Scalable video transmission over multi-hop wireless networks with enhanced quality of experience using swarm intelligence

Goudarzi, Pejman

doi:10.1016/j.image.2012.05.004

Cited by 10 publications

(11 citation statements)

References 31 publications

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“…The optimal rate of competing scalable video sources for QoE optimization has been found in [10]. Lossinduced distortion caused by video sources has been minimized and QoE has been maximized by obtaining the optimal rate and capturing the exact effect of packet loss in [11].…”

Section: Related Workmentioning

confidence: 99%

A quality of experience-aware cross-layer architecture for optimizing video streaming services

2016

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The popularity of the video services on the Internet has evolved various mechanisms that target the Quality of Experience (QoE) optimization of video traffic. The video quality has been enhanced through adapting the sending bitrates. However, rate adaptation alone is not sufficient for maintaining a good video QoE when congestion occurs. This paper presents a cross-layer architecture for video streaming that is QoE-aware. It combines adaptation capabilities of video applications and QoE-aware admission control to optimize the trade-off relationship between QoE and the number of admitted sessions. Simulation results showed the efficiency of the proposed architecture in terms of QoE and number of sessions compared to two other architectures (adaptive architecture and non-adaptive architecture).

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Section: Related Workmentioning

confidence: 99%

A quality of experience-aware cross-layer architecture for optimizing video streaming services

2016

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“…The PSO method has been applied to resource allocation in wireless networks in a limited capacity [15]- [19]. In [15], a distributed PSO algorithm for video communication in a wireless mesh network is presented.…”

Section: Related Workmentioning

confidence: 99%

“…PSO is used in [19] to maximize the weighted Quality of Experience (QoE) of competing video sources. QoE is defined in terms of allocated bandwidth and packet error probability.…”

Section: Related Workmentioning

confidence: 99%

Channel Time Allocation PSO for Gigabit Multimedia Wireless Networks

Scott-Hayward

Garcia-Palacios

2014

IEEE Trans. Multimedia

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This article introduces a resource allocation solution capable of handling mixed media applications within the constraints of a 60 GHz wireless network. The challenges of multimedia wireless transmission include high bandwidth requirements, delay intolerance and wireless channel availability. A new Channel Time Allocation Particle Swarm Optimization (CTA-PSO) is proposed to solve the network utility maximization (NUM) resource allocation problem. CTA-PSO optimizes the time allocated to each device in the network in order to maximize the Quality of Service (QoS) experienced by each user. CTA-PSO introduces network-linked swarm size, an increased diversity function and a learning method based on the personal best, Pbest, results of the swarm. These additional developments to the PSO produce improved convergence speed with respect to Adaptive PSO while maintaining the QoS improvement of the NUM. Specifically, CTA-PSO supports applications described by both convex and non-convex utility functions. The multimedia resource allocation solution presented in this article provides a practical solution for real-time wireless networks.

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“…Basically, evolutionary computing is a good candidate for finding the optimum solution for complicated optimization problems [10].…”

Section: Introductionmentioning

confidence: 99%

An evolutionary-based fuzzy resource assignment strategy for elastic traffic

Goudarzi

2013

Journal of Intelligent &Amp; Fuzzy Systems

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Many difficult engineering problems have found natural solutions which have been inspired from biological behaviors of the living kinds. Some important examples include neural networks, Genetic Algorithm (GA), DNA computing, artificial immune systems etc. Fair resource allocation strategies which are developed by many researchers are based on solving a form of constrained optimization problem. However, they are not necessarily lead to high-speed and stable solutions. There are plenty of high-speed fair rate allocation methods in the literature, some of them are based on fuzzy controllers for improving the convergence speed and are not necessarily optimal. Hence, in the current research, the GA has been adopted for finding the optimum membership functions which must be used in the fuzzy controller. Stability analysis is presented to guarantee the convergence property of the algorithm. After simulating, the results show that using the hybrid fuzzy-genetic approach improves the conventional methods in convergence speed and results in fewer oscillations in allocated rates.

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Scalable video transmission over multi-hop wireless networks with enhanced quality of experience using swarm intelligence

Cited by 10 publications

References 31 publications

A quality of experience-aware cross-layer architecture for optimizing video streaming services

A quality of experience-aware cross-layer architecture for optimizing video streaming services

Channel Time Allocation PSO for Gigabit Multimedia Wireless Networks

An evolutionary-based fuzzy resource assignment strategy for elastic traffic

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