WO2019035499A1 - Système et procédé de traitement de service saas hybride dans une plateforme de service saas hybride fondée sur la demande des utilisateurs utilisant une mise à l'échelle automatique - Google Patents

Système et procédé de traitement de service saas hybride dans une plateforme de service saas hybride fondée sur la demande des utilisateurs utilisant une mise à l'échelle automatique Download PDF

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Publication number
WO2019035499A1
WO2019035499A1 PCT/KR2017/008992 KR2017008992W WO2019035499A1 WO 2019035499 A1 WO2019035499 A1 WO 2019035499A1 KR 2017008992 W KR2017008992 W KR 2017008992W WO 2019035499 A1 WO2019035499 A1 WO 2019035499A1
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saas
service
virtual machine
virtual machines
combined service
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PCT/KR2017/008992
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English (en)
Korean (ko)
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김명진
조철용
김영현
오동휘
구원본
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주식회사 이노그리드
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Publication of WO2019035499A1 publication Critical patent/WO2019035499A1/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
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
    • 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 embodiment relates to a SaaS combined service processing system and method for simultaneously processing a plurality of SaaS combined services in a user demand based SaaS (Software as a service) combined service platform (SASP).
  • SaaS Software as a service
  • SASP combined service platform
  • SaaS Software as a Service
  • SaaS is a technology that allows vendors to provide software services to a large number of customers on a specific software platform, and services such as Twitter, Facebook, gmail, and icloud are examples of SaaS. Therefore, SaaS means making the necessary software available online through the Internet.
  • the present invention describes a software as a service SaaS (SaaS Aggregation Service Platform) based on user demand, and can efficiently utilize resources required for processing a SaaS combining service through automatic scaling SaaS combined service processing system and method therefor.
  • SaaS SaaS Aggregation Service Platform
  • a SaaS combined service processing system for processing a SaaS combined service in a user demand based SaaS (SaaS Aggregation Service Platform)
  • a monitoring unit for monitoring processing status information on a SaaS combining service currently being processed by the calculating unit and storing the processing status information in a database, a SaaS combining service processing status information
  • An automatic scaling unit for adjusting the number of virtual machines to be executed in the calculation unit and the resources used by each virtual machine based on the number of virtual machines executed by the automatic scaling unit, SaaS combining service, which is scheduled to be processed on the basis of Wherein the virtual machine runs one or more SaaS combined service execution processes and one of the running processes is a total SaaS combined service execution processes running in the virtual machine,
  • a processing status reporter module for transmitting SaaS combined service processing status information collected from the execution processes to the monitoring unit.
  • Another embodiment is a method for processing a SaaS combined service in a user demand based SaaS (Software as a service) combined service platform (SASP), comprising the steps of: An automatic scaling step of adjusting the number of virtual machines executed to process the SaaS combining service based on the SaaS combined service processing status information and the resources used by each virtual machine, And a distribution step of distributing a SaaS binding service to be processed based on information on resources used by each virtual machine to one of the virtual machines, wherein the virtual machine drives one or more SaaS binding service execution processes,
  • One of the execution processes is an overall SaaS
  • the sum and the master process for managing service establishment process there is provided a method characterized in that it comprises the operation status reporter module that functions to send the SaaS combined service operation status information collected from the process execution part the monitoring.
  • FIG. 1 is a diagram illustrating an overall configuration of a user demand based SASP according to an embodiment of the present invention.
  • FIG. 2 is a diagram illustrating an overall configuration of a SaaS combined service processing system according to an embodiment of the present invention.
  • FIG. 3 is a diagram illustrating a process of processing a SaaS combining service in a virtual machine according to an embodiment of the present invention.
  • FIG. 4 is a flowchart illustrating a method of processing a SaaS combining service according to an embodiment of the present invention.
  • first, second, A, B, (a), and (b) may be used. These terms are intended to distinguish the constituent elements from other constituent elements, and the terms do not limit the nature, order or order of the constituent elements.
  • SaaS combined service means that SaaS that is provided independently is combined with each other and provides customized services to general users.
  • SaaS combining service can be largely composed of a trigger event indicating a condition under which the SaaS combining service is executed and an action event defining an operation pattern for one or more SaaS executed in a situation where the trigger event is satisfied.
  • the trigger event and the action event described above may be expressed by a predefined SaaS combined service description language.
  • a regular user might want to have a service that automatically posts the content of his or her post to his / her twitter when another user clicks "likes" on his / her post on facebook.
  • the trigger event is that another user clicks "Like”
  • the action event is that the contents of the post where "Like” is clicked are tweeted to the twitter.
  • SaaS Aggregation Service Platform SASP
  • a SaaS combination service that meets the user's demand by combining user's personal information, current situation, and previous service usage history, and recommend a new SaaS combination service User demand-based SaaS combined service platform is needed.
  • FIG. 1 is a diagram illustrating an overall configuration of a user demand based SASP according to an embodiment of the present invention.
  • a whole software as a service (SaaS) aggregation service platform includes a SASP integrated authentication server 100, a SASP management node 110, a cloud event distribution cluster 120, A SaaS combined service processing system 130, a big data analysis system 140, a Rule Matrix DB server 150, a SASP service DB server 160, a SaaS recommendation engine server 170, and a binding history DB server 180 .
  • the SASP integrated authentication server 100 may perform a role of integrally managing authentication procedures for the user 10, the SaaS provider 20, and the operator 30 in the SASP.
  • the SASP integrated authentication server 100 can access each SaaS only by performing one integrated authentication on the SASP without having to perform authentication for each SaaS constituting the SaaS combining service to be used by the user 10 .
  • the SASP integrated authentication server 100 supports registering the SaaS provided by the SaaS provider 20 in the SASP so that the user 10 can use the SaaS. If an unauthorized SaaS can be performed when a SaaS combined service is performed, a user using SASP may be seriously damaged by SaaS operating malicious code such as Ransomware. Therefore, when the SaaS combining service is performed, all SaaS providers must register their own SaaS with the SASP to perform only the SaaS provided by the SaaS provider authenticated by the SASP.
  • the SASP integrated authentication server 100 also supports authentication of the operator 30 for authorization to manage the entire registered user 10, the SaaS provider 20 and the SaaS combining service 30. [ And the SASP integrated authentication server 100 supports performing an authentication operation for each registered SaaS 40. [
  • the SASP management node 110 can manage the overall operation of the SASP.
  • the SASP management node 110 supports the authorized user or authenticated SaaS provider through the SASP integrated authentication server 100 to register / modify / delete the SaaS combination service.
  • the SASP management node 110 can confirm whether a matching condition for a rule in which a specific SaaS combining service is executed is satisfied based on a rule stored in the Rule Matrix DB server 150.
  • a rule is defined as a definition of which SaaS combination service is recommended to a user according to the user's situation information (user's personal information, real-time information such as the user's current location).
  • the SASP management node 110 may store or load data related to the management task of the SASP in the SASP service DB server 160.
  • the SASP service DB server 160 may store the information about the user, the SaaS combining service, and the registered SaaS generated in the process of operating the SASP, and may provide the requested information if the request is made by the external system.
  • the SASP management node 110 may receive a SaaS combining service to be recommended to the user from the SaaS recommendation engine server 170 based on the personal information and the situation information of the user.
  • SaaS recommendation engine server 170 analyzes SaaS recommendation engine based on data input by the user at the time of subscription, data entered while SaaS provider registers SaaS in SASP, and real-time information (location, weather, etc.) SaaS combine services can be recommended.
  • the SASP management node 110 transmits to the cloud event distribution cluster 120 an event message for processing the SaaS combined service requested by the user or the SaaS combined service recommended to the user based on the personal information and the situation information of the user It can be delivered every fixed cycle.
  • the cloud event dispatch cluster 120 may store the binding completion confirmation information for the SaaS binding service in the binding history DB server 180 and instruct the SaaS binding service processing system 130 to process the actual SaaS binding service have.
  • Binding completion confirmation information is information on which SaaS combining service is used by the user, and records SaaS combining service utilization records of users having similar characteristics, so that SaaS combining service, which is similar to other users, As shown in FIG.
  • the SaaS combined service processing system 130 may execute a virtual machine that performs the SaaS combining service and perform a function of allowing the worker process on the virtual machine to actually process the SaaS combining service.
  • the SaaS combined service processing system 130 may transmit the result of performing the SaaS combined service to the Big Data Analysis System 140.
  • the Big Data Analysis System 140 may perform a Big Data Analysis on the processed SaaS Combined Services results.
  • the big data analysis system 140 creates a virtual machine cluster composed of one or more virtual machines to perform a big data analysis based on the processing result of a large amount processed in the SaaS combined service processing system 130, To automatically distribute the big data analysis tool selected by the administrator.
  • FIG. 2 is a diagram illustrating an overall configuration of a SaaS combined service processing system according to an embodiment of the present invention.
  • the SaaS combined service processing system may include a calculation unit 210, a monitoring unit 220, an automatic scaling unit 230, and a load balancing unit 240.
  • the calculation unit 210 may execute one or more virtual machines that process the SaaS combining service.
  • the virtual machine may receive a SaaS combined service processing request and direct the SaaS combined service execution process running on the virtual machine to process the SaaS combined service described above.
  • the SaaS combinatorial service execution process that has received the instruction actually processes the action event of the SaaS combinatorial service and processes the SaaS combinatorial service.
  • a request to process a SaaS combined service from multiple users can occur at the same time. Therefore, a virtual machine must handle a plurality of SaaS concatenation services at the same time, but there is a limit to the number of CPU cores that a virtual machine can use at a specific time. Therefore, if it is impossible to process the SaaS combined service processing request received by the currently executing virtual machine, a SaaS combined service processing request in the new virtual machine should be performed. Therefore, in the calculation unit 210, a plurality of virtual machines can be executed.
  • a threshold value of system resources usable for each virtual machine can be set at the time of creation of the virtual machine. For example, when a virtual machine is created, the virtual machine can be configured to use up to four CPU cores, 8 GB of memory, and 100 GB of disk space.
  • the monitoring unit 220 may monitor the processing status information of the SaaS combining service being processed by the calculating unit 210 and store the information in a database.
  • the monitoring unit 220 can monitor the SaaS combined service processing status information from each virtual machine executed in the calculation unit 210.
  • the SaaS combined service processing status information may include the CPU usage and network usage of each SaaS combined service execution process, the number of SaaS combination services currently being processed, and the CPU usage, network usage, and disk usage of each virtual machine.
  • the SaaS combined service processing status information may include the following information.
  • the monitoring unit 220 may store the collected SaaS combined service processing status information in the monitoring database 225.
  • the monitoring database 225 may provide the collected SaaS combined service processing status information to the external system.
  • the automatic scaling unit 230 may adjust the number of virtual machines to be executed in the calculation unit and the resources used by each virtual machine based on the SaaS combined service processing status information.
  • the automatic scaling unit 230 may obtain SaaS combined service processing status information from the monitoring database 225. [ The automatic scaling unit 230 may adjust the number of virtual machines executed by the calculation unit 210 and the resources used by the respective virtual machines according to preset automatic scaling conditions.
  • the resources used by the virtual machine means system resources such as CPU, memory, network, and disk.
  • the automatic scaling unit 230 may calculate the number of virtual machines to be executed in the calculation unit when the total number of SaaS combining service execution processes executed in the calculation unit is equal to or greater than a predetermined number of threshold execution processes .
  • the automatic scaling unit 230 may define the following parameters, and then combine them to generate a condition.
  • Threshold value for checking whether the condition is satisfied or not
  • Another example is to check the CPU usage of each virtual machine every two minutes and delete one of the existing virtual machines when the maximum value of CPU usage is less than 30% in three consecutive times. .
  • the load balancer 240 performs an operation of distributing the actual SaaS combining service to the virtual machines based on the items adjusted by the automatic scaling unit 230.
  • the automatic scaling unit 230 directly instructs the calculation unit 210 to expand / reduce the number of virtual machines executed in the calculation unit 210.
  • the load distributing unit 240 distributes the SaaS combining service scheduled to be processed based on the number of virtual machines adjusted by the automatic scaling unit 230 and the information about the resources used by the respective virtual machines to the virtual machine Lt; / RTI >
  • the load balancer 240 can establish a connection with each virtual machine in order to deliver a SaaS combined service processing request to each virtual machine executed in the calculator 210.
  • the load distributing unit 240 distributes the SaaS combining service to one of the virtual machines based on the information received from the automatic scaling unit 230. That is, the load distributing unit 240 plays a role of actually executing the instruction instructed by the automatic scaling unit 230.
  • the load distributing unit 240 distributes only the SaaS combining service to be newly processed, and does not distribute the SaaS combining service already processed in the virtual machine to another virtual machine.
  • FIG. 3 is a diagram illustrating a process of processing a SaaS combining service in a virtual machine according to an embodiment of the present invention.
  • each virtual machine can run one or more SaaS combined service execution processes.
  • the calculation unit 210 may set one of the virtual machines to be executed as a master virtual machine. For example, the calculation unit 210 may set the first virtual machine among the virtual machines as a master virtual machine. Also, when the master virtual machine is deleted, the calculation unit 210 can reset the virtual machine having the fastest creation time among the remaining virtual machines to the master virtual machine.
  • the master virtual machine can control to perform only one SaaS combined service execution process for each CPU core on each virtual machine. If multiple SaaS combined service execution processes share a single CPU core, there is a load in the process switching process, and the processing time of the entire SaaS combined service execution process increases.
  • the virtual machine may set one of the SaaS combined service execution processes as a master process.
  • the master process is one of SaaS combined service execution processes, and can also manage the entire SaaS combined service execution processes running on the virtual machine, while also performing the processing of the SaaS combined service actually.
  • the SaaS combinatorial service execution process on the virtual machine can play a role in actually handling the SaaS combinatorial service.
  • each SaaS combined service execution process can execute only one SaaS combining service at a time in order to process the service assigned to itself as quickly as possible.
  • Each virtual machine includes a processing status reporter module for collecting SaaS combined service processing status information from the SaaS combined service execution process running on each virtual machine and transmitting the collected SaaS combined service processing status information to the monitoring unit 220 can do.
  • the SaaS combined service processing status information includes the CPU usage amount and the network usage amount of each SaaS combined service execution process, the number of SaaS combining services currently processed, and the CPU usage amount, network usage amount, and disk usage amount of each virtual machine as described above can do.
  • N virtual machines from the virtual machine 1 to the virtual machine N can be executed.
  • the above-mentioned master virtual machine is referred to as virtual machine 1.
  • SaaS combined service execution process # 1 which is one of the processes, becomes the master process.
  • the SaaS combined service # 1 which is a service combining facebook and gmail, is distributed to the virtual machine 1
  • the SaaS combined service execution process # 2 which is one of the SaaS combined service execution processes of the virtual machine 1, have.
  • SaaS combined service execution process # 4 which is one of the processes, becomes the master process.
  • the SaaS combined service # 2 which is a service combining gmail and twitter, is distributed to the virtual machine 2
  • the SaaS combined service execution process # 5 which is one of the SaaS combined service execution processes of the virtual machine 2 have.
  • one or more SaaS combined service execution processes may operate in the virtual machine N.
  • SaaS combined service execution process #N which is one of the processes, is a master process, and the remaining processes, SaaS combined service execution process # (N + 1), etc., are managed by the master process SaaS combined service execution process #N.
  • SaaS combined service # 3 which is a service combining facebook and icloud, is allocated to virtual machine 3
  • SaaS combined service execution process # (N + 1) which is one of SaaS combined service execution processes of virtual machine 3, Can be performed.
  • FIG. 4 is a flowchart illustrating a method of processing a SaaS combining service according to an embodiment of the present invention.
  • a method of processing a SaaS combined service in a user demand based SaaS (Software as a service) combined service platform monitors a process status information of a SaaS combined service and stores it in a database (S410).
  • the monitoring unit 220 of the SaaS combined service processing system receives the SaaS combined service processing status information from the processing status reporter module of each virtual machine executed in the calculating unit 210 and stores the SaaS combined service processing status information in the monitoring database 225 .
  • the method may include an automatic scaling step of adjusting the number of virtual machines executed to process the SaaS combining service based on the SaaS combined service processing status information and the resources used by each virtual machine (S420) .
  • the automatic scaling unit 230 of the SaaS combined service processing system can receive the SaaS combined service processing status information from the monitoring database 225 instead of receiving the SaaS combined service processing status information directly from the monitoring unit 220. At this time, the automatic scaling unit 230 may periodically collect the SaaS combined service processing status information in the monitoring database 225 at predetermined time intervals.
  • the automatic scaling unit 230 can adjust the number of virtual machines executed to process SaaS combining service according to predefined automatic scaling conditions and the resources used by each virtual machine.
  • the condition of the automatic scaling when the total number of SaaS combining service execution processes executed by the calculating unit 210 becomes equal to or greater than the preset number of threshold execution processes, the virtual machine Can be increased.
  • a specific parameter may be defined as described above, and then a condition may be created by combining the parameters.
  • the method may include a distribution step of distributing a SaaS combination service to one of the virtual machines to be processed based on the number of the adjusted virtual machines and information about resources used by each virtual machine at step S430.
  • the SaaS combining service which is scheduled to be processed based on the number of virtual machines adjusted by the automatic scaling unit 230 and the information about the resources used by the respective virtual machines, To one of the virtual machines executed in the calculation unit 210.
  • the virtual machine that has been allocated the SaaS combining service can drive one or more SaaS combined service executing processes as described above.
  • the calculation unit 210 can set one of the virtual machines to be executed as a master virtual machine, and the master virtual machine can perform control so that only one SaaS combined service execution process is performed per one CPU core .
  • the SaaS combining service execution process executes only one SaaS combining service at a time in order to process the service allocated to the user as quickly as possible.

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Abstract

La présente invention concerne un traitement de service de logiciel à la demande (SaaS) hybride fondé sur la demande des utilisateurs, et fournit un système de traitement de service SaaS hybride comprenant : une unité de calcul pour exécuter une ou plusieurs machines virtuelles pour traiter un service SaaS hybride ; une unité de surveillance pour surveiller des informations d'état de traitement en ce qui concerne un service SaaS hybride qui est actuellement traité par l'unité de calcul et pour les stocker dans une base de données ; une unité de mise à l'échelle automatique pour coordonner le nombre de machines virtuelles exécutées par l'unité de calcul et les ressources utilisées par les machines virtuelles respectives sur la base des informations d'état de traitement de service SaaS hybride ; et une unité de distribution de charge pour distribuer un service SaaS hybride qui est échéant pour un traitement à l'une des machines virtuelles exécutées par l'unité de calcul sur la base des informations concernant le nombre de machines virtuelles et les ressources utilisées par les machines virtuelles respectives qui sont coordonnés par l'unité de mise à l'échelle automatique, la machine virtuelle faisant tourner un ou plusieurs processus d'exécution de service SaaS hybride, l'un des processus d'exécution étant un processus maître qui gère la totalité des processus d'exécution de service SaaS hybride tournant sur la machine virtuelle, et comportant un module de rapport d'état pour traiter une fonction de transmission, à l'unité de surveillance, d'informations d'état de traitement de service SaaS hybride qui sont collectées auprès de processus exécutés.
PCT/KR2017/008992 2017-08-17 2017-08-18 Système et procédé de traitement de service saas hybride dans une plateforme de service saas hybride fondée sur la demande des utilisateurs utilisant une mise à l'échelle automatique WO2019035499A1 (fr)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110764873A (zh) * 2019-10-21 2020-02-07 深圳金蝶账无忧网络科技有限公司 一种虚拟机资源管理方法、系统及相关设备
KR20220061362A (ko) * 2020-11-06 2022-05-13 한국전자기술연구원 러기드 환경에서의 엣지 서버 시스템 관리 및 제어 방법

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110213686A1 (en) * 2010-02-26 2011-09-01 James Michael Ferris Systems and methods for managing a software subscription in a cloud network
KR20120063499A (ko) * 2009-09-30 2012-06-15 알까뗄 루슨트 엔터프라이즈 네트워크에서 할당된 클라우드 자원의 동적 로드 밸런싱 및 스케일링
KR20150083713A (ko) * 2014-01-10 2015-07-20 삼성전자주식회사 자원 관리를 위한 전자 장치 및 방법
KR20150095015A (ko) * 2014-02-12 2015-08-20 한국전자통신연구원 가상 서버를 관리하는 장치 및 이를 이용하는 부하 분산 방법
US20160094410A1 (en) * 2014-09-30 2016-03-31 International Business Machines Corporation Scalable metering for cloud service management based on cost-awareness

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20120063499A (ko) * 2009-09-30 2012-06-15 알까뗄 루슨트 엔터프라이즈 네트워크에서 할당된 클라우드 자원의 동적 로드 밸런싱 및 스케일링
US20110213686A1 (en) * 2010-02-26 2011-09-01 James Michael Ferris Systems and methods for managing a software subscription in a cloud network
KR20150083713A (ko) * 2014-01-10 2015-07-20 삼성전자주식회사 자원 관리를 위한 전자 장치 및 방법
KR20150095015A (ko) * 2014-02-12 2015-08-20 한국전자통신연구원 가상 서버를 관리하는 장치 및 이를 이용하는 부하 분산 방법
US20160094410A1 (en) * 2014-09-30 2016-03-31 International Business Machines Corporation Scalable metering for cloud service management based on cost-awareness

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110764873A (zh) * 2019-10-21 2020-02-07 深圳金蝶账无忧网络科技有限公司 一种虚拟机资源管理方法、系统及相关设备
CN110764873B (zh) * 2019-10-21 2022-09-27 深圳金蝶账无忧网络科技有限公司 一种虚拟机资源管理方法、系统及相关设备
KR20220061362A (ko) * 2020-11-06 2022-05-13 한국전자기술연구원 러기드 환경에서의 엣지 서버 시스템 관리 및 제어 방법
KR102548709B1 (ko) * 2020-11-06 2023-06-28 한국전자기술연구원 러기드 환경에서의 엣지 서버 시스템 관리 및 제어 방법

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