loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Guang Peng and Katinka Wolter

Affiliation: Department of Mathematics and Computer Science, Free University of Berlin, Takustr. 9, Berlin and Germany

Keyword(s): Task Scheduling, Cloud Computing, Scientific Workflow, Particle Swarm Optimization, Multi-objective Optimization, Gaussian Mutation.

Abstract: An improved multi-objective discrete particle swarm optimization (IMODPSO) algorithm is proposed to solve the task scheduling and resource allocation problem for scientific workflows in cloud computing. First, we use a strategy to limit the velocity of particles and adopt a discrete position updating equation to solve the multi-objective time and cost optimization model. Second, we adopt a Gaussian mutation operation to update the personal best position and the external archive, which can retain the diversity and convergence accuracy of Pareto optimal solutions. Finally, the computational complexity of IMODPSO is compared with three other state-of-the-art algorithms. We validate the computational speed, the number of solutions found and the generational distance of IMODPSO and find that the new algorithm outperforms the three other algorithms with respect to all three metrics.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.222.67.251

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Peng, G. and Wolter, K. (2019). Efficient Task Scheduling in Cloud Computing using an Improved Particle Swarm Optimization Algorithm. In Proceedings of the 9th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-365-0; ISSN 2184-5042, SciTePress, pages 58-67. DOI: 10.5220/0007674400580067

@conference{closer19,
author={Guang Peng. and Katinka Wolter.},
title={Efficient Task Scheduling in Cloud Computing using an Improved Particle Swarm Optimization Algorithm},
booktitle={Proceedings of the 9th International Conference on Cloud Computing and Services Science - CLOSER},
year={2019},
pages={58-67},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007674400580067},
isbn={978-989-758-365-0},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Cloud Computing and Services Science - CLOSER
TI - Efficient Task Scheduling in Cloud Computing using an Improved Particle Swarm Optimization Algorithm
SN - 978-989-758-365-0
IS - 2184-5042
AU - Peng, G.
AU - Wolter, K.
PY - 2019
SP - 58
EP - 67
DO - 10.5220/0007674400580067
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic