A Fluid Flow Approach to Usability Analysis of Multi-user Systems
HCSE-TAMODIA '08 Proceedings of the 2nd Conference on Human-Centered Software Engineering and 7th International Workshop on Task Models and Diagrams
A New Mechanism for Job Scheduling in Computational Grid Network Environments
AMT '09 Proceedings of the 5th International Conference on Active Media Technology
Replicating web services for scalability
TGC'07 Proceedings of the 3rd conference on Trustworthy global computing
Continuous approximation of collective system behaviour: A tutorial
Performance Evaluation
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In grid applications the heterogeneity and potential failures of the computing infrastructure poses significant challenges to efficient scheduling. Performance models have been shown to be useful in providing predictions on which schedules can be based (N. Furmento et al., 2002) and most such techniques can also take account of failures and degraded service. However, when several alternative schedules are to be compared it is vital that the analysis of the models does not become so costly as to outweigh the potential gain of choosing the best schedule. Moreover, it is vital that the modelling approach can scale to match the size and complexity of realistic applications. In this paper, we present a novel method of modelling job execution on grid compute clusters. As previously we use performance evaluation process algebra (PEPA) (J. Hillston, 1996) as the system description formalism, capturing both workload and computing fabric. The novel feature is that we make a continuous approximation of the state space underlying the PEPA model and represent it as a set of ordinary differential equations (ODEs) for solution, rather than a continuous time, but discrete state space, Markov chain.