Resource prediction for media stream decoding

ABSTRACT

Resource prediction refers to predicting required compute power and energy resources for consuming a service on a device. Resource prediction is extremely useful in a client-server setup where the client requests a media service from the server or content provider. The content provider (in cooperation with the client) can then determine what service quality to deliver given the client's available resources.

This paper proposes a practical approach to predicting resources for decoding media streams. The idea is to group frames with similar decode complexity from various media streams in the content provider's database into so called scenarios. Client profiling using scenario representatives characterizes the client's computational power. This enables the content provider for predicting decode time, decode energy and quality of service for a media stream of interest once deployed on the client.

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