A cost-efficient method for streaming stored content in a guaranteed QoS internet
Computer Networks: The International Journal of Computer and Telecommunications Networking
Performance evaluation of RSVP extensions for a guaranteed delivery scenario
Computer Communications
MAC-layer QoS management for streaming rate-adaptive VBR video over IEEE 802.11e HCCA WLANs
Advances in Multimedia
Perspectives on quality of experience for video streaming over WiMAX
ACM SIGMOBILE Mobile Computing and Communications Review
Pricing-based decentralized rate allocation for multiple video streams
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Competitive equilibrium bitrate allocation for multiple video streams
IEEE Transactions on Image Processing
Delay constrained multiplexing of video streams using dual-frame video coding
IEEE Transactions on Image Processing
Quality-aware bandwidth allocation for scalable on-demand streaming in wireless networks
IEEE Journal on Selected Areas in Communications
Multi-tiered, burstiness-aware bandwidth estimation and scheduling for VBR video flows
Proceedings of the Nineteenth International Workshop on Quality of Service
Consistent-degradation macroblock grouping for parallel video streams over DiffServ networks
Computer Communications
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This paper studies efficient bandwidth resource allocation for streaming multiple MPEG-4 fine granularity scalability (FGS) video programs to multiple users. We begin with a simple single-user scenario and propose a rate-control algorithm that has low delay and achieves an excellent tradeoff between the average visual distortion and the quality fluctuation. The proposed algorithm employs two weight factors for adjusting the tradeoff, and the optimal choice of these factors is derived. We then extend to the multiuser case and propose a dynamic resource allocation algorithm with low delay and low computational complexity. By exploring the variations in the scene complexity of video programs as well as dynamically and jointly distributing the available system resources among users, our proposed algorithm provides low fluctuation of quality for each user, and can support consistent or differentiated quality among all users to meet applications' needs. Experimental results show that compared to traditional look-ahead sliding-window approaches, our algorithm can achieve comparable visual quality and channel utilization at a much lower cost of delay, computation, and storage.