QD-AMVA: Evaluating systems with queue-dependent service requirements

Giuliano Casale, Juan F. Pérez, Weikun Wang

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Abstract Workload measurements in enterprise systems often lead to observe a dependence between the number of requests running at a resource and their mean service requirements. However, multiclass performance models that feature these dependences are challenging to analyze, a fact that discourages practitioners from characterizing workload dependences. We here focus on closed multiclass queueing networks and introduce QD-AMVA, the first approximate mean-value analysis (AMVA) algorithm that can efficiently and robustly analyze queue-dependent service times in a multiclass setting. A key feature of QD-AMVA is that it operates on mean values, avoiding the computation of state probabilities. This property is an innovative result for state-dependent models, which increases the computational efficiency and numerical robustness of their evaluation. Extensive validation on random examples, a cloud load-balancing case study and comparison with a fluid method and an existing AMVA approximation prove that QD-AMVA is efficient, robust and easy to apply, thus enhancing the tractability of queue-dependent models.

Original languageEnglish (US)
Article number1821
Pages (from-to)80-98
Number of pages19
JournalPerformance Evaluation
Volume91
DOIs
StatePublished - Sep 1 2015
Externally publishedYes

Fingerprint

Mean Value Analysis
Value engineering
Queue
Dependent
Requirements
Multi-class
Workload
Multiclass Queueing Networks
Closed Queueing Networks
Queueing networks
Tractability
Performance Model
Computational efficiency
Load Balancing
Mean Value
Computational Efficiency
Resource allocation
Robustness
Fluid
Resources

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Hardware and Architecture
  • Computer Networks and Communications

Cite this

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QD-AMVA : Evaluating systems with queue-dependent service requirements. / Casale, Giuliano; Pérez, Juan F.; Wang, Weikun.

In: Performance Evaluation, Vol. 91, 1821, 01.09.2015, p. 80-98.

Research output: Contribution to journalArticle

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