize the change in term of contrast or brightness data. One may record this change in terms of the waves, image metadata or coefficients array and thus achieve image compression. Torrent based architecture multiply the processing capabilities of a cluster of sensor nodes. The single node cannot handle heavy processing task, a large number of bytes and communication at a time. Hence processing schedule and communication schedule management algorithms are needed to be designed and allocated separately to a specific set of nodes.

Introduction

In today’s era, the use of digital images is increasing. The next issue is how to store the uncompressed digital images on media and how to transfer them from one machine or node to another node. The compression can save the space on media and bandwidth required for data. For web this issue is more crucial. In case of sensor network, this issue is more crucial. Hence high degree of compression is needed. There are verities of image formats. Ex- JPEG, GIF, tiff and so on. So various types of encoder and decoder are invented. Most common we know is DCT based Encoder and Decoder. Compressions are either lossless or lossy.
Modes may be either Hierarchical, progressive or sequential. Due to low bit rate, performance of Encoder and Decoder decrease. Image may be color or grey. Multiple greyscale images are combined to produce color image. Each input 8×8 pixel block is individually compressed. The output 8×8 blocks are merged to produce one compressed image.

Conclusion

Multimedia content distribution is of great demand nowadays. The content distribution can be achieved by emerging Torrent seed nodes networks. It includes: Cost, peer organization and system potency in content access and distribution of media content. Reliability/robustness, system’s adaptation capability to the dynamic network and different environmental conditions is mandatory. The image frame rate matters in this case. Hence image compression should be done within a stipulated time. The optimized and best method of image compression are jpeg and HAAR wavelet. For transmission of data, nodemcu ESP32 or ESP 8266 can be the used

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