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رضائی, ., ghobaei, M. (2022). The Presentation of a Solution to Optimize the Time and Cost of Software Component Placement Using a Multi-Objective Meta-Exploratory Algorithm in the Cloud Environment. Electronic and Cyber Defense, 1(4), 19-33.
مریم رضائی; mostafa ghobaei. "The Presentation of a Solution to Optimize the Time and Cost of Software Component Placement Using a Multi-Objective Meta-Exploratory Algorithm in the Cloud Environment". Electronic and Cyber Defense, 1, 4, 2022, 19-33.
رضائی, ., ghobaei, M. (2022). 'The Presentation of a Solution to Optimize the Time and Cost of Software Component Placement Using a Multi-Objective Meta-Exploratory Algorithm in the Cloud Environment', Electronic and Cyber Defense, 1(4), pp. 19-33.
رضائی, ., ghobaei, M. The Presentation of a Solution to Optimize the Time and Cost of Software Component Placement Using a Multi-Objective Meta-Exploratory Algorithm in the Cloud Environment. Electronic and Cyber Defense, 2022; 1(4): 19-33.

The Presentation of a Solution to Optimize the Time and Cost of Software Component Placement Using a Multi-Objective Meta-Exploratory Algorithm in the Cloud Environment

مجله نوآوری های فناوری اطلاعات و ارتباطات کاربردی
Volume 1, Issue 4, September 2021, Pages 19-33    PDF (1.34 M)
Document Type: -
Authors
مریم رضائی; mostafa ghobaei*
Assistant Professor, facuty of Engineering, Qom Branch,Islamic Azad university,Qom, Iran
Receive Date: 19 February 2021,  Revise Date: 11 June 2021,  Accept Date: 14 August 2021 
Abstract
In the last decade, cloud computing has attracted the attention of many IT providers and users. One of the most widely used models of providing services in the field of cloud computing is the “software as a service” or SaaS model, which is usually provided as a combination of data and application components. One of the major challenges in this area is finding the optimal location for the software components on the cloud infrastructure where the software as a service can perform at its best. The problem of locating software as a service, addresses the challenge of determining which components in the cloud data center can host which components without violating the limitations of the software as a service. In this paper, we have presented a multi-objective optimization solution with the aim of reducing costs and execution time for locating components in cloud environments. We have simulated our proposed solution using the Cloudsim library and finally evaluated and compared it with two multi-objective and cuckoo search algorithms. The simulation results show that the proposed solution performs better than the two basic algorithms, reducing the implementation time of the “software as a service” components and the costs by 9.4% and 9.1% respectively, and increasing the productivity by 7.9%.
Keywords
Cloud Computing; Hybrid Software Components; Resource Management; SaaS Placement; Multi Objective Genetic Algorithm
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