A compositional approach to performance modelling
A compositional approach to performance modelling
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
Task assignment with unknown duration
Journal of the ACM (JACM)
Load profiling: a methodology for scheduling real-time tasks in a distributed system
ICDCS '97 Proceedings of the 17th International Conference on Distributed Computing Systems (ICDCS '97)
Describing Queueing Systems with MPA
Describing Queueing Systems with MPA
Fluid Flow Approximation of PEPA models
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
Comparing job allocation schemes where service demand is unknown
Journal of Computer and System Sciences
A survey of job scheduling in grids
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
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In this paper a novel job allocation scheme in distributed systems (TAG) is modelled using the Markovian process algebra PEPA. This scheme requires no prior knowledge of job size and has been shown to be more efficient than round robin and random allocation when the job size distribution is heavy tailed and the load is not high. In this paper the job size distribution is assumed to be of a phase-type and the queues are bounded. Numerical results are derived and compared with those derived from models employing random allocation and the shortest queue strategy. It is shown that TAG can perform well for a range of performance metrics.