Large-scale parallel server system with multi-component jobs

Research output: Contribution to journalArticlepeer-review

Abstract

A broad class of parallel server systems is considered, for which we prove the steady-state asymptotic independence of server workloads, as the number of servers goes to infinity, while the system load remains sub-critical. Arriving jobs consist of multiple components. There are multiple job classes, and each class may be of one of two types, which determines the rule according to which the job components add workloads to the servers. The model is broad enough to include as special cases some popular queueing models with redundancy, such as cancel-on-start and cancel-on-completion redundancy. Our analysis uses mean-field process representation and the corresponding mean-field limits. In essence, our approach relies almost exclusively on three fundamental properties of the model: (a) monotonicity, (b) work conservation and (c) the property that, on average, “new arriving workload prefers to go to servers with lower workloads.”

Original languageEnglish (US)
Pages (from-to)21-48
Number of pages28
JournalQueueing Systems
Volume98
Issue number1-2
DOIs
StatePublished - Jun 2021

Keywords

  • Asymptotic independence
  • Cancel on completion
  • Cancel on start
  • Large-scale service systems
  • Load distribution and balancing
  • Multi-component jobs
  • Redundancy
  • Replication
  • Steady-state

ASJC Scopus subject areas

  • Statistics and Probability
  • Computer Science Applications
  • Management Science and Operations Research
  • Computational Theory and Mathematics

Fingerprint Dive into the research topics of 'Large-scale parallel server system with multi-component jobs'. Together they form a unique fingerprint.

Cite this