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首页> 外文会议>International Symposium on Computer Architecture and High Performance Computing Workshop >Parallelism and Scalability: A Solution Focused on the Cloud Computing Processing Service Billing
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Parallelism and Scalability: A Solution Focused on the Cloud Computing Processing Service Billing

机译：并行性和可伸缩性：专注于云计算处理服务计费的解决方案

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摘要

The application scheduling is an important requirement in the cloud computing context. It allows to define the required resources to execute applications tasks following predefined criteria, for instance, maximum execution time, number of virtual machines, volume of data, among others. Selecting process to choose the most appropriate execution structure is driven by scheduling algorithms. This paper proposes a scheduling mechanism for data processing in cloud computing environments. Such mechanism analyzes some specific variables in the business context of a software house specialized in software for lawyers and law offices. The main goal of this mechanism is to fulfill the seasonal company's demand using IaaS services and considering two policies: (i) the maximum execution time allowed by the application may not be exceeded and (ii) the data have to be processed considering the lowest possible monetary cost. The proposed solution generates strategies to select the best set of virtual machines to process the current bunch of data considering the amount of data, the estimated execution time for each specific strategy and the monetary cost of the virtual machines sets. In the context of this work, the strategy concept means the schedule of a set of virtual machines to process a specific amount of data, load balancing decisions and the parallelism of application's execution flow. The proposed solution has resulted in great impact for that company since it allowed the vertiginous increase of the amount of clients served.
机译：在云计算环境中，应用程序调度是一项重要要求。它允许根据预定义的标准（例如，最大执行时间，虚拟机数量，数据量等）来定义执行应用程序任务所需的资源。通过调度算法来驱动选择最合适的执行结构的选择过程。本文提出了一种用于云计算环境中数据处理的调度机制。这种机制在专门为律师和律师事务所提供软件的软件公司的业务环境中分析某些特定变量。该机制的主要目标是使用IaaS服务并考虑以下两个策略来满足季节性公司的需求：（i）应用程序所允许的最大执行时间可能不会超过;（ii）必须考虑尽可能最低的条件来处理数据货币成本。所提出的解决方案考虑到数据量，每个特定策略的估计执行时间以及虚拟机集的货币成本，生成了用于选择最佳虚拟机集以处理当前数据集的策略。在本文中，策略概念是指一组虚拟机的时间表，以处理特定数量的数据，负载平衡决策以及应用程序执行流程的并行性。提议的解决方案对该公司产生了巨大的影响，因为它可以显着增加服务的客户数量。

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