Imperialist competitive algorithm with PROCLUS classifier for service time optimization in cloud computing service composition

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

Aiming to provide satisfying and value-added cloud composite services, suppliers put great effort into providing a large number of service providers. This goal, achieved by providing the "best" solutions, will not be guaranteed unless an efficient composite service composer is employed to choose an optimal set of required unique services (with respect to user-defined values for quality of service parameters) from the large number of provided services in the pool. Facing a wide service pool, user constraints, and a large number of required unique services in each request, the composer must solve an NP-hard problem. In this paper, CSSICA is proposed to make advances toward the lowest possible service time of composite service; in this approach, the PROCLUS classifier is used to divide cloud service providers into three categories based on total service time and assign a probability to each provider. An improved imperialist competitive algorithm is then employed to select more suitable service providers for the required unique services. Using a large real dataset, experimental and statistical studies are conducted to demonstrate that the use of clustering improved the results compared to other investigated approaches; thus, CSSICA should be considered by the composer as an efficient and scalable approach.

Original languageEnglish
Pages (from-to)135-145
Number of pages11
JournalExpert Systems with Applications
Volume42
Issue number1
DOIs
Publication statusPublished - 2015

Fingerprint

Cloud computing
Classifiers
Composite materials
Chemical analysis
Computational complexity
Quality of service

Keywords

  • Cloud computing
  • Clustering
  • Imperialist competition algorithm
  • Proclus
  • QoS
  • Quality of service
  • Service composition
  • Service selection
  • Service time

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Engineering(all)

Cite this

@article{38820b6f7af64559ac7fd833a3b67cdf,
title = "Imperialist competitive algorithm with PROCLUS classifier for service time optimization in cloud computing service composition",
abstract = "Aiming to provide satisfying and value-added cloud composite services, suppliers put great effort into providing a large number of service providers. This goal, achieved by providing the {"}best{"} solutions, will not be guaranteed unless an efficient composite service composer is employed to choose an optimal set of required unique services (with respect to user-defined values for quality of service parameters) from the large number of provided services in the pool. Facing a wide service pool, user constraints, and a large number of required unique services in each request, the composer must solve an NP-hard problem. In this paper, CSSICA is proposed to make advances toward the lowest possible service time of composite service; in this approach, the PROCLUS classifier is used to divide cloud service providers into three categories based on total service time and assign a probability to each provider. An improved imperialist competitive algorithm is then employed to select more suitable service providers for the required unique services. Using a large real dataset, experimental and statistical studies are conducted to demonstrate that the use of clustering improved the results compared to other investigated approaches; thus, CSSICA should be considered by the composer as an efficient and scalable approach.",
keywords = "Cloud computing, Clustering, Imperialist competition algorithm, Proclus, QoS, Quality of service, Service composition, Service selection, Service time",
author = "Amin Jula and Zalinda Othman and {A Sundararajan}, Elankovan",
year = "2015",
doi = "10.1016/j.eswa.2014.07.043",
language = "English",
volume = "42",
pages = "135--145",
journal = "Expert Systems with Applications",
issn = "0957-4174",
publisher = "Elsevier Limited",
number = "1",

}

TY - JOUR

T1 - Imperialist competitive algorithm with PROCLUS classifier for service time optimization in cloud computing service composition

AU - Jula, Amin

AU - Othman, Zalinda

AU - A Sundararajan, Elankovan

PY - 2015

Y1 - 2015

N2 - Aiming to provide satisfying and value-added cloud composite services, suppliers put great effort into providing a large number of service providers. This goal, achieved by providing the "best" solutions, will not be guaranteed unless an efficient composite service composer is employed to choose an optimal set of required unique services (with respect to user-defined values for quality of service parameters) from the large number of provided services in the pool. Facing a wide service pool, user constraints, and a large number of required unique services in each request, the composer must solve an NP-hard problem. In this paper, CSSICA is proposed to make advances toward the lowest possible service time of composite service; in this approach, the PROCLUS classifier is used to divide cloud service providers into three categories based on total service time and assign a probability to each provider. An improved imperialist competitive algorithm is then employed to select more suitable service providers for the required unique services. Using a large real dataset, experimental and statistical studies are conducted to demonstrate that the use of clustering improved the results compared to other investigated approaches; thus, CSSICA should be considered by the composer as an efficient and scalable approach.

AB - Aiming to provide satisfying and value-added cloud composite services, suppliers put great effort into providing a large number of service providers. This goal, achieved by providing the "best" solutions, will not be guaranteed unless an efficient composite service composer is employed to choose an optimal set of required unique services (with respect to user-defined values for quality of service parameters) from the large number of provided services in the pool. Facing a wide service pool, user constraints, and a large number of required unique services in each request, the composer must solve an NP-hard problem. In this paper, CSSICA is proposed to make advances toward the lowest possible service time of composite service; in this approach, the PROCLUS classifier is used to divide cloud service providers into three categories based on total service time and assign a probability to each provider. An improved imperialist competitive algorithm is then employed to select more suitable service providers for the required unique services. Using a large real dataset, experimental and statistical studies are conducted to demonstrate that the use of clustering improved the results compared to other investigated approaches; thus, CSSICA should be considered by the composer as an efficient and scalable approach.

KW - Cloud computing

KW - Clustering

KW - Imperialist competition algorithm

KW - Proclus

KW - QoS

KW - Quality of service

KW - Service composition

KW - Service selection

KW - Service time

UR - http://www.scopus.com/inward/record.url?scp=84906535775&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84906535775&partnerID=8YFLogxK

U2 - 10.1016/j.eswa.2014.07.043

DO - 10.1016/j.eswa.2014.07.043

M3 - Article

AN - SCOPUS:84906535775

VL - 42

SP - 135

EP - 145

JO - Expert Systems with Applications

JF - Expert Systems with Applications

SN - 0957-4174

IS - 1

ER -