9 research outputs found
Process-algebraic modelling of priority queueing networks
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
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
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
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
LoPC-- modeling contention in parallel algorithms
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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Generalised analytic queueing network models. The need, creation, development and validation of mathematical and computational tools for the construction of analytic queueing network models capturing more critical system behaviour.
Modelling is an important technique in the comprehension and
management of complex systems. Queueing network models capture
most relevant information from computer system and network
behaviour. The construction and resolution of these models is
constrained by many factors. Approximations contain detail lost
for exact solution and/or provide results at lower cost than
simulation.
Information at the resource and interactive command level is
gathered with monitors under ULTRIX'. Validation studies indicate
central processor service times are highly variable on the
system. More pessimistic predictions assuming this variability
are in part verified by observation.
The utility of the Generalised Exponential (GE) as a
distribution parameterised by mean and variance is explored.
Small networks of GE service centres can be solved exactly using
methods proposed for Generalised Stochastic Petri Nets. For two
centre. systems of GE type a new technique simplifying the balance equations is developed. A very efficient "building bglloocbka"l.
is presented for exactly solving two centre systems with service
or transfer blocking, Bernoulli feedback and load dependent rate,
multiple GE servers. In the tandem finite buffer algorithm the
building block illustrates problems encountered modelling high
variability in blocking networks. ':
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A parametric validation study is made of approximations for
single class closed networks of First-Come-First-Served (FCFS)
centres with general service times. The multiserver extension
using the building block is validated. Finally the Maximum
Entropy approximation is extended to FCFS centres with multiple
chains and implemented with computationally efficient
convolution