FAHP approach for autonomic resource provisioning of multitier applications in cloud computing environments

Summary Recent advancements in web‐based application, especially in cloud computing environment, allows cloud service providers to deploy and provide web‐based services in the form of multitier applications. One of the most suitable infrastructure for the running of multitier applications is a cloud...

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Vydáno v:Software, practice & experience Ročník 48; číslo 12; s. 2147 - 2173
Hlavní autoři: Khorsand, Reihaneh, Ghobaei‐Arani, Mostafa, Ramezanpour, Mohammadreza
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bognor Regis Wiley Subscription Services, Inc 01.12.2018
Témata:
Analytic hierarchy process
autonomic computing
Cloud computing
FAHP
Infrastructure
Java
multitier applications
Object oriented programming
Provisioning
Resource allocation
resource provisioning
Response time
Variation
Virtual environments
workload prediction
ISSN:0038-0644, 1097-024X
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Shrnutí:Summary Recent advancements in web‐based application, especially in cloud computing environment, allows cloud service providers to deploy and provide web‐based services in the form of multitier applications. One of the most suitable infrastructure for the running of multitier applications is a cloud computing infrastructure. Since the arrival rate of users to the multitier applications varies over the time, deciding about the right amount of resources required to handle the each tier of multitier applications is not trivial, and it depends on the current workload of its each tier. Therefore, it is necessary to automatically provision resources to deal with fluctuating demands of the multitier applications. In this paper, we propose a hybrid resource provisioning approach for multitier applications based on a combination of the concept of the autonomic computing and the fuzzy analytical hierarchy process approach. Moreover, we present a framework based on MAPE‐k control loop for autonomous resource provisioning of multitier applications in cloud computing environments. The effectiveness of the proposed approach under real and synthetic workloads was evaluated. The experimental results indicate that the proposed solution outperforms in terms of allocated virtual machines, response time, and cost compared with the other approaches.
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ISSN:0038-0644
1097-024X
DOI:10.1002/spe.2627