Large deviations for performance analysis

TL;DR: The workload model that is the basis of traditional analysis of the single queue becomes a foundation for workload relaxations used in the treatment of complex networks and Lyapunov functions and dynamic programming equations lead to the celebrated MaxWeight policy.

TL;DR: In this paper, the authors formulate some simple conditions under which a Markov chain may be approximated by the solution to a differential equation, with quantifiable error probabilities, and the role of a choice of coordinate functions for the Markov Chain is emphasised.

TL;DR: An analysis under the iterative decoding of coset low-density parity-check codes over GF(q), designed for use over arbitrary discrete-memoryless channels, shows that under a Gaussian approximation, the entire q-1-dimensional distribution of the vector messages is described by a single scalar parameter.

TL;DR: In this paper, the authors formulate some simple conditions under which a Markov chain may be approximated by the solution to a differential equation, with quantifiable error probabilities, and the role of a choice of coordinate functions for the Markov Chain is emphasised.