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

@incollection{citeulike:4022441, abstract = {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.}, author = {Nurmi, Daniel and Brevik, John and Wolski, Rich}, citeulike-article-id = {4022441}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/11549468_50}, citeulike-linkout-1 = {http://www.springerlink.com/content/031ayfp41u2y5t9x}, doi = {10.1007/11549468_50}, journal = {Euro-Par 2005 Parallel Processing}, keywords = {availability, distributed, enterprise}, pages = {432--441}, posted-at = {2009-11-09 16:27:14}, priority = {2}, title = {Modeling Machine Availability in Enterprise and Wide-Area Distributed Computing Environments}, url = {http://dx.doi.org/10.1007/11549468_50}, year = {2005} }

TY - CHAP ID - citeulike:4022441 L3 - citeulike-article-id:4022441 N2 - 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. JF - Euro-Par 2005 Parallel Processing EP - 441 TI - Modeling Machine Availability in Enterprise and Wide-Area Distributed Computing Environments SP - 432 KW - availability KW - distributed KW - enterprise AU - Nurmi, Daniel AU - Brevik, John AU - Wolski, Rich PY - 2005/// UR - http://dx.doi.org/10.1007/11549468_50 ER -