Dynamic resource allocation for shared data centers using online measurements

Since web workloads are known to vary dynamically with time, in this paper, we argue that dynamic resource allocation techniques are necessary to provide guarantees to web applications running on shared data centers. To address this issue, we use a system architecture that combines online measurements with prediction and resource allocation techniques. To capture the transient behavior of the application workloads, we model a server resource using a time-domain description of a generalized processor sharing (GPS) server. This model relates application resource requirements to their dynamically changing workload characteristics. The parameters of this model are continuously updated using an online monitoring and prediction framework. This framework uses time series analysis techniques to predict expected workload parameters from measured system metrics. We then employ a constrained non-linear optimization technique to dynamically allocate the server resources based on the estimated appl...

• Type: Conference
• Year: 2003
• Where: SIGMETRICS
• Authors: Abhishek Chandra, Weibo Gong, Prashant J. Shenoy
• Keywords: Resource Allocation Techniques, SIGMETRICS 2003, Transient Behavior, Web Workloads