Name
Abstract | ||
|---|---|---|
Presents a performance analysis of a heterogeneous multiprocessor system where tasks may arrive from Poisson sources as well as by spawning and probabilistic branching of other tasks. Non-preemptive priority scheduling is used between different tasks. Stochastic reward nets are used as the system model, and are solved analytically by generating the underlying continuous-time Markov chain. An approximation technique is used, that is based on fixed-point iteration to avoid the problem of a large underlying Markov chain. The iteration scheme works reasonably well, and the existence of a fixed point for the iterative scheme is guaranteed under certain conditions |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1109/ICDCS.1993.287678 | Pittsburgh, PA |
Keywords | Field | DocType |
Markov processes,iterative methods,multiprocessing systems,performance evaluation,queueing theory,resource allocation,scheduling,Poisson sources,approximate analysis,continuous-time Markov chain,fixed-point iteration,heterogeneous multiprocessor system,nonpreemptive priority scheduling systems,performance analysis,probabilistic branching,spawning,stochastic reward nets,task arrival | Mathematical optimization,Markov process,Continuous-time Markov chain,Scheduling (computing),Iterative method,Computer science,Fixed-point iteration,Markov chain,Probabilistic logic,Fixed point,Distributed computing | Conference |
ISBN | Citations | PageRank |
0-8186-3770-6 | 7 | 0.70 |
References | Authors | |
4 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Varsha Mainkar | 1 | 68 | 8.24 |
| Trivedi, K.S. | 2 | 7721 | 700.23 |