A performance model of disha routing in k-ary n-cube networks

A. Khonsari, A. Shahrabi, M. Ould-Khaoua

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

A number of analytical models for predicting message latency in k-ary n-cubes have recently been reported in the literature. Most of these models, however, have been discussed for adaptive routing algorithms based on deadlock avoidance, e.g. Duato's routing. Several research studies have empirically demonstrated that routing algorithms based on deadlock recovery offer maximal adaptivity that can result in considerable improvement in network performance. Disha is an example of a true fully. adaptive routing algorithm that uses minimal hardware to implement a simple and efficient progressive method to recover from potential deadlocks. This paper proposes a new analytical model of Disha in wormhole-routed k-ary n-cubes. Simulation experiments confirm that the proposed model exhibits a good degree of accuracy for various networks sizes and under different traffic conditions.

Original languageEnglish
Pages (from-to)213-228
Number of pages16
JournalParallel Processing Letters
Volume17
Issue number2
DOIs
Publication statusPublished - Jun 2007

Fingerprint

K-ary N-cubes
Performance Model
Routing algorithms
Routing Algorithm
Adaptive Routing
Routing
Deadlock
Adaptive algorithms
Adaptive Algorithm
Analytical Model
Analytical models
Deadlock Avoidance
Wormhole
Adaptivity
Network Performance
Network performance
Simulation Experiment
Latency
Recovery
Traffic

Keywords

  • Adaptive routing
  • Deadlock
  • M/G/1 queues
  • Multicomputers
  • Simulation

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

A performance model of disha routing in k-ary n-cube networks. / Khonsari, A.; Shahrabi, A.; Ould-Khaoua, M.

In: Parallel Processing Letters, Vol. 17, No. 2, 06.2007, p. 213-228.

Research output: Contribution to journalArticle

Khonsari, A. ; Shahrabi, A. ; Ould-Khaoua, M. / A performance model of disha routing in k-ary n-cube networks. In: Parallel Processing Letters. 2007 ; Vol. 17, No. 2. pp. 213-228.
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