Abstract

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.

Highlights

  • Different goals have been pursued by different researchers in solving the CCSC problem, but a factor common to most of these studies is the consideration of QoS parameters, service time and service cost

  • Further inspection of the results suggests that the mean difference between these two algorithms is significant and increases as the problem size increases

  • Based on the trends of the algorithm results, it can be concluded that the larger the problem size, the more efficient the performance of the ICACRO-C compared to that of the ICACRO-I

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Cloud suppliers are confronted with a difficult optimization such as the[4,9,10,11,12]: STCOCCSC greatly reduces the efficiency of the algorithm In this services study, a new problem providing the optimal compositions of unique thatoperwill satisfy ator is designed and proposed for the ICA to improve its efficiency in investigating large searchrequests. The experimental design and test results obtained using two different types of the ICACRO as well as two other algorithms, i.e., the ICA and niching particle swarm optimization (PSO), including numerical and statistical investigations, are discussed in detail in Sections 4 and 5, respectively.

Literature Review
Problem and Algorithm Description
Imperialist Competitive
Imperialist
ICACRO
Definitions
Comparison of Results and Discussion
Comparison
ICACRO-C or ICACRO-I?
B Problem C Problem
Fps or Fs?
Findings
Conclusions and Directions for Future Research
Full Text
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