The goal of this thesis is to find a strategy for adaptive videostreaming suitable for the Distributed Media Journaling project(DMJ). DMJ focuses on capturing and indexing distributed multimedia content in real time. An important aspect of the project is scalablemulti-receiver video streaming with fine granularity selectivity in multiple video quality dimensions.
The scalability comes from routing video data as notifications in acontent-based network. In content-based networking data is routed based on content rather than addresses. This means that the sender needs no information about individual users.
The selectivity is realized by hierarchical video coding and by mapping video data into notifications. Video quality is specified insubscriptions, which act as filters for notifications. Receivers have different interests and resource capabilities and subscriptions are the mechanism they use to specify the quality they desire. However, resource availability vary overtime and it is inconvenient for a receiver to change the subscriptionin response to these variations manually.
This thesis focuses on the development of automatic adaptation ofvideo quality in DMJ. Users should be able to specify theirpreferences in adaptation polices. When resources are scarce, the appropriate video quality is determined based on the adaptation policy, as well as the availability of resources. The goal is maximization of user utility.
It is necessary that both resource requirements and the resourceavailability are known. While monitoring resource availability isoutside the scope of this thesis, a mathematical function forapproximation of resource requirements has been suggested as analternative to performing exhaustive measurements.