Job scheduling methods for reducing waiting time variance

Nong Ye, Xueping Li, Toni Farley, Xiaoyun Xu

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


Minimizing Waiting Time Variance (WTV) is a job scheduling problem where we schedule a batch of n jobs, for servicing on a single resource, in such a way that the variance of their waiting times is minimized. Minimizing WTV is a well known scheduling problem, important in providing Quality of Service (QoS) in many industries. Minimizing the variance of job waiting times on computer networks can lead to stable and predictable network performance. Since the WTV minimization problem is NP-hard, we develop two heuristic job scheduling methods, called Balanced Spiral and Verified Spiral, which incorporate certain proven properties of optimal job sequences for this problem. We test and compare our methods with four other job scheduling methods on both small and large size problem instances. Performance results show that Verified Spiral gives the best performance for the scheduling methods and problems tested in this study. Balanced Spiral produces comparable results, but at less computational cost. During our investigation we discovered a consistent pattern in the plot of WTV over mean of all possible sequences for a set of jobs, which can be used to evaluate the sacrifice of mean waiting time while pursuing WTV minimization.

Original languageEnglish (US)
Pages (from-to)3069-3083
Number of pages15
JournalComputers and Operations Research
Issue number10
StatePublished - Oct 2007


  • Computer networks
  • Job scheduling
  • Quality of Service (QoS)
  • Waiting time variance

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research


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