CPU and memory allocation optimization using fuzzy logic

Zeev Zalevsky*, Eran Gur, David Mendlovic

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


The allocation of CPU time and memory resources, are well known problems in organizations with a large number of users, and a single mainframe. Usually the amount of resources given to a single user is based on its own statistics, not on the entire statistics of the organization therefore patterns are not well identified and the allocation system is prodigal. In this work the authors suggest a fuzzy logic based algorithm to optimize the CPU and memory distribution between the users based on the history of the users. The algorithm works separately on heavy users and light users since they have different patterns to be observed. The result is a set of rules, generated by the fuzzy logic inference engine that will allow the system to use its computing ability in an optimized manner. Test results on data taken from the Faculty of Engineering in Tel Aviv University, demonstrate the abilities of the new algorithm.

Original languageEnglish
Pages (from-to)259-266
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2002
EventApplications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation V - Seattle, WA, United States
Duration: 9 Jul 200210 Jul 2002


  • Data mining
  • Fuzzy logic
  • Optical data processing


Dive into the research topics of 'CPU and memory allocation optimization using fuzzy logic'. Together they form a unique fingerprint.

Cite this