Perceptual quality‐based image communication service framework for wireless sensor networks. Issue 1 (11th November 2011)

• Record Type: Journal Article
• Authors: Boluk, Pinar Sarisaray; Baydere, Sebnem; Harmanci, A. Emre
• Is Part Of: Wireless communications and mobile computing. Volume 14:Issue 1(2014)
• Page Start: 1
• Page End: 18
• Publication Date: 2011-11-11
• Subjects: Wireless communication systems -- Periodicals; Mobile communication systems -- Periodicals; 621.38205
• DOI: 10.1002/wcm.1218
• Languages: English
• ISSNs: 1530-8669

Abstract

<abstract abstract-type="main" id="wcm1218-abs-0001"> <title>ABSTRACT</title> <p id="wcm1218-para-0004">Wireless multimedia sensor networks (WMSNs) have an increasing variety of multimedia‐based applications including image and video transmission. In these types of applications, multimedia sensor nodes should ideally maximize perceptual quality and minimize energy expenditures in communication. For the required perceptual quality to be obtained, quality‐aware routing is a key research area in WMSNs. However, mapping the system parameters to the end user's perceptual quality‐of‐service measures is a challenging task because of incomplete identification metrics. Unfortunately, unless disputable assumptions and simplifications are made, optimal routing algorithm is not tractable. In this paper, we propose a novel image transmission framework to optimize both perceptual quality and energy expenditure in WMSNs. Our framework aims to provide acceptable perceptual quality at the end user by using an analytical distortion prediction model that is able to predict the image distortion resulting from any given error pattern. The innovation of the proposed scheme lies in the combined use of a content‐aware packet prioritization with an energy‐aware and quality‐aware routing protocol, named as image quality‐aware routing. Additionally, it does not only propose an energy‐efficient route selection policy but also manages the network load according to the energy residues of nodes, thus leading to a great energy economy. The results reveal that the framework is capable of identifying true metrics for mapping required image quality to network parameters. Copyright © 2011 John Wiley & Sons, Ltd.</p> </abstract>