Name
Title | ||
|---|---|---|
Automatic methods for predicting machine availability in desktop Grid and peer-to-peer systems |
Abstract | ||
|---|---|---|
In this paper we examine the problem of predicting machine availability in desktop and enterprise computing environments. Predicting the duration that a machine will run until it restarts (availability duration) is critically useful to application scheduling and resource characterization in federated systems. We describe one parametric model fitting technique and two nonparametric prediction techniques, comparing their accuracy in predicting the quantiles of empirically observed machine availability distributions. We describe each method analytically and evaluate its precision using a synthetic trace of machine availability constructed from a known distribution. To detail their practical efficacy, we apply them to machine availability traces from three separate desktop and enterprise computing environments, and evaluate each method in terms of the accuracy with which it predicts availability in a trace driven simulation. Our results indicate that availability duration can be predicted with quantifiable confidence bounds and that these bounds can he used as conservative bounds on lifetime predictions. Moreover a nonparametric method based on a binomial approach generates the most accurate estimates. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/CCGrid.2004.1336566 | CCGrid |
Keywords | Field | DocType |
enterprise computing environment,empirically observed machine availability,machine availability,peer-to-peer system,method analytically,resource availability,nonparametric prediction technique,automatic method,machine availability trace,synthetic trace,nonparametric method,availability duration,separate desktop,statisti- cal analysis,distributed systems modeling,desktop grid,distributed system,computer science,grid computing,parametric model,scheduling,time measurement,binomial distribution,mathematics,weibull distribution,microcomputers,predictive models,resource allocation,distributions,availability,federated systems,nonparametric statistics | Binomial distribution,Parametric model,Grid computing,Peer-to-peer,Scheduling (computing),Computer science,Real-time computing,Nonparametric statistics,Resource allocation,Grid,Distributed computing | Conference |
ISBN | Citations | PageRank |
0-7803-8430-X | 43 | 1.64 |
References | Authors | |
14 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brevik, J. | 1 | 43 | 1.64 |
| Nurmi, D. | 2 | 54 | 2.56 |
| Wolski, R. | 3 | 43 | 1.64 |