Managing Uncertainty: A Case for Probabilistic Grid Scheduling

Details Managing Uncertainty: A Case for Probabilistic Grid Scheduling Managing Uncertainty: A Case for Probabilistic Grid Scheduling

2007-11-02

arxiv.org/abs/0711.0327v1

Computer Science

Distributed, Parallel, and Cluster Computing

Scientific paper

The Grid technology is evolving into a global, service-orientated architecture, a universal platform for delivering future high demand computational services. Strong adoption of the Grid and the utility computing concept is leading to an increasing number of Grid installations running a wide range of applications of different size and complexity. In this paper we address the problem of elivering deadline/economy based scheduling in a heterogeneous application environment using statistical properties of job historical executions and its associated meta-data. This approach is motivated by a study of six-month computational load generated by Grid applications in a multi-purpose Grid cluster serving a community of twenty e-Science projects. The observed job statistics, resource utilisation and user behaviour is discussed in the context of management approaches and models most suitable for supporting a probabilistic and autonomous scheduling architecture.

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