CN107589980A - A kind of dispatching method of cloud computing resources - Google Patents
A kind of dispatching method of cloud computing resources Download PDFInfo
- Publication number
- CN107589980A CN107589980A CN201710646336.9A CN201710646336A CN107589980A CN 107589980 A CN107589980 A CN 107589980A CN 201710646336 A CN201710646336 A CN 201710646336A CN 107589980 A CN107589980 A CN 107589980A
- Authority
- CN
- China
- Prior art keywords
- user
- virtual machine
- task
- cloud computing
- resource
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Landscapes
- Debugging And Monitoring (AREA)
Abstract
The embodiments of the invention provide a kind of dispatching method of cloud computing resources, methods described includes：User's request is received, and received user's request is put into user's request queue, and whether the Information Authentication user asked according to each user is legal；If it is, the information asked according to the user judges the type that the user asks；State value of each virtual machine in preset time period is calculated according to the property indices of virtual machine in task type and current cloud computing environment；According to the state value of the virtual machine and the task type, it is determined that needing to carry out the virtual machine of scheduling of resource；Each user in user's request queue is asked to send to identified virtual machine.Using the embodiment of the present invention, realize that equilibrium uses various computer resources in cloud computing environment, realize and satisfied load balancing is obtained under less expense, improve the overall efficiency of system call.
Description
Technical field
The present invention relates to data processing field, more particularly to a kind of dispatching method of cloud computing resources.
Background technology
In recent years, with information technology high speed development and internet scale increasingly increase, internet is to be dealt with
Portfolio and data volume are also increasing rapidly.In order to effectively handle the data of these magnanimity and service, optimization user uses mutual
The experience of the Internet services, cloud computing technology arise at the historic moment.Cloud computing passes through distributed computing technology, parallel computing, virtual
The computer and network technologies such as change technology and load balancing provide a user convenient, fast, safe data storage and network clothes
Business, new opportunities and challenges are brought for the development of computer technology and IT technologies.
Scheduling of resource refers under specific resource environment, according to certain resource using rule, makes in different resources
The process of resource adjustment is carried out between user.These resources user correspond to a different calculating tasks (such as virtual solution
Certainly scheme), each calculating task corresponds to one or more process in an operating system.Generally there are two kinds of approach to realize
The scheduling of resource of calculating task：Its resource usage amount is distributed in adjustment on the machine where calculating task, or will be calculated
Task is transferred on other machines.The appearance of virtual machine causes all calculating tasks to be all encapsulated in a virtual machine internal.
Because virtual machine has isolation characteristic, therefore the mesh of calculating task migration can be reached using the dynamic migration scheme of virtual machine
's.
Although cloud computing is developed on the basis of traditional computing technique such as distributed computing technology, parallel computing
Get up, but for traditional Distributed Calculation, parallel computation, the resource pool of cloud computing is usually special by some
Server form in advance, and cloud computing towards user type and huge number, therefore, some traditional resources tune
Degree and administrative skill in cloud computing environment and do not apply to.
Because business is numerous in cloud computing, task type is also varied, if the resource by all user applications
Scheduling is all placed under identical framework, and caused scheduling result is generally not optimal for user.Therefore, need
Different scheduling strategies is selected according to the task type for treating scheduler task from the angle of task type, so as to realize pair
The efficient scheduling of different type task.Also, in existing cloud computing resources dispatching technique, have the unilateral of scheduling strategy
Property, the appearance of blindness circulation of physical resource is may result in, it is necessary to avoid as far as possible.In addition, during tasks carrying, by
It can change the resource consumption type of task in the execution of task, thus therefore the type of task can also change, this is allowed for
The situation that static Resource Distribution and Schedule often causes the deficiency of resource or wasted, and artificial dynamic resource adjustment has
Obvious hysteresis quality, therefore also needs to the execution state of monitor task in real time, and the resource consumption type intelligence for passing through task
Can ground judge the resource consumption type of task, if the resource consumption type of task with it is initial when task type it is inconsistent, and
Also will not be consistent within the sufficiently long time, and this inconsistent health value for having highly impacted virtual machine, then need
It is in due course and dynamic reschedule to realize that equilibrium uses various resources (CPU, internal memory, disk, I/ is carried out to task
O, network), single resource bottleneck is avoided the occurrence of, lifts virtual machine density, eliminates focus, improves traffic handing capacity, and it is existing
Resource scheduling scheme do not account for this point.
The content of the invention
The purpose of the embodiment of the present invention is to provide a kind of dispatching method of cloud computing resources, to realize in cloud computing environment
It is middle to realize that equilibrium uses various computer resources, realize and satisfied load balancing is obtained under less expense, improve system and adjust
The overall efficiency of degree.
In order to achieve the above object, the embodiment of the invention discloses a kind of dispatching method of cloud computing resources, methods described
Including：
User's request is received, and received user's request is put into user's request queue, and please according to each user
Whether the Information Authentication user asked is legal；
If it is, the information asked according to the user judges the type that the user asks；
Each virtual machine is calculated pre- according to the property indices of virtual machine in task type and current cloud computing environment
If the state value in the period；
According to the state value of the virtual machine and the task type, it is determined that needing to carry out the virtual machine of scheduling of resource；
Each user in user's request queue is asked to send to identified virtual machine.
Optionally, the determination needs to carry out the virtual machine of scheduling of resource, including：
The status predication value of more each virtual machine, determine the predicted value that numerical value is maximum in status predication value；
Virtual machine corresponding to the maximum predicted value of the numerical value is determined to need the virtual machine for carrying out scheduling of resource.
Optionally, when the result of the maximum predicted value of numerical value in the determination status predication value is at least two；
The load of virtual machine according to corresponding to the task type of task requests calculates at least two predicted value；
Determine the minimum value in the load；
Virtual machine corresponding to the minimum value is defined as to need the virtual machine for carrying out scheduling of resource.
Optionally, the state value for calculating each virtual machine in preset time period, including：
Calculate cpu busy percentage, memory usage, disk utilization, magnetic disc i/o utilization rate, the network bandwidth in the virtual machine
At least one of utilization rate.
Optionally, the type of user's request, including：
Calculate class, I/O classes or complex class；The generic task that calculates refers to consume the task based on cpu resource；The I/O classes
Task refers to consume the task based on magnetic disc i/o or network bandwidth；The compound generic task refers to consume a variety of moneys simultaneously
Source simultaneously cannot be distinguished by task of which kind of resource for the main resource of the type task consumption.
Optionally, methods described also includes：
When the Information Authentication user of user's request is illegal, ignore user request.
The dispatching method of cloud computing resources provided in an embodiment of the present invention, first user can be classified, at one point
User clustering is carried out in class, on the one hand can be more targeted so as to select suitable targeted customer to carry out cluster analysis,
The data volume of computing is reduced, on the other hand interference of the inhomogeneous user data for Clustering Effect can be excluded, make user group
Division is more accurate, is easy to carry out accurate formula, personalized service according to user group's division result.Certainly, the present invention is implemented
Any product or method must be not necessarily required to reach all the above advantage simultaneously.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is the required accompanying drawing used in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can be with
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is the schematic flow sheet of the dispatching method of cloud computing resources provided in an embodiment of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art are obtained every other under the premise of creative work is not made
Embodiment, belong to the scope of protection of the invention.
Fig. 1 is the schematic flow sheet of the dispatching method of cloud computing resources provided in an embodiment of the present invention, and this method includes step
Suddenly：
S101：User's request is received, and received user's request is put into user's request queue, and according to each use
Whether the Information Authentication user of family request is legal, if it is, performing S102.
In addition, when the Information Authentication user of user's request is illegal, ignore user request
S102：The information asked according to the user judges the type that the user asks.
S103：It is empty that each is calculated according to the property indices of virtual machine in task type and current cloud computing environment
State value of the plan machine in preset time period.
S104：According to the state value of the virtual machine and the task type, it is determined that needing to carry out the virtual of scheduling of resource
Machine.
S105, each user in user's request queue is asked to send to identified virtual machine.
The status predication value of more each virtual machine, determine the predicted value that numerical value is maximum in status predication value；
Virtual machine corresponding to the maximum predicted value of the numerical value is determined to need the virtual machine for carrying out scheduling of resource.When the determination
When the result of the maximum predicted value of numerical value is at least two in status predication value；
The load of virtual machine according to corresponding to the task type of task requests calculates at least two predicted value；
Determine the minimum value in the load；
Virtual machine corresponding to the minimum value is defined as to need the virtual machine for carrying out scheduling of resource.
Calculate cpu busy percentage, memory usage, disk utilization, magnetic disc i/o utilization rate, the network in the virtual machine
At least one of bandwidth availability ratio.
Calculate class, I/O classes or complex class；The generic task that calculates refers to consume the task based on cpu resource；The I/
O generic tasks refer to consume the task based on magnetic disc i/o or network bandwidth；The compound generic task refers to consume simultaneously a variety of
Resource simultaneously cannot be distinguished by task of which kind of resource for the main resource of the type task consumption.
Assuming that d0 is n nearest history virtual machine state value sequence (n value is according to circumstances selected, is elected as herein 7)：
Wherein, d1 is generated d0=(d0 (1), d0 (2) ..., d0 (n)) by the cumulative of data in d0, d1=(d1 (1), d1
(2),...,d1(n))。
If task type is calculates generic task, when task is calculates generic task, it is pre- that scheduling decision module calculates these
The cpu load rate of the maximum virtual machine of state value is surveyed, and the wherein less virtual machine of cpu load rate is virtual as what is selected
Machine, if still having, two or more are identical, select that virtual machine of foremost.Cpu load rate calculation formula is (its
In, M is cpu load rate, and P is cpu busy percentage, and Q is CPU idleness)：M=P/Q, then perform step 6；
When task is I/O generic tasks, scheduling decision module calculates the I/O loads of the maximum virtual machine of these predicted state values
Rate, and using the less virtual machine of I/O load factors as selected virtual machine, if still there is two or more identical, select
That virtual machine of foremost.I/O load factors calculation formula for (wherein, N is I/O load factors, and V is magnetic disc i/o utilization rate,
W is magnetic disc i/o idleness, and X is network bandwidth utilization factor, and Y is network bandwidth idleness)：N=V/W*50%+X/Y*50%.
When task is compound generic task, scheduling decision module calculates the synthesis of the maximum virtual machine of these predicted state values
Load factor, and using the less virtual machine of integrated load rate as selected virtual machine, if still having, two or more are identical,
That virtual machine of selected foremost.Integrated load rate calculation formula is (wherein, O is integrated load rate, and P utilizes for CPU
Rate, Q are CPU idleness, and R is memory usage, and S is internal memory idleness, and T is disk utilization, and U is disk idleness, and V is
Magnetic disc i/o utilization rate, W are magnetic disc i/o idleness, and X is network bandwidth utilization factor, and Y is network bandwidth idleness)：O=P/Q*
20%+R/S*20%+T/U*20%+V/W*20%+X/Y*20%, then perform step 6；Task scheduling can be determined to scheduling
The virtual machine that plan module selects, the smart allocation of resource is realized, so far just complete the process of first resource scheduling.
It should be noted that herein, such as first and second or the like relational terms are used merely to a reality
Body or operation make a distinction with another entity or operation, and not necessarily require or imply and deposited between these entities or operation
In any this actual relation or order.Moreover, term " comprising ", "comprising" or its any other variant are intended to
Nonexcludability includes, so that process, method, article or equipment including a series of elements not only will including those
Element, but also the other element including being not expressly set out, or it is this process, method, article or equipment also to include
Intrinsic key element.In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that
Other identical element also be present in process, method, article or equipment including the key element.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the scope of the present invention.It is all
Any modification, equivalent substitution and improvements made within the spirit and principles in the present invention etc., are all contained in protection scope of the present invention
It is interior.
Claims (6)
1. a kind of dispatching method of cloud computing resources, it is characterised in that methods described includes：
User's request is received, and received user's request is put into user's request queue, and please according to each user
Whether the Information Authentication user asked is legal；
If it is, the information asked according to the user judges the type that the user asks；
Each virtual machine is calculated pre- according to the property indices of virtual machine in task type and current cloud computing environment
If the state value in the period；
According to the state value of the virtual machine and the task type, it is determined that needing to carry out the virtual machine of scheduling of resource；
Each user in user's request queue is asked to send to identified virtual machine.
2. the dispatching method of cloud computing resources according to claim 1, it is characterised in that the determination needs to carry out resource
The virtual machine of scheduling, including：
The status predication value of more each virtual machine, determine the predicted value that numerical value is maximum in status predication value；
Virtual machine corresponding to the maximum predicted value of the numerical value is determined to need the virtual machine for carrying out scheduling of resource.
3. the dispatching method of cloud computing resources according to claim 2, it is characterised in that when the determination status predication value
When the result of the maximum predicted value of middle numerical value is at least two；
The load of virtual machine according to corresponding to the task type of task requests calculates at least two predicted value；
Determine the minimum value in the load；
Virtual machine corresponding to the minimum value is defined as to need the virtual machine for carrying out scheduling of resource.
4. the dispatching method of cloud computing resources according to claim 1, it is characterised in that described each virtual machine of calculating
State value in preset time period, including：
Calculate cpu busy percentage, memory usage, disk utilization, magnetic disc i/o utilization rate, the network bandwidth in the virtual machine
At least one of utilization rate.
5. the dispatching method of the cloud computing resources according to any one of claim 1-4, it is characterised in that the user please
The type asked, including：
Calculate class, I/O classes or complex class；The generic task that calculates refers to consume the task based on cpu resource；The I/O classes
Task refers to consume the task based on magnetic disc i/o or network bandwidth；The compound generic task refers to consume a variety of moneys simultaneously
Source simultaneously cannot be distinguished by task of which kind of resource for the main resource of the type task consumption.
6. the dispatching method of cloud computing resources according to claim 1, it is characterised in that methods described also includes：
When the Information Authentication user of user's request is illegal, ignore user request.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710646336.9A CN107589980A (en) | 2017-08-01 | 2017-08-01 | A kind of dispatching method of cloud computing resources |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710646336.9A CN107589980A (en) | 2017-08-01 | 2017-08-01 | A kind of dispatching method of cloud computing resources |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107589980A true CN107589980A (en) | 2018-01-16 |
Family
ID=61042852
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710646336.9A Pending CN107589980A (en) | 2017-08-01 | 2017-08-01 | A kind of dispatching method of cloud computing resources |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107589980A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110109733A (en) * | 2019-04-29 | 2019-08-09 | 东北大学 | Virtual Machine Worker queue and redundancy queue update method towards different aging scenes |
| CN110858160A (en) * | 2018-08-24 | 2020-03-03 | 阿里巴巴集团控股有限公司 | Resource scheduling method and device, storage medium and processor |
| CN111580951A (en) * | 2019-02-15 | 2020-08-25 | 杭州海康威视数字技术股份有限公司 | Task allocation method and resource management platform |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103164283A (en) * | 2012-05-10 | 2013-06-19 | 上海兆民云计算科技有限公司 | Method and system for dynamic scheduling management of virtualized resources in virtualized desktop system |
| CN103595780A (en) * | 2013-11-08 | 2014-02-19 | 中国人民解放军理工大学 | Cloud computing resource scheduling method based on repeat removing |
| CN104065745A (en) * | 2014-07-07 | 2014-09-24 | 电子科技大学 | Cloud computing dynamic resource scheduling system and method |
| CN106951330A (en) * | 2017-04-10 | 2017-07-14 | 郑州轻工业学院 | A kind of maximized virtual machine distribution method of cloud service center service utility |
-
2017
- 2017-08-01 CN CN201710646336.9A patent/CN107589980A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103164283A (en) * | 2012-05-10 | 2013-06-19 | 上海兆民云计算科技有限公司 | Method and system for dynamic scheduling management of virtualized resources in virtualized desktop system |
| CN103595780A (en) * | 2013-11-08 | 2014-02-19 | 中国人民解放军理工大学 | Cloud computing resource scheduling method based on repeat removing |
| CN104065745A (en) * | 2014-07-07 | 2014-09-24 | 电子科技大学 | Cloud computing dynamic resource scheduling system and method |
| CN106951330A (en) * | 2017-04-10 | 2017-07-14 | 郑州轻工业学院 | A kind of maximized virtual machine distribution method of cloud service center service utility |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110858160A (en) * | 2018-08-24 | 2020-03-03 | 阿里巴巴集团控股有限公司 | Resource scheduling method and device, storage medium and processor |
| CN111580951A (en) * | 2019-02-15 | 2020-08-25 | 杭州海康威视数字技术股份有限公司 | Task allocation method and resource management platform |
| CN111580951B (en) * | 2019-02-15 | 2023-10-10 | 杭州海康威视数字技术股份有限公司 | Task allocation method and resource management platform |
| CN110109733A (en) * | 2019-04-29 | 2019-08-09 | 东北大学 | Virtual Machine Worker queue and redundancy queue update method towards different aging scenes |
| CN110109733B (en) * | 2019-04-29 | 2022-06-24 | 东北大学 | Virtual machine work queue and redundancy queue updating method oriented to different aging scenes |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Mansouri et al. | Cost-based job scheduling strategy in cloud computing environments | |
| CN106020927B (en) | Task scheduling and the universal method of resource distribution in a kind of cloud computing system | |
| Zuo et al. | A multiqueue interlacing peak scheduling method based on tasks’ classification in cloud computing | |
| CN103713956B (en) | Method for intelligent weighing load balance in cloud computing virtualized management environment | |
| CN103885831B (en) | The system of selection of virtual machine host machine and device | |
| CN103595780B (en) | Cloud computing resource scheduling method based on the weight that disappears | |
| Jing et al. | QoS-DPSO: QoS-aware task scheduling for cloud computing system | |
| CN104601664B (en) | A kind of control system of cloud computing platform resource management and scheduling virtual machine | |
| CN104065745A (en) | Cloud computing dynamic resource scheduling system and method | |
| CN104023042B (en) | Cloud platform resource scheduling method | |
| CN103401939A (en) | Load balancing method adopting mixing scheduling strategy | |
| CN103365726A (en) | Resource management method and system facing GPU (Graphic Processing Unit) cluster | |
| CN107968810A (en) | A kind of resource regulating method of server cluster, device and system | |
| CN106202092A (en) | The method and system that data process | |
| CN105824686A (en) | Selecting method and selecting system of host machine of virtual machine | |
| Sharma et al. | An improved task allocation strategy in cloud using modified k-means clustering technique | |
| CN110347515A (en) | A kind of resource optimal distribution method of suitable edge calculations environment | |
| CN110362388A (en) | A kind of resource regulating method and device | |
| CN107589980A (en) | A kind of dispatching method of cloud computing resources | |
| CN103997515B (en) | Center system of selection and its application are calculated in a kind of distributed cloud | |
| CN105607943A (en) | Dynamic deployment mechanism of virtual machine in cloud environment | |
| Alshathri et al. | A New Reliable System For Managing Virtual Cloud Network. | |
| Taheri et al. | Hopfield neural network for simultaneous job scheduling and data replication in grids | |
| Jiang et al. | An energy-aware virtual machine migration strategy based on three-way decisions | |
| CN106506229B (en) | A kind of SBS cloud application adaptive resource optimizes and revises system and method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180116 |