Media transcoding can be used to enable mobile devices that have low resolution and low bit-rate capabilities to access content created for stationary, desktop clients with high bandwidth connections. By deploying transcoding servers near the edge of a large network, it becomes possible to support clients with multiple resolutions, while limiting the bandwidth requirements in the core network.

In this paper, we argue that manageability of file servers is just as important, if not more, as performance. We focus on the design of a self-managing file server and address the specific problem of automating bandwidth allocation to application classes in single-disk and multi-disk servers. The bandwidth allocation techniques that we propose consists of two key components: a workload monitoring module that efficiently monitors the load in each application class and a bandwidth manager that uses these workload statistics to dynamically determine the allocation of each class. We evaluate the efficacy of our techniques via a simulation study and demonstrate that our techniques (i) exploit the semantics of each application class while determining their allocations, (ii) provide control over the time-scale of monitoring and allocation, and (iii) provide stable behavior even during transient overloads. Our comparison with a static allocation technique shows that dynamic bandwidth allocation can yield queue lengths that are 59% smaller during overloads and admit a larger number of soft real-time clients into the system.

In this paper, we argue that conventional operating systems need to be enhanced with predictable resource management mechanisms to meet the diverse performance requirements of emerging multimedia and web applications. We present QLinux—a multimedia operating system based on the Linux kernel that meets this requirement. QLinux employs hierarchical schedulers for fair, predictable allocation of processor, disk and network bandwidth, and accounting mechanisms for appropriate charging of resource usage. We experimentally evaluate the efficacy of these mechanisms using benchmarks and real-world applications. Our experimental results show that (i) emerging applications can indeed benefit from predictable allocation of resources, and (ii) the overheads imposed by the resource allocation mechanisms in QLinux are small. For instance, we show that the QLinux CPU scheduler can provide predictable performance guarantees to applications such as web servers and MPEG players, albeit at the expense of increasing the scheduling overhead. We conclude from our experiments that the benefits due to the resource management mechanisms in QLinux outweigh their increased overheads, making them a practical choice for conventional operating systems.