An Evolutionary Multitasking Algorithm for Cloud Computing Service Composition

2018 ◽  
pp. 130-144 ◽  
Author(s):  
Liang Bao ◽  
Yutao Qi ◽  
Mengqing Shen ◽  
Xiaoxuan Bu ◽  
Jusheng Yu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Service Composition ◽  
Cloud Computing Service ◽  
Evolutionary Multitasking

Cloud computing service composition: A systematic literature review

2014 ◽  
Vol 41 (8) ◽  
pp. 3809-3824 ◽  
Author(s):  
Amin Jula ◽  
Elankovan Sundararajan ◽  
Zalinda Othman
Keyword(s):  
Cloud Computing ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Service Composition ◽  
Cloud Computing Service

scholarly journals Color Revolution: A Novel Operator for Imperialist Competitive Algorithm in Solving Cloud Computing Service Composition Problem

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 177
Author(s):  
Amin Jula ◽  
Elankovan A. Sundararajan ◽  
Zalinda Othman ◽  
Narjes Khatoon Naseri
Keyword(s):  
Cloud Computing ◽  
Service Time ◽  
Service Composition ◽  
Large Scale ◽  
Cost Optimization ◽  
Imperialist Competitive Algorithm ◽  
Time Cost ◽  
Competitive Algorithm ◽  
Cloud Computing Service ◽  
Color Revolution

In this paper, a novel high-performance and low-cost operator is proposed for the imperialist competitive algorithm (ICA). The operator, inspired by a sociopolitical movement called the color revolution that has recently arisen in some countries, is referred to as the color revolution operator (CRO). The improved ICA with CRO, denoted as ICACRO, is significantly more efficient than the ICA. On the other hand, cloud computing service composition is a high-dimensional optimization problem that has become more prominent in recent years due to the unprecedented increase in both the number of services in the service pool and the number of service providers. In this study, two different types of ICACRO, one that applies the CRO to all countries of the world (ICACRO-C) and one that applies the CRO solely to imperialist countries (ICACRO-I), were used for service time-cost optimization in cloud computing service composition. The ICACRO was evaluated using a large-scale dataset and five service time-cost optimization problems with different difficulty levels. Compared to the basic ICA and niching PSO, the experimental and statistical tests demonstrate that the ability of the ICACRO to approach an optimal solution is considerably higher and that the ICACRO can be considered an efficient and scalable approach. Furthermore, the ICACRO-C is stronger than the ICACRO-I in terms of the solution quality with respect to execution time. However, the differences are negligible when solving large-scale problems.

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