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Analysis of Maximum Size Matching scheduling algorithm (MSM) in input- queued switches under uniform traffic Neda Beheshti and Mohsen Bayati {nbehesht, bayati} @stanford.edu EE384Y Project May 25, 2004
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Outline Motivation Previous work The Lyapunov function and Foster’s Criteria Final words References EE384Y Project May 25, 2004
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The Lyapunov function Consider the following function EE384Y Project May 25, 2004
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It can be written in matrix form: For example if N = 2, assuming: Then we would have: EE384Y Project May 25, 2004
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Foster’s criteria Consider the following random variables: No let’s denote arrival and departure vectors with A(n) and D(n), hence: Now looking at the last two terms the second one is a bounded function, so in order to check Foster’s criteria we need to show the first one can become very negative as queue sizes get large. Call this term B.
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Arrival traffic is uniform with rate, hence: We also have: So B is now equal to: Now using we only need to show for all i,j:
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Using symmetry we only need to show the inequality for one queue say Now let and then the inequality reduces to: Consider the following three types of maximum size matchings: a) The black edge + k green edges for then b) Two red edges + k greed edges: for then c) One red edge + k green edges: for then For a, b we have: For any type c matching, MSM chooses a type c matching with equal probability. (Because we assume MSM chooses one of maximum matchings at random) And for any type a there can be at most N-k+1 different type c hence:
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Is L(n) non-negative ? Answer: For N = 2,3,4 yes. So it’s a Lyapunov function. When N = 2, positive semidefinite matrix Similarly for N=3, 4 we can write P as sum of a positive semidefinite matrix and a matrix whose entires are nonnegative, and this is enough to show L(n) is not negative.
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Final word We showed MSM is stable under uniform traffic for and input queued switches. For arrival traffic we only need the following assumptions.
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