A comparative study of online scheduling algorithms for networks of workstations

  • Authors:
  • Olaf Arndt;Bernd Freisleben;Thilo Kielmann;Frank Thilo

  • Affiliations:
  • Department of Electrical Engineering and Computer Science, University of Siegen, Germany;Department of Electrical Engineering and Computer Science, University of Siegen, Germany;Department of Mathematics and Computer Science, Vrije Universiteit, Amsterdam, The Netherlands;Department of Electrical Engineering and Computer Science, University of Siegen, Germany

  • Venue:
  • Cluster Computing
  • Year:
  • 2000

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Abstract

Networks of workstations offer large amounts of unused processing time. Resource management systems are able to exploit this computing capacity by assigning compute‐intensive tasks to idle workstations. To avoid interferences between multiple, concurrently running applications, such resource management systems have to schedule application jobs carefully. Continuously arriving jobs and dynamically changing amounts of available CPU capacity make traditional scheduling algorithms difficult to apply in workstation networks. Online scheduling algorithms promise better results by adapting schedules to changing situations. This paper compares six online scheduling algorithms by simulating several workload scenarios. Based on the insights gained by simulation, the three online scheduling algorithms performing best were implemented in the Winner resource management system. Experiments conducted with Winner in a real workstation network confirm the simulation results obtained.