Mapping tasks onto distributed heterogeneous computing systems using a genetic algorithm approach
Date
2001
Authors
Siegel, Howard Jay, author
Braun, Tracy D., author
Theys, Mitchell D., author
Maciejewski, Anthony A., author
John Wiley & Sons, Inc., publisher
Journal Title
Journal ISSN
Volume Title
Abstract
Much work has been done using GAs of various types to solve the problem of matching and scheduling of tasks and meta-tasks in a mixed-machine distributed, heterogeneous computing environment. This chapter has discussed three types of genetic algorithms that have been studied to solve this problem. Each implementation has particular specifications and qualifications that were being met. In all cases, the genetic algorithm proved to be a useful method for solving the making and scheduling problem being researched.