MARCR: Method of allocating resources based on cost of the resources in a heterogeneous cloud environment
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2023.14.3.03Keywords:
Cloud Computing; Resource allocation; Cost-based Allocation; Heterogeneous Cloud;Dimensions Badge
Issue
Section
License
Copyright (c) 2023 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The cloud is an intelligent technology that provides requested services to users. It offers unlimited services for the users. Many small and medium-scale industries are startup their businesses to the next level using cloud computing. The services have been provided to the users by allocating the requested resources. Allocating resources without waste and with the finest allocation is a critical task in the cloud. This paper proposes a method for allocating resources using the cost of the resource. Resource allocation follows a priority system when allocating resources. The proposed method gives priority to low-cost resources. The cost denotes the service cost of the resource. The requested resource is assigned to the user by the CSP, who provides the specific resource at a low cost. This proposed method suggests a UHRAM for collecting and allocating the resources from the different CSPs. UHRAM is a centralized hub for delivering requested resources to users, and it maintains a repository of details about the resources from all CSPs in the heterogeneous cloud. The proposed method is implemented with the user’s data. The results from the comparison show that the proposed cost-based resource allocation method is more efficient than existing methods.Abstract
How to Cite
Downloads
Similar Articles
- Teklil Abadeye, Teshome Yitbarek, Isreal Zewide, Kibinesh Adimasu, Assessing soil fertility influenced by land use in Moche, Gurage Zone, Ethiopia , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- Karthik Baburaj, Navaneeth kattil Madathil, Roshini Barkur, NLP Based Voice Assistant Usage on Consumer Shopping , The Scientific Temper: Vol. 16 No. Spl-2 (2025): The Scientific Temper
- S Selvakumari, M Durairaj, Performance Analysis of Deep Learning Optimizers for Arrhythmia Classification using PTB-XL ECG Dataset: Emphasis on Adam Optimizer , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- M. A. Shanti, Optimizing predictive accuracy: A comparative study of feature selection strategies in the healthcare domain , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Deepa S, Sripriya T, Radhika M, Jeneetha J. J, Experimental evaluation of artificial intelligence assisted heart disease prediction using deep learning principle , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- L Brigith Gladys, J Merline Vinotha, Multi-objective Multi-route Soft Rough Sustainable Transportation Problem based on Various Road Maintenance Conditions , The Scientific Temper: Vol. 16 No. 10 (2025): The Scientific Temper
- Sirajum Munira Priety, Farhan Bin Manjur, AI Driven Approach in Smart Manufacturing in Bangladesh , The Scientific Temper: Vol. 16 No. 10 (2025): The Scientific Temper
- Priya Rajwade, Alka Bansal, A study of the perceptions of teachers towards a holistic approach in teaching in CBSE board schools in the context of NEP 2020 at the foundational and preparatory stages , The Scientific Temper: Vol. 16 No. Spl-1 (2025): The Scientific Temper
- Abhishek Dwivedi, Nikhat Raza Khan, Reconfiguration of Automated Manufacturing Systems Using Gated Graph Neural Networks , The Scientific Temper: Vol. 13 No. 02 (2022): The Scientific Temper
- Pravin P. P, J. Arunshankar, Development of digital twin for PMDC motor control loop , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
<< < 6 7 8 9 10 11 12 13 14 15 > >>
You may also start an advanced similarity search for this article.
Most read articles by the same author(s)
- Sheena Edavalath, Manikandasaran S. Sundaram, Cost-based resource allocation method for efficient allocation of resources in a heterogeneous cloud environment , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper

