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MCDA_CC 2017 : Special Session (in conjunction with ICC 2017-Cambridge:UK):MCDA methods for Cloud Services discovery, selection and composition

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Link: http://icc-conference.org/index.php/special-sessions
 
When Mar 22, 2017 - Mar 23, 2017
Where Cambrigde_UK
Submission Deadline Oct 15, 2016
Categories    MCDA   cloud service   composition   selection
 

Call For Papers

Organizers names :

Dr. Hioual Ouassila. Department of Mathematics and Computer, Sciences and Technology Faculty, Khenchela University, Algeria

Dr. Hemam Sofiane Mounine . Department of Mathematics and Computer, Sciences and Technology Faculty, Khenchela University, Algeria


Aim and scope of the special session:

The increasing number of Cloud services available on the Web raises the new challenges which involve the issues relating to service selection, discovery and composition. Cloud Service discovery, selection and composition are the most significant topics in recent research on Service oriented Architectures (SOA). Several approaches have been proposed to solve the service selection problem, including multi-criteria decision analysis (MCDA). By using MCDA, the user will be able to choose from among a number of available choices.

This special session aims to consolidate and disseminate the latest developments and advances in these emerging focus areas. We encourage participation from both academic and industry researchers working in the area of using MCDA methods and architectures for Cloud Services technologies, theories, services, architectures, and protocols. The main goal is to present a latest snapshot of the cutting-edge research as well as to shed light on future directions in this exciting area.

Topics covered by the special session:
Fault tolerance in Cloud.
Cloud Federation and Hybrid Cloud Infrastructure.
Cloud Service Management and Load Balancing.
Architectures based MCDA for Cloud Services discovery, Selection and composition. Scalability and reliability issues in cloud computing.
Algorithms, protocols and designs for cloud systems and networks.
MCDA technologies for Cloud services discovery, Selection and composition


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