WO2014101534A1 - Profit maximization scheduling method and system for cloud computing - Google Patents

Profit maximization scheduling method and system for cloud computing Download PDF

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WO2014101534A1
WO2014101534A1 PCT/CN2013/085450 CN2013085450W WO2014101534A1 WO 2014101534 A1 WO2014101534 A1 WO 2014101534A1 CN 2013085450 W CN2013085450 W CN 2013085450W WO 2014101534 A1 WO2014101534 A1 WO 2014101534A1
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resource data
scheduling
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revenue
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朱定局
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深圳先进技术研究院
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  • the present invention relates to cloud computing technologies, and more particularly to a scheduling solution and system for cloud computing technologies.
  • the existing cloud computing technology aims to pursue load balancing, and such a cloud computing resource scheduling method cannot meet the needs of many commercial application users.
  • a scheduling method for cloud computing comprising the steps of: obtaining a step of obtaining a plurality of resource data; calculating a step of separately calculating profit of the plurality of resource data according to the plurality of resource data; comparing the steps of comparing the profits corresponding to the plurality of resource data Size, obtaining the preferred resource data corresponding to the maximum profit; and scheduling step of scheduling the cloud computing resource according to the preferred resource data.
  • the resource data includes revenue and cost; in the calculating step, the profit is equal to the revenue minus the cost.
  • the revenue is equal to the amount of tasks completed, and the cost is equal to the number of cloud computing nodes that need to be used.
  • the revenue is equal to the completed task amount multiplied by the weight k1
  • the cost is equal to the number of cloud computing nodes to be used multiplied by the weight K2.
  • the weight K1 and the weight K2 are taken from the training database; K1 is the revenue of the unit task, from the task attribute library; K2 is the cost of the unit cloud computing node, from the cloud computing resource attribute library.
  • a cloud computing scheduling system includes: obtaining a module to obtain a plurality of resource data; a computing module, respectively calculating profit of the plurality of resource data according to the plurality of resource data; comparing the modules, comparing the profit corresponding to the plurality of resource data, The preferred resource data corresponding to the maximum profit is obtained; and the scheduling module performs scheduling of the cloud computing resource according to the preferred resource data.
  • the resource data obtained by the obtaining module includes revenue and cost; the computing module performs the calculation that the profit is equal to the revenue minus the cost.
  • the revenue is equal to the amount of tasks completed, and the cost is equal to the number of cloud computing nodes that need to be used.
  • the revenue is equal to the completed task amount multiplied by the weight k1
  • the cost is equal to the number of cloud computing nodes to be used multiplied by the weight K2.
  • the weight K1 and the weight K2 are taken from the training database; K1 is the revenue of the unit task, from the task attribute library; K2 is the cost of the unit cloud computing node, from the cloud computing resource attribute library.
  • the cloud computing scheduling method and system of the present invention calculates the profit of different scheduling schemes of cloud computing resources by reducing the cost, and then obtains and implements the cloud computing resource scheduling scheme with the largest profit by comparing the profit size.
  • FIG. 1 is a flowchart of a method for scheduling cloud computing according to the present invention
  • FIG. 2 is a schematic block diagram of a scheduling system for cloud computing according to the present invention.
  • the invention utilizes the existing cloud computing resources for scheduling, and implements cloud computing with the goal of obtaining the maximum computing profit as much as possible.
  • the scheduling method of the cloud computing of the present invention includes the following steps:
  • Resource data includes revenue and cost; income and cost have two calculation methods. The first is that the revenue is equal to the completed task quantity, the cost is equal to the number of cloud computing nodes to be used, and the second is that the revenue is equal to the completed task quantity multiplication.
  • the weight k1 the cost is equal to the number of cloud computing nodes to be used multiplied by the weight K2, and the weight K1 and the weight K2 are taken from the relevant industry training database according to different application industries; K1 is the revenue of the unit task, from the task attribute library; K2 is The cost of a unit cloud computing node comes from the cloud computing resource attribute library.
  • S2 a calculation step of separately calculating profit of a plurality of resource data according to the plurality of resource data, and the profit is equal to the income minus the cost.
  • S3 a comparison step of comparing the size of the profit corresponding to the plurality of resource data to obtain the preferred resource data corresponding to the maximum profit.
  • S4 a scheduling step of scheduling cloud computing resources according to the preferred resource data.
  • the scheduling system of the cloud computing of the present invention includes an obtaining module, a computing module, a comparing module, and a scheduling module that are sequentially connected.
  • the acquisition module obtains multiple resource data, including revenue and cost.
  • revenue is equal to the amount of tasks completed
  • the cost is equal to the number of cloud computing nodes to be used
  • the second is that the revenue is equal to the completed task multiplied by the weight k1, and the cost is equal to the need.
  • the number of cloud computing nodes used is multiplied by the weight K2, and the weight K1 and the weight K2 are taken from the relevant industry training database according to different application industries
  • K1 is the revenue of the unit task, from the task attribute library
  • K2 is the cost of the unit cloud computing node, From the cloud computing resource property library.
  • the calculation module separately calculates the profit of the plurality of resource data according to the plurality of resource data.
  • the comparison module compares the size of the profit corresponding to the plurality of resource data, and obtains the preferred resource data corresponding to the maximum profit.
  • the scheduling module performs scheduling of the cloud computing resources according to the preferred resource data.

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Abstract

A scheduling method and system for cloud computing. The method comprises: obtaining a plurality of resource data, respectively computing profits of the plurality of resource data according to the plurality of resource data, comparing profits corresponding to the plurality of resource data, so as to obtain a preferential resource datum corresponding to the maximum profit, and performing scheduling on cloud computing resources according to the preferential resource datum. According to the scheduling method and system for cloud computing of the present invention, the profits of different scheduling solutions of the cloud computing resources are computed by subtracting costs from earnings, and a cloud computing resource scheduling solution with the maximum profit is obtained and implemented by comparing the profits.

Description

云计算的利润最大化调度方法和***  Cloud computing profit maximization scheduling method and system
【技术领域】[Technical Field]
本发明涉及云计算技术，特别是涉及云计算技术的调度解决方法和***。The present invention relates to cloud computing technologies, and more particularly to a scheduling solution and system for cloud computing technologies.
【背景技术】【Background technique】
现有的云计算技术中，在进行资源调度时，主要考虑云计算资源的负载均衡。但在云计算的实际应用中，用户多数想通过云计算资源的调度来获得最大的利润，特别是在云计算的商业应用中，应用资源的利润成为重要的参考因素。In the existing cloud computing technology, when resource scheduling is performed, load balancing of cloud computing resources is mainly considered. However, in the practical application of cloud computing, most users want to obtain the maximum profit through the scheduling of cloud computing resources, especially in the commercial application of cloud computing, the profit of application resources becomes an important reference factor.
因此，现有的云计算技术以追求负载均衡为目的，这样的云计算资源调度方法是无法满足众多商业应用用户的需求的。Therefore, the existing cloud computing technology aims to pursue load balancing, and such a cloud computing resource scheduling method cannot meet the needs of many commercial application users.
【发明内容】[Summary of the Invention]
基于此，有必要针对云计算资源的调度问题，提供一种利润优选的云计算的调度方法和***，通过计算各种云计算调度方案的利润，选择利润大的调度方案，来实施对云计算资源的调度以获得最大的利润。Based on this, it is necessary to provide a profit-optimized cloud computing scheduling method and system for the scheduling problem of cloud computing resources. By calculating the profit of various cloud computing scheduling schemes and selecting a profitable scheduling scheme, the cloud computing is implemented. The scheduling of resources to get the most profit.
一种云计算的调度方法，包括如下步骤：获得步骤，获得多个资源数据；计算步骤，根据多个资源数据分别计算多个资源数据的利润；比较步骤，比较多个资源数据对应的利润的大小，获得最大利润对应的优选资源数据；以及调度步骤，依据优选资源数据进行云计算资源的调度。A scheduling method for cloud computing, comprising the steps of: obtaining a step of obtaining a plurality of resource data; calculating a step of separately calculating profit of the plurality of resource data according to the plurality of resource data; comparing the steps of comparing the profits corresponding to the plurality of resource data Size, obtaining the preferred resource data corresponding to the maximum profit; and scheduling step of scheduling the cloud computing resource according to the preferred resource data.
在其中一个实施例中，获得步骤中，资源数据包括收益和成本；计算步骤中，利润等于收益减去成本。In one of the embodiments, in the obtaining step, the resource data includes revenue and cost; in the calculating step, the profit is equal to the revenue minus the cost.
在其中一个实施例中，收益等于完成的任务量，成本等于需要使用的云计算节点数量。In one of the embodiments, the revenue is equal to the amount of tasks completed, and the cost is equal to the number of cloud computing nodes that need to be used.
在其中一个实施例中，收益等于完成的任务量乘以权重k1，成本等于需要使用的云计算节点数量乘以权重K2。In one of the embodiments, the revenue is equal to the completed task amount multiplied by the weight k1, and the cost is equal to the number of cloud computing nodes to be used multiplied by the weight K2.
在其中一个实施例中，权重K1和权重K2取自训练数据库；K1为单位任务的收益，来自任务属性库；K2为单位云计算节点的成本，来自云计算资源属性库。In one embodiment, the weight K1 and the weight K2 are taken from the training database; K1 is the revenue of the unit task, from the task attribute library; K2 is the cost of the unit cloud computing node, from the cloud computing resource attribute library.
一种云计算的调度***，包括：获得模块，获得多个资源数据；计算模块，根据多个资源数据分别计算多个资源数据的利润；比较模块，比较多个资源数据对应的利润的大小，获得最大利润对应的优选资源数据；以及调度模块，依据优选资源数据进行云计算资源的调度。A cloud computing scheduling system includes: obtaining a module to obtain a plurality of resource data; a computing module, respectively calculating profit of the plurality of resource data according to the plurality of resource data; comparing the modules, comparing the profit corresponding to the plurality of resource data, The preferred resource data corresponding to the maximum profit is obtained; and the scheduling module performs scheduling of the cloud computing resource according to the preferred resource data.
在其中一个实施例中，获得模块获得的资源数据包括收益和成本；计算模块执行如下计算：利润等于收益减去成本。In one of the embodiments, the resource data obtained by the obtaining module includes revenue and cost; the computing module performs the calculation that the profit is equal to the revenue minus the cost.
在其中一个实施例中，收益等于完成的任务量，成本等于需要使用的云计算节点数量。In one of the embodiments, the revenue is equal to the amount of tasks completed, and the cost is equal to the number of cloud computing nodes that need to be used.
在其中一个实施例中，收益等于完成的任务量乘以权重k1，成本等于需要使用的云计算节点数量乘以权重K2。In one of the embodiments, the revenue is equal to the completed task amount multiplied by the weight k1, and the cost is equal to the number of cloud computing nodes to be used multiplied by the weight K2.
在其中一个实施例中，权重K1和权重K2取自训练数据库；K1为单位任务的收益，来自任务属性库；K2为单位云计算节点的成本，来自云计算资源属性库。In one embodiment, the weight K1 and the weight K2 are taken from the training database; K1 is the revenue of the unit task, from the task attribute library; K2 is the cost of the unit cloud computing node, from the cloud computing resource attribute library.
本发明的云计算的调度方法和***，通过收益减去成本来计算云计算资源的不同调度方案的利润，再通过比较利润大小，来得到并实施利润最大的云计算资源调度方案。The cloud computing scheduling method and system of the present invention calculates the profit of different scheduling schemes of cloud computing resources by reducing the cost, and then obtains and implements the cloud computing resource scheduling scheme with the largest profit by comparing the profit size.
【附图说明】[Description of the Drawings]
图1为本发明的云计算的调度方法的流程图；1 is a flowchart of a method for scheduling cloud computing according to the present invention;
图2为本发明的云计算的调度***的原理框图。2 is a schematic block diagram of a scheduling system for cloud computing according to the present invention.
【具体实施方式】 【detailed description】
本发明利用已有的云计算资源进行调度，以尽量获得最大的计算利润为目标来实施云计算。The invention utilizes the existing cloud computing resources for scheduling, and implements cloud computing with the goal of obtaining the maximum computing profit as much as possible.
如图1所示，本发明的云计算的调度方法，包括如下步骤：As shown in FIG. 1 , the scheduling method of the cloud computing of the present invention includes the following steps:
S1：获得步骤，获得多个资源数据。资源数据包括收益和成本；收益和成本有两种计算方法，第一种是，收益等于完成的任务量，成本等于需要使用的云计算节点数量；第二种是，收益等于完成的任务量乘以权重k1，成本等于需要使用的云计算节点数量乘以权重K2，权重K1和权重K2根据不同的应用行业取自相关的行业训练数据库；K1为单位任务的收益，来自任务属性库；K2为单位云计算节点的成本，来自云计算资源属性库。S1: Obtain a step to obtain multiple resource data. Resource data includes revenue and cost; income and cost have two calculation methods. The first is that the revenue is equal to the completed task quantity, the cost is equal to the number of cloud computing nodes to be used, and the second is that the revenue is equal to the completed task quantity multiplication. With the weight k1, the cost is equal to the number of cloud computing nodes to be used multiplied by the weight K2, and the weight K1 and the weight K2 are taken from the relevant industry training database according to different application industries; K1 is the revenue of the unit task, from the task attribute library; K2 is The cost of a unit cloud computing node comes from the cloud computing resource attribute library.
S2：计算步骤，根据多个资源数据分别计算多个资源数据的利润，利润等于收益减去成本。S2: a calculation step of separately calculating profit of a plurality of resource data according to the plurality of resource data, and the profit is equal to the income minus the cost.
S3：比较步骤，比较多个资源数据对应的利润的大小，获得最大利润对应的优选资源数据。S3: a comparison step of comparing the size of the profit corresponding to the plurality of resource data to obtain the preferred resource data corresponding to the maximum profit.
S4：调度步骤，依据优选资源数据进行云计算资源的调度。S4: a scheduling step of scheduling cloud computing resources according to the preferred resource data.
如图2所示，本发明的云计算的调度***，包括依次连接的获得模块、计算模块、比较模块和调度模块。As shown in FIG. 2, the scheduling system of the cloud computing of the present invention includes an obtaining module, a computing module, a comparing module, and a scheduling module that are sequentially connected.
获得模块获得多个资源数据，资源数据包括收益和成本。收益和成本有两种计算方法，第一种是，收益等于完成的任务量，成本等于需要使用的云计算节点数量；第二种是，收益等于完成的任务量乘以权重k1，成本等于需要使用的云计算节点数量乘以权重K2，权重K1和权重K2根据不同的应用行业取自相关的行业训练数据库；K1为单位任务的收益，来自任务属性库；K2为单位云计算节点的成本，来自云计算资源属性库。The acquisition module obtains multiple resource data, including revenue and cost. There are two ways to calculate the benefits and costs. The first is that the revenue is equal to the amount of tasks completed, the cost is equal to the number of cloud computing nodes to be used, and the second is that the revenue is equal to the completed task multiplied by the weight k1, and the cost is equal to the need. The number of cloud computing nodes used is multiplied by the weight K2, and the weight K1 and the weight K2 are taken from the relevant industry training database according to different application industries; K1 is the revenue of the unit task, from the task attribute library; K2 is the cost of the unit cloud computing node, From the cloud computing resource property library.
计算模块根据多个资源数据分别计算多个资源数据的利润。The calculation module separately calculates the profit of the plurality of resource data according to the plurality of resource data.
比较模块比较多个资源数据对应的利润的大小，获得最大利润对应的优选资源数据。The comparison module compares the size of the profit corresponding to the plurality of resource data, and obtains the preferred resource data corresponding to the maximum profit.
调度模块依据优选资源数据进行云计算资源的调度。The scheduling module performs scheduling of the cloud computing resources according to the preferred resource data.
以上所述实施例仅表达了本发明的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对本发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干变形和改进，这些都属于本发明的保护范围。因此，本发明专利的保护范围应以所附权利要求为准。The above-mentioned embodiments are merely illustrative of several embodiments of the present invention, and the description thereof is more specific and detailed, but is not to be construed as limiting the scope of the invention. It should be noted that a number of variations and modifications may be made by those skilled in the art without departing from the spirit and scope of the invention. Therefore, the scope of the invention should be determined by the appended claims.

Claims (10)

  1. 一种云计算的调度方法，包括如下步骤：A cloud computing scheduling method includes the following steps:
    获得步骤，获得多个资源数据；Obtaining steps to obtain multiple resource data;
    计算步骤，根据该多个资源数据分别计算该多个资源数据的利润；a calculating step of separately calculating profit of the plurality of resource data according to the plurality of resource data;
    比较步骤，比较该多个资源数据对应的利润的大小，获得最大利润对应的优选资源数据；以及a comparison step of comparing the size of the profit corresponding to the plurality of resource data to obtain the preferred resource data corresponding to the maximum profit;
    调度步骤，依据优选资源数据进行云计算资源的调度。The scheduling step is to perform scheduling of the cloud computing resource according to the preferred resource data.
  2. 根据权利要求1所述的云计算的调度方法，其特征在于，所述的获得步骤中，该资源数据包括收益和成本；所述的计算步骤中，该利润等于该收益减去该成本。The method for scheduling cloud computing according to claim 1, wherein in the obtaining step, the resource data includes revenue and cost; and in the calculating step, the profit is equal to the revenue minus the cost.
  3. 根据权利要求2所述的云计算的调度方法，其特征在于，该收益等于完成的任务量，该成本等于需要使用的云计算节点数量。The cloud computing scheduling method according to claim 2, wherein the revenue is equal to the completed task amount, and the cost is equal to the number of cloud computing nodes to be used.
  4. 根据权利要求2所述的云计算的调度方法，其特征在于，该收益等于完成的任务量乘以权重k1，该成本等于需要使用的云计算节点数量乘以权重K2。The cloud computing scheduling method according to claim 2, wherein the revenue is equal to the completed task amount multiplied by a weight k1, the cost being equal to the number of cloud computing nodes to be used multiplied by the weight K2.
  5. 根据权利要求4所述的云计算的调度方法，其特征在于，该权重K1和该权重K2取自训练数据库；K1为单位任务的收益，来自任务属性库；K2为单位云计算节点的成本，来自云计算资源属性库。The method for scheduling cloud computing according to claim 4, wherein the weight K1 and the weight K2 are taken from a training database; K1 is a revenue of a unit task, from a task attribute library; K2 is a cost of a unit cloud computing node, From the cloud computing resource property library.
  6. 一种云计算的调度***，其特征在于，包括：A cloud computing scheduling system, comprising:
    获得模块，获得多个资源数据；Obtain a module to obtain multiple resource data;
    计算模块，根据该多个资源数据分别计算该多个资源数据的利润；a calculating module, respectively calculating a profit of the plurality of resource data according to the plurality of resource data;
    比较模块，比较该多个资源数据对应的利润的大小，获得最大利润对应的优选资源数据；以及Comparing a module, comparing the size of the profit corresponding to the plurality of resource data, and obtaining the preferred resource data corresponding to the maximum profit;
    调度模块，依据优选资源数据进行云计算资源的调度。The scheduling module performs scheduling of the cloud computing resources according to the preferred resource data.
  7. 根据权利要求6所述的云计算的调度***，其特征在于，所述的获得模块获得的该资源数据包括收益和成本；所述的计算模块执行如下计算：该利润等于该收益减去该成本。The scheduling system for cloud computing according to claim 6, wherein the resource data obtained by the obtaining module includes revenue and cost; and the calculating module performs the following calculation: the profit is equal to the revenue minus the cost. .
  8. 根据权利要求7所述的云计算的调度***，其特征在于，该收益等于完成的任务量，该成本等于需要使用的云计算节点数量。The cloud computing scheduling system according to claim 7, wherein the revenue is equal to the completed task amount, and the cost is equal to the number of cloud computing nodes to be used.
  9. 根据权利要求7所述的云计算的调度***，其特征在于，该收益等于完成的任务量乘以权重k1，该成本等于需要使用的云计算节点数量乘以权重K2。The cloud computing scheduling system according to claim 7, wherein the revenue is equal to the completed task amount multiplied by a weight k1, the cost being equal to the number of cloud computing nodes to be used multiplied by the weight K2.
  10. 根据权利要求9所述的云计算的调度***，其特征在于，该权重K1和该权重K2取自训练数据库；K1为单位任务的收益，来自任务属性库；K2为单位云计算节点的成本，来自云计算资源属性库。The scheduling system for cloud computing according to claim 9, wherein the weight K1 and the weight K2 are taken from a training database; K1 is a revenue of a unit task, from a task attribute library; K2 is a cost of a unit cloud computing node, From the cloud computing resource property library.
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Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103002053B (en) * 2012-12-25 2016-06-08 深圳先进技术研究院 The profit maximization dispatching method of cloud computing and system
US9417923B2 (en) 2013-12-17 2016-08-16 International Business Machines Corporation Optimization of workload placement
CN106446959B (en) * 2016-10-10 2019-06-07 北京邮电大学 A kind of cloud computing resources dynamic matching method and device
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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101702650A (en) * 2009-11-11 2010-05-05 中兴通讯股份有限公司 Counting method of network computing service and network computing service providing system
CN102185926A (en) * 2011-05-25 2011-09-14 盛大计算机（上海）有限公司 Cloud computing resource management system and method
CN102317962A (en) * 2008-12-12 2012-01-11 纽约市哥伦比亚大学理事会 Machine optimization devices, methods, and systems
CN102662764A (en) * 2012-04-25 2012-09-12 梁宏斌 Dynamic cloud computing resource optimization allocation method based on semi-Markov decision process (SMDP)
US20120232864A1 (en) * 2010-01-05 2012-09-13 International Business Machines Corporation Analyzing Anticipated Value and Effort in Using Cloud Computing to Process a Specified Workload
CN103002053A (en) * 2012-12-25 2013-03-27 深圳先进技术研究院 Profit maximization scheduling method and system of cloud computing

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7685283B2 (en) * 2006-01-23 2010-03-23 International Business Machiens Corporation Method for modeling on-demand free pool of resources
CN102331948A (en) * 2011-09-01 2012-01-25 杭州湾云计算技术有限公司 Resource state-based virtual machine structure adjustment method and adjustment system

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102317962A (en) * 2008-12-12 2012-01-11 纽约市哥伦比亚大学理事会 Machine optimization devices, methods, and systems
CN101702650A (en) * 2009-11-11 2010-05-05 中兴通讯股份有限公司 Counting method of network computing service and network computing service providing system
US20120232864A1 (en) * 2010-01-05 2012-09-13 International Business Machines Corporation Analyzing Anticipated Value and Effort in Using Cloud Computing to Process a Specified Workload
CN102185926A (en) * 2011-05-25 2011-09-14 盛大计算机（上海）有限公司 Cloud computing resource management system and method
CN102662764A (en) * 2012-04-25 2012-09-12 梁宏斌 Dynamic cloud computing resource optimization allocation method based on semi-Markov decision process (SMDP)
CN103002053A (en) * 2012-12-25 2013-03-27 深圳先进技术研究院 Profit maximization scheduling method and system of cloud computing

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