An Approach for Energy-Efficient Resource Allocation Through Early Planning of Virtual Machines to Servers in Cloud Server Farms

Kumar, Parveen; Kumar, Sunil; Priya, L.

doi:10.1007/978-981-19-5868-7_54

Cited by 7 publications

(1 citation statement)

References 14 publications

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“…In present times, cloud computing [1,2] has become a major trend in many areas of our lives, including businesses, government, entrepreneurship, manufacturers, and business. A parallel and distributed system known as cloud computing allows for the sharing of centralized data storage, data processing tasks, and online access to information technology services or resources by connecting groups of remote servers.…”

Section: Introductionmentioning

confidence: 99%

DLTN-LOSP: A Novel Deep-Linear-Transition-Network-Based Resource Allocation Model with the Logic Overhead Security Protocol for Cloud Systems

Ramachandran,

Naqi,

Perumal

et al. 2023

Sensors

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Cloud organizations now face a challenge in managing the enormous volume of data and various resources in the cloud due to the rapid growth of the virtualized environment with many service users, ranging from small business owners to large corporations. The performance of cloud computing may suffer from ineffective resource management. As a result, resources must be distributed fairly among various stakeholders without sacrificing the organization’s profitability or the satisfaction of its customers. A customer’s request cannot be put on hold indefinitely just because the necessary resources are not available on the board. Therefore, a novel cloud resource allocation model incorporating security management is developed in this paper. Here, the Deep Linear Transition Network (DLTN) mechanism is developed for effectively allocating resources to cloud systems. Then, an Adaptive Mongoose Optimization Algorithm (AMOA) is deployed to compute the beamforming solution for reward prediction, which supports the process of resource allocation. Moreover, the Logic Overhead Security Protocol (LOSP) is implemented to ensure secured resource management in the cloud system, where Burrows–Abadi–Needham (BAN) logic is used to predict the agreement logic. During the results analysis, the performance of the proposed DLTN-LOSP model is validated and compared using different metrics such as makespan, processing time, and utilization rate. For system validation and testing, 100 to 500 resources are used in this study, and the results achieved a make-up of 2.3% and a utilization rate of 13 percent. Moreover, the obtained results confirm the superiority of the proposed framework, with better performance outcomes.

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Section: Introductionmentioning

confidence: 99%