Adaptive cloud orchestration resource selection using rough set theory

R. Manikandan; Rajesh Kumar Maurya; Tariq Rasheed; S. Subash Chandra Bose; José Luis Arias-Gonzáles; Udit Mamodiya; Ashish Tiwari

doi:10.47974/JIM-1662

Adaptive cloud orchestration resource selection using rough set theory

R. Manikandan, Rajesh Kumar Maurya, Tariq Rasheed, S. Subash Chandra Bose, José Luis Arias-Gonzáles, Udit Mamodiya, Ashish Tiwari

Research output: Contribution to journal › Article › peer-review

28 Scopus citations

Abstract

The recent research is developing in a vast speed to develop the cloud orchestration system. In cloud system the remotely managed servers are storing, finding, removing, replacing and retrieving the various services in an adaptive optimized manner. The lot of services are provided by the vast number of providers in the market with the help of approximation theory by the rough set system (RST). RST finds in helping in getting the efficient cloud resources as a service to the users. The proposed OCRS (Optimized Cost Resource System) approach is being simulated and compared with the existing cloud simulator. The simulator gives the approximate results in many parameters of cloud services. In all aspects our algorithm is performing better.

Original language	English
Pages (from-to)	311-320
Number of pages	10
Journal	Journal of Interdisciplinary Mathematics
Volume	26
Issue number	3
DOIs	https://doi.org/10.47974/JIM-1662
State	Published - 2023
Externally published	Yes

Keywords

Approximation system
Cloud parameters
Cloud Services
Cloud Simulation
Resource optimization
Rough set theory
Service parameters

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10.47974/JIM-1662

Cite this

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abstract = "The recent research is developing in a vast speed to develop the cloud orchestration system. In cloud system the remotely managed servers are storing, finding, removing, replacing and retrieving the various services in an adaptive optimized manner. The lot of services are provided by the vast number of providers in the market with the help of approximation theory by the rough set system (RST). RST finds in helping in getting the efficient cloud resources as a service to the users. The proposed OCRS (Optimized Cost Resource System) approach is being simulated and compared with the existing cloud simulator. The simulator gives the approximate results in many parameters of cloud services. In all aspects our algorithm is performing better.",

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AU - Rasheed, Tariq

AU - Bose, S. Subash Chandra

AU - Arias-Gonzáles, José Luis

AU - Mamodiya, Udit

AU - Tiwari, Ashish

PY - 2023

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AB - The recent research is developing in a vast speed to develop the cloud orchestration system. In cloud system the remotely managed servers are storing, finding, removing, replacing and retrieving the various services in an adaptive optimized manner. The lot of services are provided by the vast number of providers in the market with the help of approximation theory by the rough set system (RST). RST finds in helping in getting the efficient cloud resources as a service to the users. The proposed OCRS (Optimized Cost Resource System) approach is being simulated and compared with the existing cloud simulator. The simulator gives the approximate results in many parameters of cloud services. In all aspects our algorithm is performing better.

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Adaptive cloud orchestration resource selection using rough set theory

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Keywords

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