Abstract Over the last decade research has been pursued on all aspects of streaming media. While many theoretical results have been reported in the literature, few performance results of large‐scale systems have been published. In this report we specifically explore the scalability aspects of our Yima streaming media architecture in an end‐to‐end test environment. With Yima, it was our goal to design and implement an architecture that would scale in performance from small to large systems. Some of the design features include (1) a multi‐node cluster architecture based on commodity hardware and custom software, (2) media type independence (support ranges from 500 Kb s$^{-1}$ MPEG‐4 to 45 Mb s$^{-1}$ HDTV, at both variable and constant bitrates), (3) fine‐grained online scale up/down capabilities, and (4) a client‐controlled rate smoothing protocol. We briefly discuss the design and implementation of these capabilities of Yima and then thoroughly evaluate its scalability through several sets of experiments. Our results show that Yima scales linearly (within the range of our test parameters) as a function of the cluster size and also as a function of available resources such as network bandwidth and CPU performance. Copyright © 2004 John Wiley & Sons, Ltd.

Scalable storage architectures allow for the addition of disks to increase storage capacity and/or bandwidth. In its general form, disk scaling also refers to disk removals when either capacity needs to be conserved or old disk drives are retired. Assuming random placement of blocks on multiple nodes of a continuous media server, our optimization objective is to redistribute a minimum number of media blocks after disk scaling. This objective should be met under two restrictions. First, uniform distribution and hence a balanced load should be ensured after redistribution. Second, the redistributed blocks should be retrieved at the normal mode of operation in one disk access and through low complexity computation. We propose a technique that meets the objective, while we prove that it also satisfies both restrictions. The SCADDAR approach is based on using a series of REMAP functions which can derive the location of a new block using only its original location as a basis.

Yima is a scalable, real-time streaming architecture that enables applications such as video-on-demand and distance learning on a large scale. While Yima incorporates lessons learned from first generation research prototypes, it also complies with industry standards in content format (MPEG-4) and communication protocols (RTP/RTSP). Yima improves upon both research and commercial approaches by using a bipartite design and alternative approaches to handling variable-bit-rate (VBR) video. We also integrated a selective retransmission protocol into Yima's RTP server to recover from packet loss. Lastly, we tweaked available hardware and software to achieve certain objectives (e.g., playback of HDTV streams on an HDTV monitor). Yima is operational and supports a variety of display bandwidths.