Informationally decentralized system resource management for multiple multimedia tasks
IEEE Transactions on Circuits and Systems for Video Technology
Content-aware distortion-fair video streaming in congested networks
IEEE Transactions on Multimedia - Special issue on quality-driven cross-layer design for multimedia communications
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
A suboptimal network utility maximization approach for scalable multimedia applications
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
A systematic framework for dynamically optimizing multi-user wireless video transmission
IEEE Journal on Selected Areas in Communications
Cross-layer content/channel aware multi-user scheduling for downlink wireless video streaming
ISWPC'10 Proceedings of the 5th IEEE international conference on Wireless pervasive computing
Spectrum auction games for multimedia streaming over cognitive radio networks
IEEE Transactions on Communications
Mobile video streaming in modern wireless networks
Proceedings of the international conference on Multimedia
EURASIP Journal on Wireless Communications and Networking - Special issue on adaptive cross-layer strategies for fourth generation wireless communications
QoE-based opportunistic transmission for video broadcasting in heterogeneous circumstance
Proceedings of the 20th ACM international conference on Multimedia
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Multi-user video streaming over wireless channels is a challenging problem, where the demand for better video quality and small transmission delays needs to be reconciled with the limited and often time-varying communication resources. This paper presents a framework for joint network optimization, source adaptation, and deadline-driven scheduling for multi-user video streaming over wireless networks. We develop a joint adaptation, resource allocation and scheduling (JARS) algorithm, which allocates the communication resource based on the video users' quality of service, adapts video sources based on smart summarization, and schedules the transmissions to meet the frame delivery deadlines. The proposed algorithm leads to near full utilization of the network resources and satisfies the delivery deadlines for all video frames. Substantial performance improvements are achieved compared with heuristic schemes that do not take the interactions between multiple users into consideration.