Managing Uncertainty: A Case for Probabilistic Grid Scheduling

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 delivering deadline/economy based scheduling in a heterogeneous application environment using statistical properties of job’s 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.

• Type: Journal
• Year: 2007
• Where: CORR
• Authors: Aleksandar Lazarevic, Lionel Sacks, Ognjen Prnjat
• Keywords: CORR 2007, Education, Grid, Grid Technology, Multi-purpose Grid Cluster