A multi-workflow resource supply method under virtualized container resources

A technology for virtualizing containers and workflows, applied in the field of cloud computing, can solve the problems of inability to allocate workflow tasks and coordinate virtualized resource supply, and achieve the effect of improving resource utilization.

Active Publication Date: 2021-02-19
GUANGDONG UNIV OF PETROCHEMICAL TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing cloud workflow scheduling either focuses on workflow task allocation under fixed virtualization resources, or focuses on elastic resource supply under workflow load changes, or focuses on how to integrate existing workflow management systems into cloud platforms In this case, workflow task allocation and virtualization resource supply cannot be coordinated with each other

Method used

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  • A multi-workflow resource supply method under virtualized container resources
  • A multi-workflow resource supply method under virtualized container resources

Examples

Experimental program
Comparison scheme
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Embodiment

[0025] The system model of multi-workflow resource supply under virtualized container resources is as follows: figure 1 As shown, the supply at the resource level is to map the needs of users to submit workflow tasks to specific resources, so that the performance of the application is optimal, and the utilization rate of resources is also improved as much as possible. The workflow in the cloud environment is composed of a series of subtasks. At this time, the resource level supply, first of all, is how to select the appropriate available resources to complete the creation of the virtual unit, which is the generation of the virtual unit; the second is how to reduce the activation The number of physical machines and the occupation of network bandwidth, that is, the placement of virtual units.

[0026] This embodiment adopts the following technical solutions to achieve the effect of mutual coordination and matching between resource supply and workflow tasks:

[0027] A method fo...

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Abstract

The invention discloses a multi-workflow resource supply method under virtualized container resources, which utilizes reinforcement learning to schedule workflows, supply resources, define resource utility indicators U, and establish tasks running in container clusters at each resource scheduling time and the supply and demand relationship between virtualized container resources, the design of the reward function meets the requirements of multi-workflow resource generation with the container cluster as the granularity: it is necessary to ensure that the number and type of container units in the container cluster conform to the running process of the cloud workflow, It is also necessary to prevent workflows with different QoS requirements from violating service level agreements and improve the resource utilization of the entire container cluster. The status information of tasks in each container cluster can be obtained in real time, and workflow task allocation and virtualization resource supply can be coordinated with each other.

Description

technical field [0001] The invention relates to the field of cloud computing, in particular to a multi-workflow resource supply method under virtualized container resources. Background technique [0002] It is very difficult to coordinate adaptive scheduling of workflow tasks and virtualized resources in the ever-changing cloud computing environment. For example, the data centers of Amazon, IBM, Microsoft, and Yahoo all have hundreds of thousands of servers, and the number of servers owned by Google even exceeds 1 million. After the virtualization of various physical resources, the number is even larger, and the physical nodes and virtualization units are down. , Dynamic join and revoke, etc. occur from time to time, and the management is technically difficult and complex. As another example, taking the multi-tier Web service workflow as an example, the law of load changes caused by emergencies is often unpredictable. [0003] From the perspective of task optimization allo...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L29/08G06F9/455G06F9/48
CPCG06F9/45558G06F9/4881H04L67/10H04L67/1023
Inventor 李棕钟积海崔得龙彭志平柯文德李启锐
Owner GUANGDONG UNIV OF PETROCHEMICAL TECH
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