Quality adaptation in a multisession multimedia system : model, algorithms and architecture

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dc.contributor.author Khan, Md. Shahadatullah
dc.date.accessioned 2017-09-27T20:32:17Z
dc.date.available 2017-09-27T20:32:17Z
dc.date.copyright 1998 en_US
dc.date.issued 2017-09-27
dc.identifier.uri https://dspace.library.uvic.ca//handle/1828/8593
dc.description.abstract Flexible and adaptive quality of service (QoS) is desirable for real-time multimedia applications. Suppose a multimedia system is supporting a 30 frame/second video stream which is using a network bandwidth of 2 Mbps, and due to network congestion the network bandwidth is reduced to 1 Mbps. It is desirable that the system supports graceful adaptation of quality of the video stream, for example, by reducing the frame rate to 15 frame/second. The focus of this dissertation is to investigate the design of an adaptive multimedia system (AMS) with multiple concurrent sessions, where the quality of individual sessions is dynamically adapted to the available resources and to the run-time user preferences. We propose the Utility Model -- a Mathematical model to capture the issues of resource management within multisession AMSs. In this model, each session provides a quality profile, which is a set of operating qualities arranged from the minimum acceptable quality to the maximum desired quality. Any operating quality may be mapped to the required resources using a quality-resource mapping, and also to a session utility using a quality-utility mapping. The main problem in a multisession AMS is to find an operating quality for each session such that the overall system utility (e.g. system revenue) is maximized under the system resource constraints. This is called the adaptive multimedia problem (AMP). The Utility Model formulates the AMP as the multiple-choice multi-dimension 0–1 knapsack problem (MMKP). It provides a unified and computationally feasible way to solve the admission problem for new multimedia sessions. and the dynamic quality adaptation and integrated resource allocation problems for existing sessions. In order to use the Utility Model, we propose two solutions for the (MMKP): a branch and bound algorithm BBLP for optimal solutions, and a heuristic HEU for fast and near-optimal solutions. We report computational experiences, and compare the two approaches for practical applications, finding that HEU solutions are usually within 4% of the optimum but at a much reduced computational cost. The heuristic HEU is suitable for time-critical applications such as real-time admission and adaptation decisions in multimedia systems. We present the Padma Architecture—a system architecture for multisession AMSs. This architecture has two novelties: (1) integrated and adaptive management of system resources based on the Utility Model, and (2) the use of metaspaces to encapsulate the machinery of quality adaptation. The former provides improved resource utilization and dynamic quality adaptation, and the latter provides the application programmers freedom from the concerns of low-level resource management issues while developing multimedia applications. Finally, we present the Utility Model Demonstration Prototype (UMDP)—a prototype which demonstrates the capability of the Utility Model to handle admission control, quality adaptation and integrated resource allocation in a unified way. We evaluate the performance of UMDP using random sequences of events, and show that the system utility achieved by the UMDP is significantly higher than that of a simple reservation model prototype (SRMP). For applications such multimedia service providers, it means that UMDP will generate more revenue than SRMP from the same amounts of system resources provisioned. en_US
dc.language English eng
dc.language.iso en en_US
dc.rights Available to the World Wide Web en_US
dc.subject Multimedia systems en_US
dc.subject Computer algorithms en_US
dc.title Quality adaptation in a multisession multimedia system : model, algorithms and architecture en_US
dc.type Thesis en_US
dc.contributor.supervisor Li, Kin F.
dc.contributor.supervisor Manning, Eric
dc.degree.department Department of Electrical and Computer Engineering en_US
dc.degree.level Doctor of Philosophy Ph.D. en_US
dc.description.scholarlevel Graduate en_US

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