Admission control for media on demand services

Abstract

Admission control software is used to make accept or deny decisions about incoming service requests to avoid overload. Existing media streaming software includes only limited support for admission control by allowing for predefined static rules. Such rules limit for example the number of requests that are allowed to enter the system during a certain time or define thresholds concerning the utilization level of a single resource such as network bandwidth. In media streaming applications, however, the bottleneck resource (CPU, Disk I/O, network bandwidth, etc.) might change over time depending on the current demand for different types of audio or video files. This paper proposes a model for adaptive admission control in the presence of multiple scarce resources. Opportunity costs for a service request are determined at the moment of an incoming request and compared to the revenue of a request in order to make an accept/deny decision. Opportunity costs are based on resource utilization, service resource requirements, expected future demand for services, and the revenue per accepted service. The model allows rejection of service requests early to reserve capacity required to perform future service requests with higher revenues. We describe a number of experiments to illustrate the benefits of adaptive admission control models over static admission control rules.