Research Repository

Resource Allocation Scheme Based on Online QoE Estimation of Mobile H.264 Video Streaming

M. Alreshoodi, and J. woods, and E. Danish, and A. Fernando, (2015) Resource Allocation Scheme Based on Online QoE Estimation of Mobile H.264 Video Streaming. In: 2015 9th International Conference on Next Generation Mobile Applications, Services and Technologies, 2015-09-09 - 2015-09-11.

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Abstract

Demand on multimedia content by consumers' handheld devices over wireless channels is on the increase. In view of the accelerated trend towards consumption of high quality video, power utilization by mobile devices is expected to excessively increase. This paper presents a power and bandwidth efficient resource allocation scheme considering the end user's Quality of Experience (QoE) in the context of mobile video streaming. QoE has become the prime performance criterion for media delivery technologies. The QoE is estimated by an objective online estimation model based on adaptive Fuzzy Inference Systems (FIS). We simulate a mobile video transmission through which we identify the correlation between receiver's signal-to-noise ratio and QoE. Compared to QoS-based techniques, the proposed QoE-based scheme enables to save up to 33.13% in power and grant up to 50% more data bits for transmission.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Notes: Demand on multimedia content by consumers' handheld devices over wireless channels is on the increase. In view of the accelerated trend towards consumption of high quality video, power utilization by mobile devices is expected to excessively increase. This paper presents a power and bandwidth efficient resource allocation scheme considering the end user's Quality of Experience (QoE) in the context of mobile video streaming. QoE has become the prime performance criterion for media delivery technologies. The QoE is estimated by an objective online estimation model based on adaptive Fuzzy Inference Systems (FIS). We simulate a mobile video transmission through which we identify the correlation between receiver's signal-to-noise ratio and QoE. Compared to QoS-based techniques, the proposed QoE-based scheme enables to save up to 33.13% in power and grant up to 50% more data bits for transmission.
Uncontrolled Keywords: bandwidth allocation; data compression; estimation theory; fuzzy reasoning; mobile handsets; multimedia communication; quality of experience; resource allocation; video codecs; video coding; video streaming; wireless channels; FIS; adaptive fuzzy inference systems; bandwidth efficient resource allocation scheme; handheld devices; media delivery technologies; mobile H.264 video streaming; mobile devices; mobile video transmission; multimedia content; online QoE estimation; power utilization; signal-to-noise ratio; Adaptation models; Estimation; Quality of service; Resource management; Signal to noise ratio; Streaming media; Wireless communication; AMC; MCS; MOS; QoE; QoS; VQM
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 14 Feb 2017 11:39
Last Modified: 15 Jan 2022 00:58
URI: http://repository.essex.ac.uk/id/eprint/17631

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