Elasticity analysis process oriented cloud resource allocation optimization method

A technology of elasticity analysis and configuration optimization, applied in resource allocation, multi-programming devices, program control devices, etc., can solve problems such as system bottlenecks, and achieve the effect of accurately estimating response time

Active Publication Date: 2017-02-15
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

In the case of continuous arrival of request load, one resource instance is enough for a certain component, but other components may need more instances, otherwise it will become a system bottleneck

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  • Elasticity analysis process oriented cloud resource allocation optimization method
  • Elasticity analysis process oriented cloud resource allocation optimization method
  • Elasticity analysis process oriented cloud resource allocation optimization method

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Embodiment Construction

[0022] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0023] For elastic analysis process, the present invention adopts cloud resource configuration optimization strategy based on queuing network theory. Generally speaking, the analysis process includes multiple components, each component has independent functions and can be deployed independently, and the components have interdependence. The currently existing cloud resource configuration optimization method for workflow is to regard the entire process as a whole and allocate cloud resources to it. In th...

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Abstract

The invention provides an elasticity analysis process oriented cloud resource allocation optimization method. The method comprises the steps of S1, carrying out performance modeling on an elasticity analysis process through adoption of an open queuing network theory, namely modeling the whole analysis process to form an open queuing network, wherein each component in the process corresponds to sub-queues in a queuing network system, and the output of one component is the input of another component; and S2, estimating average response time of the whole open queuing network through a queuing theory, carrying out cloud resource allocation on each component according to the estimated average response time, thereby enabling the total number of resources to be the least on the premise of satisfying the average response time required by a user. According to the method, the resource allocation can be carried out on the analysis process with requests arriving continuously, the average response time of the system is estimated by employing a queuing theory; the response time is estimated relatively accurately, an allocable server solution set of each component is estimated according to the queuing theory, and a quasi-optimal solution is obtained by employing a heuristic algorithm.

Description

technical field [0001] The present invention relates to the technical field of cloud resource configuration optimization, in particular to a cloud resource configuration optimization method oriented to an elastic analysis process. Background technique [0002] In recent years, the popularization and development of cloud computing and mobile Internet have led to the generation of massive data in different fields, such as bioinformatics, social networks, and intelligent transportation systems. The analysis and processing of these massive data has become a research hotspot. Effective analysis of these data can make decision-making more accurate and faster. Generally speaking, data analysis is a computationally intensive application. For data analysis tasks that arrive continuously, if you want to process all requests in time, you must allocate enough resources to meet the highest load. However, this will result in a waste of idle resources when the load request is relatively...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50G06F9/455
CPCG06F9/45558G06F9/5027G06F9/5072G06F2009/4557
Inventor 曹健姚艳
Owner SHANGHAI JIAO TONG UNIV
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