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A Framework for a Decision Support System to Optimize Cloud-hosted Services for Multitenancy Isolation

by Laud Charles Ochei, Rotimi Ogunsakin, Nemitari Ajienka
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International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 12 - Number 40
Year of Publication: 2023
Authors: Laud Charles Ochei, Rotimi Ogunsakin, Nemitari Ajienka
10.5120/ijais2023451941

Laud Charles Ochei, Rotimi Ogunsakin, Nemitari Ajienka . A Framework for a Decision Support System to Optimize Cloud-hosted Services for Multitenancy Isolation. International Journal of Applied Information Systems. 12, 40 ( April 2023), 22-39. DOI=10.5120/ijais2023451941

@article{ 10.5120/ijais2023451941,
author = { Laud Charles Ochei, Rotimi Ogunsakin, Nemitari Ajienka },
title = { A Framework for a Decision Support System to Optimize Cloud-hosted Services for Multitenancy Isolation },
journal = { International Journal of Applied Information Systems },
issue_date = { April 2023 },
volume = { 12 },
number = { 40 },
month = { April },
year = { 2023 },
issn = { 2249-0868 },
pages = { 22-39 },
numpages = {9},
url = { https://www.ijais.org/archives/volume12/number40/1135-2023451941/ },
doi = { 10.5120/ijais2023451941 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T19:11:40.774344+05:30
%A Laud Charles Ochei
%A Rotimi Ogunsakin
%A Nemitari Ajienka
%T A Framework for a Decision Support System to Optimize Cloud-hosted Services for Multitenancy Isolation
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 12
%N 40
%P 22-39
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the challenges of optimizing the deployment of components of cloud-hosted services for guaranteeing multitenancy isolation is how to make optimal decisions that involve resolving the trade-off between a lower degree of isolation versus the possible interference that may occur between components or a higher degree of isolation versus the challenge of high resource consumption and the running cost of the components. Although, many cloud providers offer some functionality in the form of rule-based algorithms, such as Amazon’s Auto-Scaling and Microsoft’s Windows Azure Traffic Manager. These functionalities are deployed to configure the scaling function of the cloud-hosted services but do not implement the varying degrees of multitenancy isolation for individual components. The aim of this paper is to present a framework for developing a decision support system for optimizing the deployment of components of cloud-hosted services for guaranteeing multitenancy isolation. The framework comprises of a decision support model algorithm, a system architecture, and an algorithm for creating the input files for implementing the decision support system. Extensive experimental evaluation of the framework with a decision support model algorithm shows that it can be used by cloud providers and users to guarantee varying degrees of isolation between tenants.

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Index Terms

Computer Science
Information Sciences

Keywords

Framework Decision Support System Cloudhosted Service Cloud Deployment Optimization Multitenancy Tenant Isolation

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