A new approach for service migration in cloud‐based e‐commerce using an optimization algorithm

Huang, Lixia; Abnoosian, Karlo

doi:10.1002/dac.4457

Cited by 7 publications

(4 citation statements)

References 51 publications

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“…This work, being scalable, can identify the incidence values of each item in a survey that evaluates a factor [43]. With this feature, it is possible to design surveys that guarantee the quality of the data and capture the real impression of the consumer with respect to the digital market [44]. The application of the method and the results obtained made it possible to generate a comparison with related works.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Data from Surveys for the Identification of the Factors That Influence the Migration of Small Companies to eCommerce

et al. 2022

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Currently, medium and small businesses face a significant change in the way consumers purchase their services, products, or goods. This change is fundamentally due to the pandemic caused by the 2019 coronavirus disease, during which people were forced to use information and communication technologies to satisfy their needs and interact with other people. After the pandemic, people’s dependence on technology increased exponentially, to such an extent that the Internet has become the channel through which any product can be purchased in an agile and varied way, from the comfort of home, and regardless of schedules. Therefore, for companies, moving from the traditional market to eCommerce is a necessity, but the change must take place efficiently. Therefore, identifying the factors that influence consumers to access a brand, a service, or a product is a characteristic of eCommerce. This paper presents an analysis of the factors that influence the use of electronic commerce. For this, a review of similar works was carried out for the design of surveys and the identification of the critical points considered by consumers. These data were analyzed in a granular way with tools used in business intelligence to improve decision making in the migration to a digital market.

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Section: Discussionmentioning

confidence: 99%

Analysis of Data from Surveys for the Identification of the Factors That Influence the Migration of Small Companies to eCommerce

et al. 2022

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“…Software is offered to clients as on-demand services, normally in a browser, in SaaS. It reduces the difficulties of software disposal and maintenance (Huang and Abnoosian, 2020). A model of cloud computing services is depicted in Figure 1.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…Traditional trade has been transformed by e-commerce, which is online vs real-life commerce. The following are few examples of E-commerce: stocks, retailing, bond investing, banking, real estate dealing, auctions, airline booking and movie rentals – nearly anything you might consider in the real world (Huang and Abnoosian, 2020). Moreover, a cloud-based e-commerce technology model helps retailers execute e-commerce operations effectively when working with minimal resources (Rukhsara et al , 2016).…”

Section: Proposed Methodsmentioning

confidence: 99%

A new method for human resource allocation in cloud-based e-commerce using a meta-heuristic algorithm

Al-Shourbaji

Zogaan

2021

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PurposeThe human resource (HR) allocation problem is one of the critical dimensions of the project management process. Due to this nature of the problem, researchers are continually optimizing one or more critical scheduling and allocation challenges in different ways. This study aims to optimize two goals, increasing customer satisfaction and reducing costs using the imperialist competitive algorithm.Design/methodology/approachCloud-based e-commerce applications are preferred to conventional systems because they can save money in many areas, including resource use, running expenses, capital costs, maintenance and operation costs. In web applications, its core functionality of performance enhancement and automated device recovery is important. HR knowledge, expertise and competencies are becoming increasingly valuable carriers for organizational competitive advantage. As a result, HR management is becoming more relevant, as it seeks to channel all of the workers’ energy into meeting the organizational strategic objectives. The allocation of resources to maximize benefit or minimize cost is known as the resource allocation problem. Since discovering solutions in polynomial time is complicated, HR allocation in cloud-based e-commerce is an Nondeterministic Polynomial time (NP)-hard problem. In this paper, to promote the respective strengths and minimize the weaknesses, the imperialist competitive algorithm is suggested to solve these issues. The imperialist competitive algorithm is tested by comparing it to the literature’s novel algorithms using a simulation.FindingsEmpirical outcomes have illustrated that the suggested hybrid method achieves higher performance in discovering the appropriate HR allocation than some modern techniques.Practical implicationsThe paper presents a useful method for improving HR allocation methods. The MATLAB-based simulation results have indicated that costs and waiting time have been improved compared to other algorithms, which cause the high application of this method in practical projects.Originality/valueThe main novelty of this paper is using an imperialist competitive algorithm for finding the best solution to the HR allocation problem in cloud-based e-commerce.

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“…On cloud‐oriented e‐commerce, Huang and Abnoosian 24 proposed an automated smart service migration outline using the Ant Colony Optimization (ACO) method. The provided model utilized the ACO algorithm to make the best (near‐optimal) service migration decisions.…”

Section: Research Backgroundmentioning

confidence: 99%

A fuzzy‐based method for cloud service migration using a shark smell optimization algorithm

Liu

Cheng

et al. 2022

Concurrency and Computation

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Computation should develop and become more powerful and flexible as a result of the expansion of apps and the incorporation of novel consumers into the realm of computing systems. The potential of live virtual machine (VM) migration among various clouds is one of the growing study fields in cloud computing. It can be more important when the cloud service quality that a user is presently using deteriorates or when a new cloud service is launched that is superior in performance, quality, and pricing to the existing services. Because this problem is NP-Hard in nature, this article proposes a method to migrate the load from an over-loaded VMs to the active machine that is least loaded using a fuzzy-based shark smell optimization algorithm. This algorithm is based on a shark's ability to discover prey as a strong hunter in nature, based on the shark's smell sense and motion to the odor source. The suggested optimization technique mathematically models diverse shark behaviors in the search environment, which is seawater.The CloudSim is utilized to illustrate the efficiency of the approach compared to others. The outcomes reveal that energy consumption and execution time are better than Genetic Algorithm and Particle Swarm Optimization algorithms.

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A new approach for service migration in cloud‐based e‐commerce using an optimization algorithm

Cited by 7 publications

References 51 publications

Analysis of Data from Surveys for the Identification of the Factors That Influence the Migration of Small Companies to eCommerce

Analysis of Data from Surveys for the Identification of the Factors That Influence the Migration of Small Companies to eCommerce

A new method for human resource allocation in cloud-based e-commerce using a meta-heuristic algorithm

A fuzzy‐based method for cloud service migration using a shark smell optimization algorithm

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