Static-Task Scheduling Incorporating Precedence Constraints and Deadlines in a Heterogeneous-Computing Environment

Abstract

Distributed systems have grown in popularity due to the rapid increase in networking of personal computers. A mixture of computers consisting of different architectures can be more powerful, reliable, and scalable than a single supercomputer. The problem of optimally scheduling jobs on a cluster of heterogeneous machines to minimize the time at which the last machine finishes is NP-complete. Nonetheless, the choice of a heuristic algorithm greatly affects the speed of solution. This work evaluates a greedy algorithm, an A* algorithm, and a simulated annealing algorithm applied to the heterogeneous scheduling problem with deadline and dependency constraints. Tradeoffs of speed and schedule quality were noted between the algorithms. The greedy algorithm produced results quicker than the A* and simulated annealing algorithms, but with a lower schedule quality. Because of these offsetting performance criteria, an analysis was conducted to determine which algorithms should be used for which input cases.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2000
Accession Number
ADA380969

Entities

People

  • Michael D. Niedert

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Annealing
  • Applied Computer Science
  • Artificial Intelligence
  • Computer Science
  • Computers
  • Distributed Computing
  • Engineering
  • Environment
  • Fish
  • Operating Systems
  • Parallel Computing
  • Personal Computers
  • Scheduling (Production)
  • Two Dimensional
  • United States
  • United States Naval Academy

Fields of Study

  • Computer science

Readers

  • Economics
  • Operations Research
  • Parallel and Distributed Computing.