A QoS-driven approach for cloud computing addressing attributes of performance and security

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• 作者：Bruno Guazzelli Batista^a ; ^{brunoguazzelli@unifei.edu.br}Author Vitae ; Carlos Henrique Gomes Ferreira^bAuthor Vitae ; Danilo Costa Marim Segura^cAuthor Vitae ; Dionisio Machado Leite Filho^dAuthor Vitae ; Maycon Leone Maciel Peixoto^eAuthor Vitae
• 关键词：Cloud computing ; Quality of service ; Performance evaluation ; Security mechanisms ; Resource management
• 刊名：Future Generation Computer Systems
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：68
• 期：Complete
• 页码：260-274
• 全文大小：1344 K
• 卷排序：68

文摘

In recent years, cloud computing has been one of the most widely discussed topics in the field of Information Technology. Owing to the popularity of services offered by cloud environments, several critical aspects of security have aroused interest in the academic and industrial world, where there is a concern to provide efficient mechanisms to combat a wide range of threats. As is well known, the application of security techniques and methodologies has a direct influence on the performance of the system, since security and performance are two quantities that are inversely proportional. This means that if the service providers fail to manage their computing infrastructure efficiently, the demand for services may not be met with the quality required by clients, including security and performance requirements, and the computational resources may be used inefficiently. The aim of this paper was to define QoS-driven approaches for cloud environments on the basis of the results of a performance evaluation of a service in which different security mechanisms are employed. These mechanisms impose additional overhead on the performance of the service, and to counter this, an attempt was made to change computational resources dynamically and on-the-fly. On the basis of the results, it could be shown that in a cloud environment, it is possible to maintain the performance of the service even with the overhead imposed by the security mechanisms, through an alteration in the virtualized computational resources. However, this change in the amount of resources had a direct effect on the response variables.