WO2021095943A1 - Procédé pour placer un conteneur en considération d'un profil de service - Google Patents

Procédé pour placer un conteneur en considération d'un profil de service Download PDF

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Publication number
WO2021095943A1
WO2021095943A1 PCT/KR2019/015652 KR2019015652W WO2021095943A1 WO 2021095943 A1 WO2021095943 A1 WO 2021095943A1 KR 2019015652 W KR2019015652 W KR 2019015652W WO 2021095943 A1 WO2021095943 A1 WO 2021095943A1
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WIPO (PCT)
Prior art keywords
container
node
service profile
consideration
algorithm
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PCT/KR2019/015652
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English (en)
Korean (ko)
Inventor
진성근
이재륜
김태영
김태현
전인걸
하수정
Original Assignee
대구대학교 산학협력단
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Priority to PCT/KR2019/015652 priority Critical patent/WO2021095943A1/fr
Publication of WO2021095943A1 publication Critical patent/WO2021095943A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]

Definitions

  • the present invention relates to a method of disposing a container in consideration of a service profile when disposing a container to a node in the field of cloud computing.
  • Virtual machine-based computer virtualization technology for cloud computing environments is a technology that virtualizes the computer's hardware resources such as CPU, memory, storage devices, etc. to create an environment so that applications can be operated. It is widely used in products or technologies such as VmWare and VirtualBox. It is being utilized. However, since the virtual machine-based virtualization technology virtualizes hardware resources of a computer, there is a problem in that performance rapidly deteriorates when an application with a large amount of resource utilization runs and performs a task.
  • a container technology has been developed that directly utilizes resources provided by a computer by reducing the weight of a virtual environment in which an application runs. Unlike traditional virtual machines, container technology uses much less resources and shares the host's kernel. Above all, since the CPU is not virtualized, additional operations for CPU operation are much more advantageous than virtual machine-based virtualization technology. Therefore, current technology development and development is progressing from a virtual machine-based virtualization technology to a container-based virtualization technology.
  • Kubernetes developed by Google as an operating environment tool for container deployment and management, is now a de facto standard technology.
  • Kubernetes monitors the utilization of resources such as CPU utilization, memory utilization, and disk I/O, and when a new container deployment request comes in, it selects the most optimal computer node based on the current resource utilization so that the container can be deployed.
  • resources such as CPU utilization, memory utilization, and disk I/O
  • various algorithms can be used to select an optimal computer node.
  • the conventional method has the following problems.
  • container A provides a video service.
  • the video service does not require real-time characteristics, but it must provide an uninterrupted video service by securing an appropriate level of bandwidth.
  • the B container can provide a service that controls the robot in real time. At this time, in order to secure real-time characteristics, a response to a request must be made in a very fast time.
  • the C container provides office services such as Word, real-time characteristics are not important, and an appropriate level of bandwidth is not required. As such, various levels of service characteristics must be provided through containers, but there is a problem that the current container arrangement method does not take this into account.
  • the embodiment of the present invention was devised to solve the above problems, and in consideration of the properties of the service provided by the container in a cloud computing environment, a service capable of placing a container on an optimal computer node and effectively managing the computer node We would like to provide a container arrangement method considering the profile.
  • a service profile is defined according to a property of a service provided through the container, A first step of classifying; A second step of calculating a scheduling score of each node by reflecting a weight according to a service profile to each execution score for a plurality of algorithms for each node according to a predetermined equation, and summing them according to a predetermined equation; And a third step of distributing the container to the node that has obtained the highest score.
  • the equation is Is, where Is the scheduling score of node n for service profile i, Is the weight factor of algorithm k for service profile i, Denotes the execution score of algorithm k for node n.
  • the execution score may be calculated by inputting the resource utilization amount of the node measured immediately before each algorithm is executed into the algorithm.
  • the weight factor may be calculated in consideration of the service profile and the algorithm.
  • the container in the container arrangement method in consideration of a service profile according to an embodiment of the present invention, can be placed on an optimal computer node in consideration of the properties of the service provided by the container, so that the computer node can be effectively managed in a cloud computing environment. .
  • FIG. 1 is a flowchart of a container arrangement method in consideration of a service profile according to an embodiment of the present invention.
  • FIG. 2 is a diagram schematically showing the flow of FIG. 1;
  • FIG. 1 is a flowchart illustrating a container arrangement method in consideration of a service profile according to an embodiment of the present invention
  • FIG. 2 is a diagram schematically illustrating the flow of FIG. 1.
  • a method of arranging a container in consideration of a service profile according to an embodiment of the present invention includes a first step (S10) to a third step (S30).
  • a container means an isolated space between an application and the environment in which it runs.
  • the resources of the operating system are shared, so that as many resources as necessary for the execution of the application can be allocated, the resources of the entire server can be used efficiently.
  • the arrangement of containers means scheduling corresponding to one of various management tasks for a plurality of containers. This means automatically placing containers on the most optimal node.
  • the method of arranging containers operated in a container-based cloud computing environment is to monitor the resource usage (or usage) of each resource such as CPU, memory, and storage devices in real time, and based on this, the optimal computer node is determined.
  • the method of selection This is accomplished by running a plurality of algorithms on each node and then summing the execution points measured for each node.
  • the first step is a step of defining and classifying a service profile according to the attribute of the service provided through the container.
  • the attribute of the service is considered most importantly when a container provides a service. It refers to the element to be. This means that the required resources vary according to the properties of the service.
  • the service profile according to the attribute of the service means, for example, delay sensitive, computationality (CPU centric), an amount of allocated memory, and the like. A plurality of such service profiles can be defined.
  • the second step is to calculate the scheduling score of the node by reflecting the weight according to the service profile to each execution score for a plurality of algorithms according to a preset equation and summing them when there is a request for placement of a container. This is the step. (S20)
  • Is the scheduling score of node n for service profile i Is the weight factor of algorithm k for service profile i, Denotes the execution score of algorithm k for node n.
  • m means the number of algorithms.
  • Algorithm 1 is an algorithm that gives a high score to a node that provides computationality
  • Algorithm 2 is an algorithm that gives a high score to a node that provides low latency
  • Algorithm 3 is an algorithm that gives a high score to a node with a large amount of allocated memory. It is an algorithm that gives a score.
  • the scheduling score of node 1 can be calculated as follows using the above equation.
  • the scheduling score of node 2 is calculated as follows.
  • the weight factor of Algorithm 2 Will have a relatively high number.
  • the weight factor of Algorithm 1 ( ) and the weight factor of Algorithm 3 ( ) Will have a relatively low number.
  • container a can be placed in node 2.
  • the execution score of the algorithm is calculated by inputting the resource utilization amount of the node measured just before each algorithm is executed. That is, the data input to the algorithm uses the measured value at the start of the algorithm from among the resource utilization of each node measured in real time.
  • a weight factor (weight) is calculated by considering a service profile and an algorithm, respectively. That is, the weight factor is calculated in consideration of the properties of the service and the design purpose of the algorithm. In this way, the weight factor differs in a value applied for each algorithm according to the service profile. On the other hand, it is preferable to form a set after the weight factor is set in advance.
  • the second step before calculating the scheduling score of each node, it may further include filtering a node that does not meet a preset criterion among the nodes. For example, a certain filtering criterion may be set, such as when it is difficult to place a container any more because the current resource utilization among computer nodes exceeds a certain level, or when the computer node is in a state in which networking is not possible. And, in the case of such an inappropriate node, the scheduling score is not calculated by excluding it in advance.
  • the container is placed on the node that has obtained the highest score (S30). That is, the node that has obtained the highest score among the scheduling scores of each node calculated in the second step is selected and the container is placed.

Abstract

La présente invention concerne un procédé pour placer un conteneur sur un nœud optimal dans un environnement infonuagique à base de conteneurs et, plus particulièrement, concerne un procédé pour placer un conteneur en considération d'un profil de service, le procédé comprenant : une première étape consistant à définir et à classifier un profil de service en fonction d'un attribut d'un service fourni par le biais d'un conteneur; une deuxième étape consistant à, lorsqu'il y a une demande de placement d'un conteneur, calculer un score d'ordonnancement de chaque nœud par un schéma consistant à appliquer un poids en fonction du profil de service à des scores d'exécution pour de multiples algorithmes respectifs pour chaque nœud, puis à additionner les scores d'exécution appliqués au poids conformément à une équation pré-configurée; et une troisième étape consistant à placer le conteneur sur un nœud ayant obtenu le score le plus élevé.
PCT/KR2019/015652 2019-11-15 2019-11-15 Procédé pour placer un conteneur en considération d'un profil de service WO2021095943A1 (fr)

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Cited By (2)

* Cited by examiner, † Cited by third party
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CN114265704A (zh) * 2022-03-03 2022-04-01 环球数科集团有限公司 一种基于凸优化的混合容器云调度系统
KR20220098636A (ko) * 2021-01-04 2022-07-12 네이버 주식회사 페이지 캐시를 사용하는 컨테이너의 스케줄링을 위한 방법, 시스템, 및 컴퓨터 판독가능한 기록 매체

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WO2015049789A1 (fr) * 2013-10-04 2015-04-09 株式会社日立製作所 Système de gestion de ressources et procédé de gestion de ressources
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US20170257424A1 (en) * 2016-03-04 2017-09-07 Bladelogic, Inc. Provisioning of containers for virtualized applications
US9794136B1 (en) * 2015-01-21 2017-10-17 Pivotal Software, Inc. Distributed resource allocation
US20190102226A1 (en) * 2017-09-30 2019-04-04 Oracle International Corporation Dynamic node rebalancing between container platforms

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KR20150043377A (ko) * 2012-08-07 2015-04-22 어드밴스드 마이크로 디바이시즈, 인코포레이티드 클라우드 컴퓨팅 시스템을 튜닝하는 시스템 및 방법
WO2015049789A1 (fr) * 2013-10-04 2015-04-09 株式会社日立製作所 Système de gestion de ressources et procédé de gestion de ressources
US9794136B1 (en) * 2015-01-21 2017-10-17 Pivotal Software, Inc. Distributed resource allocation
US20170257424A1 (en) * 2016-03-04 2017-09-07 Bladelogic, Inc. Provisioning of containers for virtualized applications
US20190102226A1 (en) * 2017-09-30 2019-04-04 Oracle International Corporation Dynamic node rebalancing between container platforms

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20220098636A (ko) * 2021-01-04 2022-07-12 네이버 주식회사 페이지 캐시를 사용하는 컨테이너의 스케줄링을 위한 방법, 시스템, 및 컴퓨터 판독가능한 기록 매체
KR102456005B1 (ko) 2021-01-04 2022-10-18 네이버 주식회사 페이지 캐시를 사용하는 컨테이너의 스케줄링을 위한 방법, 시스템, 및 컴퓨터 판독가능한 기록 매체
CN114265704A (zh) * 2022-03-03 2022-04-01 环球数科集团有限公司 一种基于凸优化的混合容器云调度系统
CN114265704B (zh) * 2022-03-03 2022-05-17 环球数科集团有限公司 一种基于凸优化的混合容器云调度系统

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