Modeling Machine Availability in Enterprise and Wide-Area Distributed Computing Environments

• Published in: Euro-Par 2005 Parallel Processing pp. 432 - 441
• Main Authors: Nurmi, Daniel, Brevik, John, Wolski, Rich
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Autonomic Computing; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Empirical Distribution Function; Exact sciences and technology; Pareto Distribution; Software; Weibull Distribution; Weibull Model; Availability; High performance; Statistical analysis; Probabilistic approach; Pareto optimum; Distributed system; Distributed computing; Modeling; Statistical data; Business model; Behavioral analysis; Database; Data distribution; Weibull distribution; Firm cooperation; Firm
• ISBN: 3540287000; 9783540287001
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/11549468_50

In this paper, we consider the problem of modeling machine availability in enterprise-area and wide-area distributed computing settings. Using availability data gathered from three different environments, we detail the suitability of four potential statistical distributions for each data set: exponential, Pareto, Weibull, and hyperexponential. In each case, we use software we have developed to determine the necessary parameters automatically from each data collection. To gauge suitability, we present both graphical and statistical evaluations of the accuracy with each distribution fits each data set. For all three data sets, we find that a hyperexponential model fits slightly more accurately than a Weibull, but that both are substantially better choices than either an exponential or Pareto. These results indicate that either a hyperexponential or Weibull model effectively represents machine availability in enterprise and Internet computing environments.