Large Deviations Analysis for Distributed Algorithms in an Ergodic Markovian Environment

Large Deviations Analysis for Distributed Algorithms in an Ergodic Markovian Environment We provide a large deviations analysis of deadlock phenomena occurring in distributed systems sharing common resources. In our model transition probabilities of resource allocation and deallocation are time and space dependent. The process is driven by an ergodic Markov chain and is reflected on the boundary of the d -dimensional cube. In the large resource limit, we prove Freidlin-Wentzell estimates, we study the asymptotic of the deadlock time and we show that the quasi-potential is a viscosity solution of a Hamilton-Jacobi equation with a Neumann boundary condition. We give a complete analysis of the colliding 2-stacks problem and show an example where the system has a stable attractor which is a limit cycle. Applied Mathematics and Optimization Springer Journals

Large Deviations Analysis for Distributed Algorithms in an Ergodic Markovian Environment

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Copyright © 2009 by Springer Science+Business Media, LLC
Mathematics; Numerical and Computational Physics; Mathematical Methods in Physics; Theoretical, Mathematical and Computational Physics; Systems Theory, Control; Calculus of Variations and Optimal Control; Optimization
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