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

Title:
Imperialist competitive algorithm with PROCLUS classifier for service time optimization in cloud computing service composition
Source:
Expert systems with applications. 42(1):135-145
Publisher Information:
Amsterdam: Elsevier, 2015.
Publication Year:
2015
Physical Description:
print, 3/4 p
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Logiciel, Software, Systèmes informatiques et systèmes répartis. Interface utilisateur, Computer systems and distributed systems. User interface, Organisation des mémoires. Traitement des données, Memory organisation. Data processing, Systèmes d'information. Bases de données, Information systems. Data bases, Algorithme évolutionniste, Evolutionary algorithm, Algoritmo evoluciónista, Amas, Cluster, Montón, Analyse statistique, Statistical analysis, Análisis estadístico, Approche probabiliste, Probabilistic approach, Enfoque probabilista, Classification, Clasificación, Colonie, Colony, Colonia, Composition, Composicion, Compétition, Competition, Competencia, Coordination, Coordinación, Durée service, Service life, Duración servicio, Etude expérimentale, Experimental study, Estudio experimental, Intergiciel publication souscription, Publish subscribe middleware, Intergicial editor suscriptor, Optimisation, Optimization, Optimización, Orienté service, Service oriented, Orientado servicio, Problème NP difficile, NP hard problem, Problema NP duro, Qualité service, Service quality, Calidad servicio, Service utilisateur, User service, Servicio usuario, Service web, Web service, Servicio web, Temps service, Service time, Tiempo servicio, Valeur ajoutée, Added value, Valor añadido, Algorithme compétitif, Competitive algorithms, Algoritmo Competitivo, Base donnée très grande, Very large databases, Base de datos a gran escala, Informatique dans les nuages, Cloud computing, Computación en nube, Offre service, Service Proposal, Proveedores de servicios, Clustering, Imperialist competition algorithm, Proclus, QoS, Quality of service, Service composition, Service selection
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Data Mining and Optimization Research Group, Centre for Artificial Intelligence, UKM Bangi, 43600 Selangor, Malaysia
Centre of Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, UKM Bangi, 43600 Selangor, Malaysia
ISSN:
0957-4174
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.28843388
Database:
PASCAL Archive

Further Information

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.