9 research outputs found

    Process-algebraic modelling of priority queueing networks

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    We consider a closed multiclass queueing network model in which each class receives a different priority level and jobs with lower priority are served only if there are no higher-priority jobs in the queue. Such systems do not enjoy a product form solution, thus their analysis is typically carried out through approximate mean value analysis (AMVA) techniques. We formalise the problem in PEPA in a way amenable to differential analysis. Experimental results show that our approach is competitive with simulation and AMVA methods

    Approximate reduction of heterogenous nonlinear models with differential hulls

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    We present a model reduction technique for a class of nonlinear ordinary differential equation (ODE) models of heterogeneous systems, where heterogeneity is expressed in terms of classes of state variables having the same dynamics structurally, but which are characterized by distinct parameters. To this end, we first build a system of differential inequalities that provides lower and upper bounds for each original state variable, but such that it is homogeneous in its parameters. Then, we use two methods for exact aggregation of ODEs to exploit this homogeneity, yielding a smaller model of size independent of the number of heterogeneous classes. We apply this technique to two case studies: a multiclass queuing network and a model of epidemics spread

    Process-Algebraic Modelling of Priority Queueing Networks

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    We consider a closed multiclass queueing network model in which each class receives a different priority level and jobs with lower priority are served only if there are no higher-priority jobs in the queue. Such systems do not enjoy a product form solution, thus their analysis is typically carried out through approximate mean value analysis (AMVA) techniques. We formalise the problem in PEPA in a way amenable to differential analysis. Experimental results show that our approach is competitive with simulation and AMVA methods

    Analysis of Scheduling Policies for a M/G/I Queue with Rework

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    This thesis analyzes a multi-class M/G/1 priority queueing system in which distinct job types require one service cycle and, with non-zero probability, require a second service cycle. The main objective is to find a new heuristic scheduling policy that minimizes the long-run expected holding and preemption costs. Arrival rates, service rates, and the probability of undertaking second service are all class specific. A mean value analysis (MVA) approach was employed to derive the long- run mean time in queue for each job type under each policy, thereby providing the appropriate cost equations. Numerical experiments suggest that the preemptive resume scheduling policy yields the lowest cost most frequently

    Approximate Reduction of Heterogenous Nonlinear Models With Differential Hulls

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    LoPC-- modeling contention in parallel algorithms

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    Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (p. 43-44).by Matthew Frank.M.S
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