Abstract—The focus of our work is on developing techniques for selecting nodes for scheduling applications in large-scale, cooperatively pooled, shared computing platforms. In such platforms, resources at a node are allocated to competing users on fair-share basis, without any reserved resource capacities for any user. There is no platform-wide resource manager for the placement of users on different nodes. The users independently select nodes for their applications. Our study is focused on the PlanetLab environment which exemplifies such platforms. For developing node selection techniques, we first study the resource utilization characteristics of PlanetLab nodes. Our approach uses the notion of eligibility period, which represents a contiguous duration for which a node satisfies a given resource requirement. We study the characteristics of the eligibility periods of Planetlab nodes for various resource capacity requirements. Based on this study we develop models for identifying nodes that are likely to satisfy a given requirement for long durations. We also develop an online model for predicting the idle resource capacity that is likely to be available on a node over a short term. We evaluate and demonstrate the performance benefits of the node selection techniques and the prediction model using the PlanetLab node utilization data traces collected at different intervals over an extended period of several months. I
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