An Optimal Time-Based Resource Allocation for Biomedical Workflow Applications in Cloud

Mohanapriya, N.; Kousalya, G.; Balakrishnan, P.

doi:10.1080/03772063.2020.1724521

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…The service industry and academic communities have taken note of these developments (Heidari and Navimipour, 2021; Sheng et al , 2020). One of the significant factors of information structures is cloud computing (Mohanapriya et al , 2020; Rahimi et al , 2021). National Institute of Standards and Technology (NIST) describes it as a paradigm to allow proper and on-demand access to a collective category of configurable resources that can be easily authenticated and published with little managing difficulty or provider interference (Lynn et al , 2018).…”

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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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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“…17 However, the increasing popularity and benefits of using cloud computing have encouraged researchers to make great efforts to provide appropriate solutions and tools to facilitate cloud migration. 18 With the growth and adoption of cloud computing, the difficulty of cloud migration decision-making has prompted several business managers and research institutes to focus on developing cloud migration decision support systems. 19 Cloud service providers have also made efforts to address this demand by providing various guidelines and evaluation tools.…”

Section: Research Backgroundmentioning

confidence: 99%

“…When choosing cloud services, engineers and designers have to consider a set of heterogeneous conditions and criteria with complex dependencies, which seems impossible to do manually; so, this is a big challenge 17 . However, the increasing popularity and benefits of using cloud computing have encouraged researchers to make great efforts to provide appropriate solutions and tools to facilitate cloud migration 18 . With the growth and adoption of cloud computing, the difficulty of cloud migration decision‐making has prompted several business managers and research institutes to focus on developing cloud migration decision support systems 19 .…”

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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Fault-Tolerant Based Group Key Servers with Enhancement of Utilizing the Contributory Server for Cloud Storage Applications

Vivekrabinson¹,

Muneeswaran²

2021

IETE Journal of Research

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An Optimal Time-Based Resource Allocation for Biomedical Workflow Applications in Cloud

Cited by 4 publications

References 10 publications

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

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

Fault-Tolerant Based Group Key Servers with Enhancement of Utilizing the Contributory Server for Cloud Storage Applications

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