Beyond processor sharing

  • Authors:
  • Samuli Aalto;Urtzi Ayesta;Sem Borst;Vishal Misra;Rudesindo Núñez-Queija

  • Affiliations:
  • TKK Helsinki University of Technology, TKK, Finland;LAAS-CNRS, Toulouse Cedex, France;Bell Laboratories, Alcatel-Lucent, Murray Hill, NJ and CWI, Amsterdam, The Netherlands and Eindhoven University of Technology, Eindhoven, The Netherlands;Columbia University, New York, NY;CWI, Amsterdam, The Netherlands and TNO Information and Communication Technology, Delft, The Netherlands

  • Venue:
  • ACM SIGMETRICS Performance Evaluation Review
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

While the (Egalitarian) Processor-Sharing (PS) discipline offers crucial insights in the performance of fair resource allocation mechanisms, it is inherently limited in analyzing and designing differentiated scheduling algorithms such as Weighted Fair Queueing and Weighted Round-Robin. The Discriminatory Processor-Sharing (DPS) and Generalized Processor-Sharing (GPS) disciplines have emerged as natural generalizations for modeling the performance of such service differentiation mechanisms. A further extension of the ordinary PS policy is the Multilevel Processor-Sharing (MLPS) discipline, which has captured a pivotal role in the analysis, design and implementation of size-based scheduling strategies. We review various key results for DPS, GPS and MLPS models, highlighting to what extent these disciplines inherit desirable properties from ordinary PS or are capable of delivering service differentiation.