基于作业延迟完成时间相关历史数据的分布式数据处理系统架构 资源效率改进

A. B. Klimenko
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摘要

研究目的。本研究的目的是开发一种方法,以提高在网络雾层和边缘层运行的数据处理系统分布式架构的效率。在网络基础设施和负载都高度动态的条件下,数据处理系统架构的形成任务需要定期解决(虚拟机迁移、水平扩展б 等),与此同时,计算节点剩余资源的消耗问题实际上没有得到考虑,而经常使用的设备容量相对较低,其高负荷工作导致使用寿命缩短。因此,创建有效节约计算资源的计算设备系统架构的方法是一项紧迫任务。本研究采用的主要科学方法包括领域分析、运筹学方法、优化方法和计算机建模,证实了所开发方法主要方面的可行性。为了提高在网络片段节点上布置计算任务的效率,本文提出了一个多标准优化问题,其中矢量目标函数的每个元素都对应计算设备无故障运行概率的一个单独值。为了获得成本函数的估计值,使用了节点延迟完成计算问题求解的先验估计值,因为分配用于求解的资源取决于分配的时间,而求解问题的时间则分别取决于分配的计算资源。成本函数的值是根据近似先验估计计算得出的,这将对设备计算资源的消耗产生积极影响。研究结果是开发出一种方法,用于提高在网络雾层和边缘层运行的数据处理系统分布式架构的效率。本研究提出的方法可以选择这样的负载分布,以减少设备的工作量,从而降低设备计算资源的消耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Data Proceeding Systems Architectures Resource Efficiency Improvement on the Basis of Apriory Data about the Jobs Late Completion Times
Purpose of research. The purpose of this study is to develop a method for improving the efficiency of distributed architectures of data processing systems operating in the fog and edge layers of the network. In conditions of high dynamics of both the network infrastructure and the load, the task of forming the architecture of data processing systems is solved regularly (migration of virtual machines, horizontal scalingб etc.) At the same time, the issue of the consumption of the residual resource of computing nodes is practically not considered, while the often used devices have relatively low capacity, and their high workload leads to a reduction in the service life. Therefore, the creation of methods for forming an architecture of a computing device system that is effective in terms of saving a computing resource is an urgent task.Methods. The main scientific methods used in this study are domain analysis, operations research methods, optimization methods and computer modeling, confirming the feasibility of the main aspects of the developed method. To improve the efficiency of placing computational tasks on the nodes of a network fragment, this paper formulated a multicriteria optimization problem, where each element of the vector objective function corresponds to an individual value of the probability of failure-free operation of a computing device. To obtain estimated values of the cost function, a priori estimates of the late completion of the solution of computational problems by nodes are used, since the resource allocated for solving depends on the allocated time, and the time for solving the problem, respectively, on the allocated computing resource. The value of the cost function is calculated on the basis of approximate a priori estimates, which leads to a positive effect in terms of the consumption of computing resources of devices.Results. The result of the study is a developed method for improving the efficiency of distributed architectures of data processing systems operating in the fog and edge layers of the network.Conclusion. The method proposed in this work allows to choose such a load distribution in order to reduce the workload of devices and thus reduce the consumption of computing resources of the devices.
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