Task Assignment With Unknown Duration

Abstract

We consider a distributed server system and ask which policy should be used for assigning tasks to hosts. In our server, tasks are not preemptible. Also, the task's service demand is not known a priori. We are particularly concerned with the case where the workload is heavy tailed, as is characteristic of many empirically measured computer workloads. We analyze several natural task assignment policies and propose a new one TAGS (Task Assignment based on Guessing Size). The TAGS algorithm is counterintuitive in many respects, including load unbalancing, non-work-conserving, and fairness. We find that under heavy tailed workloads, TAGS can outperform all task assignment policies known to us by several orders of magnitude with respect to mean response time and mean slowdown, provided the system load is not too high. We also introduce a new practical performance metric for distributed servers called server expansion. Under the server expansion metric, TAGS significantly outperforms all other task assignment policies, regardless of system load.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1999
Accession Number
ADA368426

Entities

People

  • Mor Harchol-balter

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Central Processing Units
  • Coefficients
  • Computations
  • Computer Science
  • Computers
  • Contrast
  • Distribution Functions
  • Environment
  • Feedback
  • Literature
  • Measurement
  • Parallel Processors
  • Probability
  • Scheduling (Production)
  • Simulations
  • Workload

Fields of Study

  • Computer science

Readers

  • Parallel and Distributed Computing.