|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|4950257||1364283||2018||13 صفحه PDF||ندارد||دانلود کنید|
â¢A new problem in cloud-based MapReduce computations is identified and formulated.â¢An event-driven framework is proposed to tackle the problem.â¢Two new resource scaling algorithms used in the framework are proposed.â¢The proposed event-driven framework and new resource scaling algorithms are evaluated.
How to guarantee Quality of Service (QoS) with the minimum resource cost has become a new problem in cloud-based computation-intensive MapReduce computations. However, the new problem is challenging as the cloud-based MapReduce environment is dynamically changing. As a result, a static resource allocation scheme is not suitable for cloud-based MapReduce as resources may be under-provisioning, which leads to violations in the QoS of cloud-based MapReduce, or over-provisioning, which increases unnecessary resource cost. This paper abstracts the problem of cloud-based computation-intensive MapReduce computations as a dynamical optimization problem, and proposes an event-driven resource provisioning framework to solve that problem. This new event-driven framework has been compared with existing popular static resource provisioning frameworks and periodic resource provisioning frameworks by experiments. The experimental results have shown that the new event-driven resource provisioning framework not only guarantees the QoS of those MapReduce computations, but also reduces the running cost of MapReduce computations by 4.87â21.61 percent compared with those static resource provisioning frameworks, and by 1.70â16.12 percent compared with those periodic resource provisioning frameworks.
Journal: Future Generation Computer Systems - Volume 78, Part 1, January 2018, Pages 18-30