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Journal ArticleDOI

Hybrid optimization for virtual machine migration of utilizing healthcare text in the cloud

R. Prathap, +1 more
- 01 Jun 2021 - 
- Vol. 24, Iss: 2, pp 359-365
TLDR
This study suggests a modern cloud-based Health care services paradigm for optimizing VM migration utilizing Parallel Particle Swarm Optimization (PPSO) and reveals that the suggested model is 67% better than other referred versions.
Abstract
Cloud computing as the modern technology that generates, processing, storing, and sharing of medical data has evolved significantly. The health industry has made a lot of progress in transforming its data management activities, from regular storage to the digitalization of health care data. Cloud computing impacting based on lowering of costs, availability of resources, and power. moreover patient has the right or ownership of data in-the-cloud virtualization technology. Keeping the data of the patient in the cloud also facilitates interoperability between the various sectors of the health-care sector-pharmacy, insurance, and payments. Cloud offers virtual hardware, runtime settings, and facilities for those with a credit card. Cloud infrastructure has become a common term for reference to various devices, resources, and concepts. The proposed framework provides a simulated migration approach that is complex and energy-intensive. By activating idle physical machinery mode, this mechanism reduces the power to conserve electricity. This study suggests a modern cloud-based Health care services paradigm for optimizing VM migration utilizing Parallel Particle Swarm Optimization (PPSO). To measure the performance of our VMs model, a new model for health care service is also provided. The findings reveal that, in the overall deployment period, the new model approaches 60% of the state-of-the-art implementations. Furthermore, device performance is increased by 6.2% for demanded data in real-time. Furthermore, the accuracy of the smart hybrid model of resource utilization is 96.8%. In all associated activities, the suggested model is 67% better than other referred versions.

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Citations
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Improved beetle swarm optimization algorithm for energy efficient virtual machine consolidation on cloud environment

TL;DR: Improved beetle swarm optimization (IBSO) algorithm based on energy‐aware VM consolidation is presented in this article, and it is depicted that the proposed approach outperformed different previous methods in terms of different evaluation measures.
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Sea lion attacking‐based deer hunting optimization algorithm for dynamic nurse scheduling in health care sector contribution of hybrid algorithm in cloud

TL;DR: The main intent of this article is to frame the dynamic NSP in the cloud using a multi‐objective optimization strategy called sea lion attacking‐based deer hunting optimization algorithm to generate a feasible and near‐optimal schedule at the end of the horizon.
References
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Journal ArticleDOI

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TL;DR: A new model based on cloud environment using Parallel Particle Swarm Optimization (PPSO) to optimize the VMs selection and a new model for chronic kidney disease (CKD) diagnosis and prediction is proposed to measure the performance of the proposed VMs model.
Journal ArticleDOI

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TL;DR: This paper proposes a novel VM placement policy that prefers placing a migratable VM on a host that has the minimum correlation coefficient, and runs simulations to conclude that the policies it proposes perform better than existing policies in terms of energy consumption, VM migration time, and SLA violation percentage.

Bees Life Algorithm for Job Scheduling in Cloud Computing

TL;DR: A new Bee Swarm optimization algorithm called Bees Life Algorithm (BLA) applied to efficiently schedule computation jobs among processing resources onto the cloud datacenters showed that BLA outperforms GA in terms of execution time (makespan) with the least complexity.
Journal ArticleDOI

Cloud Computing Simulation Using CloudSim

TL;DR: As the authors know that Cloud Computing is a new paradigm in IT, it has many advantages and disadvantages but in future it will spread in the whole world and all their resources will be available in the cloud.
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