Optimizing Cloud Computing Task Schedules Through Advanced Intelligent Optimization Methods

Ahmed Chiheb Ammari, Rami Al Hmouz, Lazhar Khriji, Meng Chu Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The number of Distributed Green Cloud Datacenters (DGCDs) is globally increasing. Such DGCDs deploy different types of renewable sources to generate clean energy and save money. They are located in different regions depending on the availability of renewable energy sources, costs of bandwidth and grid electricity prices. This paper focuses on applications within them, which are sensitive to delay and looks into a way to schedule different applications with respect to time constraint. The paper uses the Firefly algorithm, bat algorithm and simulated annealing-bat algorithms as optimization techniques to minimize total operational cost of such DGCDs. These algorithms have been compared through data-driven experiments carried out in this study. Of particular note is the Firefly algorithm's superior performance when compared with others.

Original languageEnglish (US)
Title of host publicationProceedings of IEMTRONICS 2024 - International IoT, Electronics and Mechatronics Conference
EditorsPhillip G. Bradford, S. Andrew Gadsden, Shiban K. Koul, Kamakhya Prasad Ghatak
PublisherSpringer Science and Business Media Deutschland GmbH
Pages443-456
Number of pages14
ISBN (Print)9789819747832
DOIs
StatePublished - 2025
EventInternational IoT, Electronics and Mechatronics Conference, IEMTRONICS 2024 - London, United Kingdom
Duration: Apr 3 2024Apr 5 2024

Publication series

NameLecture Notes in Electrical Engineering
Volume1228
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational IoT, Electronics and Mechatronics Conference, IEMTRONICS 2024
Country/TerritoryUnited Kingdom
CityLondon
Period4/3/244/5/24

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

Keywords

  • Bat algorithms
  • Firefly
  • Minimizing operational cost
  • Optimizing task scheduling
  • Renewable energy
  • Simulated annealing

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