Adaptive and lazy segmentation based proxy caching for streaming media delivery
NOSSDAV '03 Proceedings of the 13th international workshop on Network and operating systems support for digital audio and video
IEEE Transactions on Knowledge and Data Engineering
COPACC: An Architecture of Cooperative Proxy-Client Caching System for On-Demand Media Streaming
IEEE Transactions on Parallel and Distributed Systems
RaDiO edge: rate-distortion optimized proxy-driven streaming from the network edge
IEEE/ACM Transactions on Networking (TON)
A Novel Dynamic and Scalable Caching Algorithm of Proxy Server for Multimedia Objects
Journal of VLSI Signal Processing Systems
Caching collaboration and cache allocation in peer-to-peer video systems
Multimedia Tools and Applications
Achieving simultaneous distribution control and privacy protection for Internet media delivery
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Design and analysis of a variable bit rate caching algorithm for continuous media data
Multimedia Tools and Applications
Proxy caching for video-an-demand using flexible starting point selection
IEEE Transactions on Multimedia
On the power of cooperation in multimedia caching
MMNS'06 Proceedings of the 9th IFIP/IEEE international conference on Management of Multimedia and Mobile Networks and Services
Dynamic and scalable caching algorithm of proxy server for multiple videos
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part II
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Proxy caching has been used to speed up Web browsing and reduce networking costs. In this paper, we study the extension of proxy caching techniques to streaming video applications. A trivial extension consists of storing complete video sequences in the cache. However, this may not be applicable in situations where the video objects are very large and proxy cache space is limited. We show that the approaches proposed in this paper (referred to as selective caching), where only a few frames are cached, can also contribute to significant improvements in the overall performance. In particular, we discuss two network environments for streaming video, namely, quality-of-service (QoS) networks and best-effort networks (Internet). For QoS networks, the video caching goal is to reduce the network bandwidth costs; for best-effort networks, the goal is to increase the robustness of continuous playback against poor network conditions (such as congestion, delay, and loss). Two different selective caching algorithms (SCQ and SCB) are proposed, one for each network scenario, to increase the relevant overall performance metric in each case, while requiring only a fraction of the video stream to be cached. The main contribution of our work is to provide algorithms that are efficient even when the buffer memory available at the client is limited. These algorithms are also scalable so that when changes in the environment occur it is possible, with low complexity, to modify the allocation of cache space to different video sequences.