Authors: Xueping Li, Nong Ye, Xiaoyun Xu, Rapinder Sawhey
Addresses: Department of Industrial and Information Engineering, University of Tennessee, 408 East Stadium Hall, Knoxville, TN 37996-0700, USA. ' Department of Industrial Engineering, Arizona State University, Tempe, AZ 85287-5906, USA. ' Department of Industrial Engineering, Arizona State University, Tempe, AZ 85287-5906, USA. ' Department of Industrial and Information Engineering, University of Tennessee, Knoxville, TN 37996-0700, USA
Abstract: When a batch of jobs are waiting for services from a machine or resource, sometimes it is desirable to minimise the variance of job waiting times Waiting Time Variance (WTV) for service stability to all the jobs in the batch so that the jobs have about the same waiting times. Many factors, including the sum of the jobs| processing times, the probability distribution of job processing times and the scheduling method may influence the variance of job waiting times. In this paper, we use multivariate exploratory techniques such as Principal Components Analysis (PCA) and Correspondence Analysis (CA) along with other statistical analysis techniques to investigate these factors. We prove that the expected WTV can be predicted given characteristics of the jobs. These findings can be applied to achieve a desire level of WTV for service stability.
Keywords: job scheduling; waiting time variance; WTV; quality of service; QoS; statistical analysis; principal components analysis; PCA; correspondence analysis; industrial engineering; job processing times.
European Journal of Industrial Engineering, 2007 Vol.1 No.1, pp.56 - 73
Published online: 05 Mar 2007 *Full-text access for editors Access for subscribers Purchase this article Comment on this article