CN103401938B - Based on resource allocation system and the method thereof of traffic performance under distributed cloud framework - Google Patents
Based on resource allocation system and the method thereof of traffic performance under distributed cloud framework Download PDFInfo
- Publication number
- CN103401938B CN103401938B CN201310342532.9A CN201310342532A CN103401938B CN 103401938 B CN103401938 B CN 103401938B CN 201310342532 A CN201310342532 A CN 201310342532A CN 103401938 B CN103401938 B CN 103401938B
- Authority
- CN
- China
- Prior art keywords
- cloud
- data center
- user
- resource
- computation data
- 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.)
- Active
Links
Landscapes
- Debugging And Monitoring (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses resource allocation system and method thereof based on traffic performance under a kind of distributed cloud framework, this method step is: (1) sets up the cloud resource distribution system based on traffic performance；(2) update mechanism of data center's state table is set up；(3) cloud user submits cloud resource request to Resource Scheduler；(4) step (5) or (6) is selected according to the traffic performance of cloud user；(5) centralized mode is used to be that cloud user disposes virtual machine；(6) distributed mode is used to be that cloud user disposes virtual machine；(7) virtual machine is assigned, and explorer is to cloud user feedback allocation result.Mainly solve under distributed cloud computing environment, have the resource allocation problem of the cloud customer service of different business characteristic.
Description
Technical field
The present invention relates to field of cloud calculation, be specifically related to the resource allocation system based on traffic performance under distributed cloud framework
And method.The present invention is applicable to solve under distributed cloud computing environment, has the cloud customer service of different business characteristic
Resource allocation problem.
Background technology
Universal with cloud computing, increasing user by the cloud computing platform of business migration to cloud service provider,
Operate on the virtual machine of cloud computing platform, become cloud user.Cloud service provider according to the real needs of cloud customer service is
The resources, i.e. cloud resource such as its distribution calculating, storage, bandwidth.These cloud resource composition virtual machines, the business of cloud user just operates in
On these virtual machines.
Cloud computing platform is to be made up of multiple data centers, the geographical position of each data center, capacity and resource valency
Lattice are different.Cloud service provider is its corresponding cloud resource of distribution according to the real needs of cloud user, by these cloud resources
Constitute virtual machine and run the business of corresponding cloud user.
Can cloud service provider gain and depend on stability, resource utilization and the cloud money of its cloud platform being provided
The factors such as the price model in source.The research of current cloud resource distribution is concentrated mainly on the angle from cloud computing platform, finds
The method improving cloud computing resources utilization rate.
Generally speaking, the research of current cloud resource distribution is concentrated mainly on the following aspects:
The scheduling virtual machine machine of first, IaaS (Infrastructure as a Service, infrastructure i.e. services) level
The research of system, adjusts the distribution of virtual machine dynamically, thus improves cloud money according to the dynamic change to cloud resource requirement for the user
The utilization rate in source；
Second, based on the resource distribution of priority, business is classified by cloud service provider according to priority, is preferably
The high traffic assignments resource of priority, then for the traffic assignments resource that priority is low, improves the utilization rate of resource with this；
3rd, based on the resource distribution mode of Traffic prediction, in this fashion, cloud service provider is to cloud user's industry
The required stock number of business is predicted, and is then its distribution resource by the demand of cloud customer service.
Current resource allocation methods can improve the utilization rate of resource to a certain extent, and increases cloud service provider
Income.But, from the angle of cloud user, these methods can not bring how many incomes.Therefore, the angle from cloud service characteristics
Degree research cloud computing resources distribution, improves cloud resource utilization, need further to study.
Owing to the traffic performance of different cloud users is different, in terms of to resource price, time delay and resource deployment mode etc.
Requirement different, rack in resource allocation process entering, it is necessary to the characteristic according to cloud customer service enters resource of racking
Distribution, thus effectively reduce the cost of cloud user, it is achieved the maximization of cloud service provider long-term gain.
Content of the invention
In view of the deficiencies in the prior art, the present invention is different according to the characteristic of cloud customer service, proposes a kind of special based on business
The cloud resource allocation system of property and method thereof.
Further, the present invention can substantially reduce the cost of different business characteristic cloud user, and realizes different cloud computing
Load balancing between data center.
The basic fundamental thinking of the present invention is, utilizes Resource Scheduler to receive the request of cloud user, including needed for cloud user
The total amount of cloud resource and the description to own service characteristic for the cloud user；Status information further according to cloud computation data center draws
Candidate data centralization；Then this cost index at candidate data center for cloud customer service is calculated；Refer to finally according to cost
The traffic performance of number and this cloud user completes the distribution of cloud resource.
For achieving the above object, the technical solution used in the present invention is as follows:
Based on the resource allocation system of traffic performance under a kind of distributed cloud framework, described system includes:
Resource Scheduler, the state computation of the requirement according to cloud user and each cloud computation data center draws cloud user's phase
Cost index to each cloud computation data center, and be that virtual machine is disposed in its distribution according to the demand of cloud user；Described resource
Scheduler module may operate in certain cloud computation data center of cloud computing platform；
Cloud data center condition monitoring process, sends the state letter of place cloud computation data center to described Resource Scheduler
Breath, described cloud data center condition monitoring process is to operate in the monitoring process of cloud computation data center；
Data center's block of state, is for storing each cloud computation data center status information in described Resource Scheduler
Module, carries out real-time update according to the status information that cloud computation data center is reported, including the time delay of cloud computation data center is estimated
The information of meter, surplus resources and resource price.
The method carrying out resource distribution based on the resource allocation system of traffic performance under distributed cloud framework, described method bag
Include following steps:
(1) the cloud resource distribution system based on traffic performance is set up；Receive asking from cloud user according to Resource Scheduler
Ask, according to cloud data center condition monitoring process, monitor the state of the cloud computation data center at its place, and adjust to described resource
Degree device report, calculates the cost index of the relatively each cloud computation data center of cloud user, according to institute according to the information in described report
Stating cost index is cloud user resource allocation or the request of refusal cloud user；
(2) renewal of cloud computation data center block of state is set up；Described cloud data center condition monitoring process is periodically
Ground is to the status information of Resource Scheduler report place cloud computation data center, and wherein, described status information includes surplus resources
Lk,t, price P of data center resourcek,tAnd the time delay estimation D of data centerk,t；
(3) cloud user submits cloud resource request R to Resource Scheduleri(li,ni,ci), li=li(f, m, h b) represent that cloud is used
The configuration of virtual machine needed for family, wherein, f represents dominant frequency, and m represents built-in storage, and h represents hard disk, and b represents bandwidth, niRepresent cloud
The quantity of virtual machine, c needed for user ii=(si,αi,βi) represent cloud user i traffic performance, wherein, siRepresent cloud user i institute
Need the deployment request of virtual machine, si=1 expression cloud user requires that virtual machine is concentrated and is deployed in a cloud computation data center, si
=v, (v ＞ 1) represents that cloud user requires that virtual machine is deployed in v cloud computation data center respectively, αi,βi∈ [0,1] table respectively
Showing time delay factor and the Price factor of cloud user i, the time delay factor of different business is different with Price factor, gets over time delay or price
Sensitivity, αiOr βiValue bigger；
(4) if cloud user si=1, step (5)；If si=v, (v ＞ 1), step (6)；
(5) centralized mode is used to be that cloud user i disposes virtual machine, wherein
(5a) described Resource Scheduler searches described data center block of state, selects and meets cloud user i resource requirement Ri
(li,ni) cloud computation data center k*, L must be metk,t≥nili, and constitute candidate collection G of user ii；
If (5b) described candidate collection GiFor empty set, represent that currently there is no enough resources distributes to user i, then described money
The request of source scheduler refusal user i, step (7)；Otherwise calculate described candidate collection GiIn each cloud computation data center
Cost index T of relative cloud user ii,k,t,k∈Gi；
(5c) described candidate collection G is selectediDescribed in cost index Ti,k,tMinimum cloud computation data center k*Use for cloud
Family i disposes virtual machine；
(5d) surplus resources state L to the cloud computation data center selectingk,tIt is updated, step (7)；
(6) distributed mode is used to be that cloud user i disposes virtual machine, wherein
(6a) described Resource Scheduler searches described data center block of state, selects and meets cloud user i resource requirement Ri
(li,ni) cloud computation data center k*, L must be metk,t≥nili/ v, wherein, Lk,tFor surplus resources, niRepresent cloud user i institute
Need the quantity of virtual machine, liRepresenting the configuration of virtual machine needed for cloud user, v represents that cloud user i requires to dispose virtual machine respectively
In v cloud computation data center, these cloud computation data center constitute candidate collection G of user ii；
If the cloud computation data center number (6b) in candidate collection | Gi| ＜ v, represent and currently there is no enough cloud computings
Data center meets the resource requirement of cloud user i, the then request of Resource Scheduler refusal cloud user i, step (7)；Otherwise
Calculate described candidate collection GiIn cost index T of each cloud computation data center relatively described cloud user ii,k,t,k∈Gi；
(6c) in described candidate collection GiIn choose cost index Ti,k,tV minimum cloud computation data center constitutes setIn setIn this v cloud computation data center be cloud user i dispose virtual machine；
(6d) surplus resources state L to the cloud computation data center selectingk,tIt is updated, perform (7)；
(7) virtual machine is assigned, and described Resource Scheduler is to described cloud user's i feedback allocation result.
Need it is further noted that the renewal step in described step (2) includes:
When the status information of cloud computation data center changes, described cloud data center condition monitoring process reads to be worked as
Surplus resources L under front statek,tAnd resource price Pk,t, it is then sent to described Resource Scheduler, described Resource Scheduler
It is updated according to the status information to cloud computation data center corresponding in described data center block of state for the information receiving；
Described Resource Scheduler periodically tests signal to cloud computation data center transmission delay, and in described data
Heart block of state records the answer delay d of this test signalk,t, the transmission cycle of test signal is td, and whenever described resource
Scheduler receives also can be when this cloud computation data center sends one when the status information of a cloud computation data center
Delay test signal.
It should be noted that described resource price Pk,tThere is provided according to the following formula by described cloud data center condition monitoring process:
Pk,t=γ1Pk+γ2f(Lk,t)+γ3g(Dk,t)；
Wherein, k represents that cloud computation data center is numbered, and t represents current time, γiFor weight factor, Σ γi=1, PkIt is
The basic resources price of cloud computation data center k, is definite value, f (Lk,t) and g (Dk,t) it is to estimate with surplus yield and time delay respectively
In respect of the function closing.
It should be noted that the time delay of described cloud computation data center is estimated, such as following formula:
Wherein I represents length of window, and the average answer delay of I test signal is this cloud computation data center i.e. recently
Estimation time delay.
It should be noted that described cost index Ti,k,tCalculate according to below equation:
Ti,k,t=αiDk,t+βiPk,t；
Wherein, αi,βi∈ [0,1] represents time delay factor and the Price factor of cloud user i respectively, the time delay of different business because of
Son is different with Price factor, more sensitive to time delay or price, αiOr βiValue bigger；Dk,tAnd Pk,tRepresent t cloud computing respectively
The time delay of data center k is estimated and resource price.
The present invention has the beneficial effects that, solves under distributed cloud computing environment, and the cloud having different business characteristic is used
The resource allocation problem of family business, hence it is evident that reduce the cost of different business characteristic cloud user, and realize in different cloud computing data
Load balancing in the heart.
Brief description
Fig. 1 is the system architecture diagram of the present invention；
Fig. 2 is the flow chart of the inventive method.
Detailed description of the invention
Below in conjunction with accompanying drawing, the invention will be further described.
As it is shown in figure 1, the present invention is the resource allocation system under a kind of distributed cloud framework based on traffic performance, described system
System includes:
Resource Scheduler 1, the state computation of the requirement according to cloud user 2 and each cloud computation data center 3 show that cloud is used
The cost index of family 2 each cloud computation data center 3 relative, and be that virtual machine is disposed in its distribution according to the demand of cloud user 2；Institute
State Resource Scheduler 1 to may operate in certain cloud computation data center 3 of cloud computing platform；
Cloud data center condition monitoring process, sends the status information of place data center 3 to described Resource Scheduler 1,
Described cloud data center condition monitoring process operates in the monitoring process of cloud computation data center 3；
Data center's block of state, is for storing each cloud computation data center 3 status information in described Resource Scheduler 1
Module, according to cloud computation data center 3 report status information carry out real-time update, including cloud computation data center 3 when
Prolong the information of estimation, surplus resources and resource price.
As in figure 2 it is shown, the present invention to be embodied as step as follows:
(1) the cloud resource distribution system based on traffic performance is set up；Receive asking from cloud user according to Resource Scheduler
Ask, according to cloud data center condition monitoring process, monitor the state of the cloud computation data center at its place, and adjust to described resource
Degree device report, is cloud user resource allocation or the request of refusal cloud user according to the information in described report；
(2) renewal of cloud computation data center block of state is set up；Described cloud data center condition monitoring process is periodically
Ground is to the status information of Resource Scheduler report place cloud computation data center, and wherein, described status information includes surplus resources
Lk,t, price P of data center resourcek,tAnd the time delay estimation D of data centerk,t；
Need it is further noted that the renewal step in described step (2) includes:
When the status information of cloud computation data center changes, described cloud data center condition monitoring process reads to be worked as
Surplus resources L under front statek,tAnd resource price Pk,t, it is then sent to described Resource Scheduler, described Resource Scheduler
It is updated according to the status information to cloud computation data center corresponding in described data center block of state for the information receiving；
Described Resource Scheduler periodically tests signal to cloud computation data center transmission delay, and in described data
Heart block of state records the answer delay d of this test signalk,t, the transmission cycle of test signal is td, and whenever described resource
Scheduler receives also can be when this cloud computation data center sends one when the status information of a cloud computation data center
Delay test signal.
(3) cloud user submits cloud resource request R to Resource Scheduleri(li,ni,ci), li=li(f, m, h b) represent that cloud is used
The configuration of virtual machine needed for family, wherein, f represents dominant frequency, and m represents built-in storage, and h represents hard disk, and b represents bandwidth, niRepresent cloud
The quantity of virtual machine, c needed for user ii=(si,αi,βi) represent cloud user i traffic performance, wherein, siRepresent cloud user i institute
Need the deployment request of virtual machine, si=1 expression cloud user requires that virtual machine is concentrated and is deployed in a cloud computation data center, si
=v, (v ＞ 1) represents that cloud user requires deploying virtual machine in v cloud computation data center, αi,βi∈ [0,1] represents cloud respectively
The time delay factor of user i and Price factor, the time delay factor of different business is different with Price factor, quicker to time delay or price
Sense, αiOr βiValue bigger；
(4) if cloud user si=1, step (5)；If si=v, (v ＞ 1), step (6)；
(5) centralized mode is used to be that cloud user i disposes virtual machine, wherein
(5a) described Resource Scheduler searches described data center block of state, selects and meets cloud user i resource requirement Ri
(li,ni) cloud computation data center k*, L must be metk,t≥nili, and constitute candidate collection G of user ii；
If (5b) described candidate collection GiFor empty set, represent that currently there is no enough resources distributes to user i, then described money
The request of source scheduler refusal user i, step (7)；Otherwise calculate described candidate collection GiIn each cloud computation data center
Cost index T of relative cloud user ii,k,t,k∈Gi；
(5c) described candidate collection G is selectediDescribed in cost index Ti,k,tMinimum cloud computation data center k*Use for cloud
Family i disposes virtual machine；
(5d) surplus resources state L to the cloud computation data center selectingk,tIt is updated, step (7)；
(6) distributed mode is used to be that cloud user i disposes virtual machine, wherein
(6a) described Resource Scheduler searches described data center block of state, selects and meets cloud user i resource requirement Ri
(li,ni) cloud computation data center k*, L must be metk,t≥nili/ v, wherein, Lk,tFor surplus resources, niRepresent cloud user i institute
Need the quantity of virtual machine, liRepresenting the configuration of virtual machine needed for cloud user, v represents that cloud user requires to be deployed in virtual machine respectively
In v cloud computation data center, these cloud computation data center constitute candidate collection G of user ii；
If the cloud computation data center number (6b) in candidate collection | Gi| ＜ v, represent and currently there is no enough cloud computings
Data center meets the resource requirement of cloud user i, the then request of Resource Scheduler refusal cloud user i, step (7)；Otherwise
Calculate described candidate collection GiIn cost index T of each cloud computation data center relatively described cloud user ii,k,t,k∈Gi；
(6c) in described candidate collection GiIn choose cost index Ti,k,tV minimum cloud computation data center constitutes setIn setIn this v cloud computation data center be cloud user i dispose virtual machine；
(6d) surplus resources state L to the cloud computation data center selectingk,tIt is updated, perform (7)；
(7) virtual machine is assigned, and described Resource Scheduler is to described cloud user's i feedback allocation result.
It should be noted that described resource price Pk,tThere is provided according to the following formula by described cloud data center condition monitoring process:
Pk,t=γ1Pk+γ2f(Lk,t)+γ3g(Dk,t)；
Wherein, k represents that cloud computation data center is numbered, and t represents current time, γiFor weight factor, as Σ γi=1, Pk
It is the basic resources price of cloud computation data center k, be definite value, f (Lk,t) and g (Dk,t) be respectively and surplus yield and time delay
Estimate relevant function.
It should be noted that the time delay of described cloud computation data center is estimated, such as following formula:
Wherein I represents length of window, and the average answer delay of I test signal is this cloud computation data center i.e. recently
Estimation time delay.
It should be noted that described cost index Ti,k,tCalculate according to below equation:
Ti,k,t=αiDk,t+βiPk,t；
Wherein, αi,βi∈ [0,1] represents cloud user's i time delay factor and Price factor, the time delay factor of different business respectively
Different with Price factor, more sensitive to time delay or price, αiOr βiValue bigger；Dk,tAnd Pk,tRepresent t cloud computing number respectively
Estimate and resource price according to the time delay of center k.
Claims (5)
1. based on the distribution method of resource allocation system of traffic performance under distributed cloud framework, it is characterised in that described method
Comprise the following steps:
(1) the cloud resource distribution system based on traffic performance is set up；Receive the request from cloud user, root according to Resource Scheduler
According to cloud data center condition monitoring process, monitor the state of the cloud computation data center at its place, and to described Resource Scheduler
Report, is cloud user resource allocation or the request of refusal cloud user according to the information in described report；
(2) renewal of cloud computation data center block of state is set up；Described cloud data center condition monitoring process periodically to
The status information of Resource Scheduler report place cloud computation data center, wherein, described status information includes surplus resources Lk,t、
Price P of data center resourcek,tAnd the time delay estimation D of data centerk,t；K represents that cloud computation data center is numbered, and t represents
Current time；
(3) cloud user submits cloud resource request R to Resource Scheduleri(li,ni,ci), li=li(f, m, h b) represent cloud user institute
Needing the configuration of virtual machine, wherein, f represents dominant frequency, and m represents built-in storage, and h represents hard disk, and b represents bandwidth, niRepresent cloud user i
The quantity of required virtual machine, ci=(si,αi,βi) represent cloud user i traffic performance, wherein, siRepresent virtual needed for cloud user i
The deployment request of machine, si=1 expression cloud user requires that virtual machine is concentrated and is deployed in a cloud computation data center, si=v, (v
＞ 1) represent that cloud user requires that virtual machine is deployed in v cloud computation data center respectively, αi,βi∈ [0,1] represents that cloud is used respectively
The time delay factor of family i and Price factor, the time delay factor of different business is different with Price factor, more sensitive to time delay or price,
αiOr βiValue bigger；
(4) if cloud user si=1, step (5)；If si=v, (v ＞ 1), step (6)；
(5) centralized mode is used to be that cloud user i disposes virtual machine, wherein
(5a) described Resource Scheduler searches described data center block of state, selects and meets cloud user i resource requirement Ri(li,
ni) cloud computation data center k, L must be metk,t≥nili, and constitute candidate collection G of user ii；
If (5b) described candidate collection GiFor empty set, represent that currently there is no enough resources distributes to user i, then described resource is adjusted
The request of degree device refusal user i, step (7)；Otherwise calculate described candidate collection GiIn each cloud computation data center relative
Cost index T of cloud user ii,k,t,k∈Gi；
(5c) described candidate collection G is selectediDescribed in cost index Ti,k,tMinimum cloud computation data center k* is cloud user i portion
Administration's virtual machine；
(5d) surplus resources state L to the cloud computation data center selectingk,tIt is updated, step (7)；
(6) distributed mode is used to be that cloud user i disposes virtual machine, wherein
(6a) described Resource Scheduler searches described data center block of state, selects and meets cloud user i resource requirement Ri(li,
ni) cloud computation data center k, L must be metk,t≥nili/ v, wherein, Lk,tFor surplus resources, niRepresent empty needed for cloud user i
The quantity of plan machine, liRepresenting the configuration of virtual machine needed for cloud user, v represents that cloud user i requires to be deployed in virtual machine respectively v
In cloud computation data center, these cloud computation data center constitute candidate collection G of user ii；
If the cloud computation data center number (6b) in candidate collection | Gi| ＜ v, represent currently to there is no there is no enough cloud computing numbers
Meet the resource requirement of cloud user i, the then request of Resource Scheduler refusal cloud user i, step (7) according to center；Otherwise count
Calculate described candidate collection GiIn cost index T of each cloud computation data center relatively described cloud user ii,k,t,k∈Gi；
(6c) in described candidate collection GiIn choose cost index Ti,k,tV minimum cloud computation data center constitutes set
In setIn this v cloud computation data center be cloud user i dispose virtual machine；
(6d) surplus resources state L to the cloud computation data center selectingk,tIt is updated, perform (7)；
(7) virtual machine is assigned, and described Resource Scheduler is to described cloud user's i feedback allocation result.
2. based on the distribution method of resource allocation system of traffic performance under distributed cloud framework according to claim 1,
It is characterized in that, the renewal step in described step (2) includes:
When the status information of cloud computation data center changes, described cloud data center condition monitoring process reads current shape
Surplus resources L under statek,tAnd resource price Pk,t, be then sent to described Resource Scheduler, described Resource Scheduler according to
The status information to cloud computation data center corresponding in described data center block of state for the information receiving is updated；
Described Resource Scheduler periodically tests signal to cloud computation data center transmission delay, and at described data center shape
Morphotype block records the answer delay d of this test signalk,t, the transmission cycle of test signal is td, and whenever described scheduling of resource
Device receives and also can send a time delay survey to this cloud computation data center when the status information of a cloud computation data center
Trial signal.
3. based on the distribution side of resource allocation system of traffic performance under distributed cloud framework according to claim 1 and 2
Method, it is characterised in that described resource price Pk,tThere is provided according to the following formula by described cloud data center condition monitoring process:
Pk,t=γ1Pk+γ2f(Lk,t)+γ3g(Dk,t)；
Wherein, k represents that cloud computation data center is numbered, and t represents current time, γiFor weight factor, as ∑ γi=1, PkIt is cloud
Calculate the basic resources price of data center k, be definite value, f (Lk,t) and g (Dk,t) it is to estimate with surplus yield and time delay respectively
Relevant function.
4. based on the distribution method of resource allocation system of traffic performance under distributed cloud framework according to claim 2,
It is characterized in that, the time delay of described cloud computation data center is estimated, such as following formula:
Wherein I represents length of window, and the average answer delay of I test signal is the estimation of this cloud computation data center i.e. recently
Time delay.
5. based on the distribution method of resource allocation system of traffic performance under distributed cloud framework according to claim 1,
It is characterized in that, described cost index Ti,k,tCalculate according to below equation:
Ti,k,t=αiDk,t+βiPk,t；
Wherein, αi,βi∈ [0,1] represents cloud user's i time delay factor and Price factor, the time delay factor of different business and valency respectively
The lattice factor is different, more sensitive to time delay or price, αiOr βiValue bigger；Dk,tAnd Pk,tRepresent respectively in t cloud computing data
The time delay of heart k is estimated and resource price.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310342532.9A CN103401938B (en) | 2013-08-07 | 2013-08-07 | Based on resource allocation system and the method thereof of traffic performance under distributed cloud framework |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310342532.9A CN103401938B (en) | 2013-08-07 | 2013-08-07 | Based on resource allocation system and the method thereof of traffic performance under distributed cloud framework |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103401938A CN103401938A (en) | 2013-11-20 |
| CN103401938B true CN103401938B (en) | 2016-11-09 |
Family
ID=49565461
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310342532.9A Active CN103401938B (en) | 2013-08-07 | 2013-08-07 | Based on resource allocation system and the method thereof of traffic performance under distributed cloud framework |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103401938B (en) |
Families Citing this family (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103647823A (en) * | 2013-12-11 | 2014-03-19 | 浪潮电子信息产业股份有限公司 | Storage resource scheduling method in cloud computing operating system |
| CN103647824A (en) * | 2013-12-11 | 2014-03-19 | 浪潮电子信息产业股份有限公司 | Storage resource optimized scheduling and discovering algorithm |
| CN103747085A (en) * | 2014-01-10 | 2014-04-23 | 浪潮电子信息产业股份有限公司 | Storage resource scheduling algorithm under cloud computing operation system |
| CN103888542A (en) * | 2014-01-17 | 2014-06-25 | 汉柏科技有限公司 | Method and system for cloud computing resource allocation |
| CN103873460B (en) * | 2014-01-27 | 2017-08-25 | 华为技术有限公司 | Service resources group implementation method and device |
| CN104811467B (en) * | 2014-01-28 | 2018-07-06 | 青岛海尔电子有限公司 | The data processing method of aggreggate utility |
| CN105099950B (en) * | 2014-04-17 | 2018-08-14 | 华为技术有限公司 | A kind of resource allocation methods, message communication method and device |
| CN104601664B (en) * | 2014-12-22 | 2018-10-23 | 西安电子科技大学 | A kind of control system of cloud computing platform resource management and scheduling virtual machine |
| CN106464733B (en) * | 2015-04-28 | 2019-08-16 | 华为技术有限公司 | The method and device of virtual resource in a kind of adjustment cloud computing |
| CN105791447B (en) * | 2016-05-20 | 2019-03-01 | 北京邮电大学 | A kind of cloud resource dispatching method and device towards Video service |
| US10542100B2 (en) * | 2016-09-16 | 2020-01-21 | Oracle International Corporation | Systems and methodologies for defining and scheduling custom actions as cloud operations |
| CN106357800B (en) * | 2016-10-21 | 2020-06-05 | 黄东 | QoE-based cloud computing service architecture |
| CN106953895A (en) * | 2017-02-20 | 2017-07-14 | 中山大学 | A kind of distributed cloud system cluster of peering structure |
| CN110096337B (en) * | 2019-05-06 | 2021-01-05 | 燕山大学 | Cloud data center resource allocation method and system for enterprise application cloud deployment |
| CN110308989A (en) * | 2019-05-31 | 2019-10-08 | 中国科学院计算技术研究所 | A kind of resource management apparatus and method for OpenStack across data center |
| CN111796994B (en) * | 2019-11-20 | 2022-07-12 | 华为云计算技术有限公司 | Time delay guaranteeing method, system and device, computing equipment and storage medium |
| CN111988392B (en) * | 2020-08-14 | 2022-11-11 | 腾讯科技（深圳）有限公司 | Resource allocation method based on cloud service, related device, equipment and system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103152438A (en) * | 2013-04-09 | 2013-06-12 | 上海理想信息产业（集团）有限公司 | Method for obtaining business health degree under cloud computing environment |
| CN103220337A (en) * | 2013-03-22 | 2013-07-24 | 合肥工业大学 | Cloud computing resource optimizing collocation method based on self-adaptation elastic control |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7734778B2 (en) * | 2002-04-05 | 2010-06-08 | Sheng (Ted) Tai Tsao | Distributed intelligent virtual server |
-
2013
- 2013-08-07 CN CN201310342532.9A patent/CN103401938B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103220337A (en) * | 2013-03-22 | 2013-07-24 | 合肥工业大学 | Cloud computing resource optimizing collocation method based on self-adaptation elastic control |
| CN103152438A (en) * | 2013-04-09 | 2013-06-12 | 上海理想信息产业（集团）有限公司 | Method for obtaining business health degree under cloud computing environment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103401938A (en) | 2013-11-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103401938B (en) | Based on resource allocation system and the method thereof of traffic performance under distributed cloud framework | |
| CN104850450B (en) | A kind of load-balancing method and system towards mixed cloud application | |
| CN104283946B (en) | The resource-adaptive adjustment system and method for multi-dummy machine under a kind of single physical machine | |
| CN104756444B (en) | CDN load balances in cloud | |
| CN104756467B (en) | CDN traffic managements in cloud | |
| CN106155791B (en) | A kind of workflow task dispatching method under distributed environment | |
| CN107045455A (en) | A kind of Docker Swarm cluster resource method for optimizing scheduling based on load estimation | |
| CN106233276B (en) | The coordination admission control of network-accessible block storage device | |
| CN103067297B (en) | A kind of dynamic load balancing method based on resource consumption prediction and device | |
| US9483288B2 (en) | Method and system for running a virtual appliance | |
| CN103294546B (en) | The online moving method of virtual machine of multi-dimensional resource performance interference aware and system | |
| CN110047014A (en) | A kind of user's electricity data restorative procedure based on load curve and history electricity | |
| CN104168332A (en) | Load balance and node state monitoring method in high performance computing | |
| CN103064744B (en) | The method for optimizing resources that a kind of oriented multilayer Web based on SLA applies | |
| CN105718364A (en) | Dynamic assessment method for ability of computation resource in cloud computing platform | |
| CN109788489A (en) | A kind of base station planning method and device | |
| CN104902001A (en) | Method for load balancing of Web requests based on operating system virtualization | |
| WO2024094104A1 (en) | Dynamic feedback weighted cloud storage resource scheduling method, apparatus and device | |
| JP2012517639A (en) | Method and system for calculating charges online based on user service volume | |
| CN106301984A (en) | A kind of mobile communications network capacity prediction methods and device | |
| CN104978236A (en) | HDFS load source and sink node selection method based on multiple measurement indexes | |
| CN109901927A (en) | Intelligent Task dynamic scheduling system and its method | |
| CN107483292B (en) | Dynamic monitoring method for cloud platform | |
| CN104063265A (en) | Method for comprehensively evaluating virtual resources | |
| CN110096489A (en) | A kind of data query method, system, device and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20220713 Address after: 510700 room 1003, building 3, room 1004, building 3, room 1005, building 3, room 1006, building 3, No. 11, spectral Middle Road, Huangpu District, Guangzhou, Guangdong Province Patentee after: Yuedong (Guangdong) Information Technology Co.,Ltd. Address before: 710071 Xi'an Electronic and Science University, 2 Taibai South Road, Shaanxi, Xi'an Patentee before: XIDIAN University |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20221013 Address after: Unit 16, Floor 02, Building 3, Yunsheng Science Park, No. 11, Middle Spectra Road, Huangpu District, Guangzhou City, Guangdong Province, 510000 (office only) Patentee after: Guangzhou Lanka Technology Co.,Ltd. Address before: 510700 room 1003, building 3, room 1004, building 3, room 1005, building 3, room 1006, building 3, No. 11, spectral Middle Road, Huangpu District, Guangzhou, Guangdong Province Patentee before: Yuedong (Guangdong) Information Technology Co.,Ltd. |