Abstract
This article presents a performance evaluation method for the dimensioning of load sharing policies in high performance distributed systems such as clusters and grids. Even for moderate system size, the corresponding Markovian models are not tractable neither analytically nor numerically. We propose a modelling framework and a simulation kernel which provides an unbiased sampling of the stationary distribution. As needed by the Propp & Wilson algorithm, we prove that events of load sharing systems preserve partial ordering on the state space (monotone events) that guarantees the simulation efficiency. This has been tested on large scale models (about 1000 nodes) in the Ψ2 simulation framework and applied for the comparison between work sharing and work stealing policies performances and for the optimisation of parameters such as the control rate and the probing depth.
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Gorgo, G., Vincent, JM. (2010). Perfect Sampling of Load Sharing Policies in Large Scale Distributed Systems. In: Al-Begain, K., Fiems, D., Knottenbelt, W.J. (eds) Analytical and Stochastic Modeling Techniques and Applications. ASMTA 2010. Lecture Notes in Computer Science, vol 6148. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13568-2_13
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DOI: https://doi.org/10.1007/978-3-642-13568-2_13
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