Transmission and Access Scheduling for Streaming Media


The increasing demand for streaming media delivery over data networks motivates the problem of building scalable data storage and transfer systems with quality of service guarantees. This project deals with resource allocation for dynamically scheduling data transfers from storage servers to multiple distributed clients across a network. A hierarchical decomposition technique is followed to achieve scalability. Using proxy caching for data reduction and prefetching for aggregate bandwidth smoothing, the scheduling algorithms aim to maximize the number of simultaneous clients in a dynamic environment.


Participants