The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving
  • Editorial Board

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Computing Conference 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future of Information and Communication Conference (FICC) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Hybrid Invasive Weed Optimization with Tabu Search Algorithm for an Energy and Deadline Aware Scheduling in Cloud Computing

Author 1: Pradeep Venuthurumilli
Author 2: Sridhar Mandapati

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2020.0111251

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 12, 2020.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: The current existing high flexibility, profitability, and potential have made cloud computing extremely popular among the companies. This is used for improving and applying resources in an efficient manner and optimize makespan of the tasks. Scheduling is easy while there are only a few tasks to complete with few resources. Contrastingly, at the time the users forward several demands to the environment of the cloud, there may be a need for optimally selecting and allocating resources for achieving the desired quality of service that makes scheduling challenging. In this work, using intelligent metaheuristic algorithms for processing the requests and tasks of users in energy-aware scheduling made for a deadline is proposed. Genetic Algorithm (GA) the evolutionary algorithm that is inspired by the natural process of selection and the evolution theory. The Invasive Weed Optimization (IWO) was yet another novel stochastic based on the population that was a derivative-free technique of optimization inspired by the growth of the weed plants. The TABU Search (TS) was a generalization technique of local search where the TABU list was used for preventing cycling and further generating the candidates of the neighborhood. A hybrid GA with the TS (GA-TS) with a hybrid IWO with TS (IWO-TS) has been proposed for the energy and deadline aware scheduling. The framework further offers optimization of energy and performance. The primary purpose of this algorithm has been to improve deadline and scheduling in cloud computing along with local as well as global search algorithms. This framework will offer optimization of performance and energy. The reason behind presenting this algorithm was improving both scheduling and deadline in cloud computing using both local and global algorithms and results proved the algorithm to have better results.

Keywords: Cloud computing; scheduling; Genetic Algorithm (GA); Invasive Weed Optimization (IWO) and Tabu Search (TS)

Pradeep Venuthurumilli and Sridhar Mandapati, “Hybrid Invasive Weed Optimization with Tabu Search Algorithm for an Energy and Deadline Aware Scheduling in Cloud Computing” International Journal of Advanced Computer Science and Applications(IJACSA), 11(12), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111251

@article{Venuthurumilli2020,
title = {Hybrid Invasive Weed Optimization with Tabu Search Algorithm for an Energy and Deadline Aware Scheduling in Cloud Computing},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111251},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111251},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {12},
author = {Pradeep Venuthurumilli and Sridhar Mandapati}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2021

29-30 April 2021

  • Virtual

Computing Conference 2021

15-16 July 2021

  • London, United Kingdom

IntelliSys 2021

2-3 September 2021

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2021

28-39 October 2021

  • Vancouver, Canada
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Your Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • FAQ's
  • Terms and Conditions
  • Privacy Policy

© 2018 The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org