CN107797870A - A kind of cloud computing data resource dispatching method - Google Patents
A kind of cloud computing data resource dispatching method Download PDFInfo
- Publication number
- CN107797870A CN107797870A CN201711104783.8A CN201711104783A CN107797870A CN 107797870 A CN107797870 A CN 107797870A CN 201711104783 A CN201711104783 A CN 201711104783A CN 107797870 A CN107797870 A CN 107797870A
- Authority
- CN
- China
- Prior art keywords
- task
- cloud
- scheduling
- priority
- computing
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5083—Techniques for rebalancing the load in a distributed system
- G06F9/5088—Techniques for rebalancing the load in a distributed system involving task migration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/48—Program initiating; Program switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
- G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
Abstract
The invention discloses a kind of cloud computing data resource dispatching method, establish the task and resource model in mixed cloud, the adaptively selected suitable scheduling resource of mission requirements that can be submitted according to user, higher task can be with priority scheduling to public cloud to be required to deadline, under equal conditions, private clound preferential principle is taken into account.This paper scheduling strategy is simple, is not related to complicated algorithm, workable.
Description
Technical Field
The invention relates to the field of cloud computing, in particular to a cloud computing data resource scheduling method.
Background
In the cloud computing environment, a virtualization technology is adopted, the server is wholly virtualized into a data resource pool, and due to the fact that the data resources are various and large in scale, cloud computing data resource scheduling becomes one of hot spots of cloud computing research. The hybrid cloud comprises a local private cloud and a public cloud with higher computing power, such as some applications requiring stronger computing power and storage power, or the private cloud resources are overloaded during peak hours, so that more application tasks cannot be processed simultaneously. However, how to balance and call the resources of the hybrid cloud is a problem, and many of the existing research methods focus on the scheduling problem of a single cloud in the hybrid cloud. The present patent will address these issues, from the perspective of the user, and study scheduling issues in the hybrid cloud for differences in the user's demand for deadline. The scheduling method provided by the patent is simple, does not relate to differential and integral operation, and is relatively low in complexity.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a cloud computing data resource scheduling method, which solves the problems of complex computation and single-sided cloud scheduling in the existing hybrid cloud scheduling.
In order to achieve the above purpose, the invention adopts the following technical scheme: a cloud computing data resource scheduling method is characterized by comprising the following steps: the method comprises the following steps:
1) Resource description:
defining public cloud resources: r is u Comprises the following steps:
R u ＝<C u ,L u > (1)
wherein, C u Computing capacity of public cloud resources is achieved, and computing time of tasks is influenced; l is a radical of an alcohol u For transmission capacity, the transmission time of a task is influenced;
defining private cloud resources R r ：
R r ＝<C r ,L r > (2)
Wherein, C r The computing time of the task is influenced for the computing capacity of the private cloud resources; l is r The task transmission time is influenced for the transmission capability.
2) Task description:
task T i Is defined as:
Ti＝<Tλ i ,TD i ,TC i ,TL i > (3)
wherein, T lambda i A task priority weight value; TD i Is the deadline of the task; TC (tungsten carbide) i Is the task size; TL i Calculating the required information amount for the task;
3) The scheduling constraint describes:
computing task T i Completion time t in public cloud and private cloud, respectively i R u 、t i R r The following were used:
4) A priority scheduling strategy:
the priority scheduling policy is: firstly, scheduling task priority weighted value T lambda preferentially i The method comprises the following steps of firstly judging the completion time of a task on public and private cloud resources, dispatching the task to the resource capable of being completed as early as possible, considering the principle of priority of the private cloud under the same condition, and constraining and describing the following formula:
minimum time formula:
public cloud deadline constraints:
private cloud deadline constraints:
the cloud computing data resource scheduling method is characterized in that: the task size in the formula (3) is the task code amount.
The cloud computing data resource scheduling method is characterized in that: the priority principle of the private cloud is as follows: and if the completion time of the public cloud is the same as or similar to that of the private cloud, the task is preferentially scheduled to the private cloud, otherwise, the task is scheduled to the public cloud.
The cloud computing data resource scheduling method is characterized in that: the cloud computing data resource scheduling model comprises a user interface, a task request manager and a scheduling manager; the user interface is used for sending a task request submitted by a user to the request manager, the task request manager is used for transmitting task request information to the scheduling manager, the scheduling manager schedules the task to the public cloud or the private cloud by using a hybrid cloud scheduling method according to task requirements and in combination with resource information of the public cloud and the private cloud stored in the scheduling manager, and the result is returned to the user after the task processing is completed.
The cloud computing data resource scheduling method is characterized in that: the task request information comprises a priority weight value, a task size, a required data volume and a required completion deadline.
The cloud computing data resource scheduling method is characterized in that: the information of the public cloud and the private cloud resources comprises the computing capacity and the transmission capacity of the resources.
The invention achieves the following beneficial effects: according to the method, the task deadline is used as a priority strategy, a task and resource model in the hybrid cloud is established, tasks with higher requirements on the deadline can be preferentially scheduled to the public cloud, and the deadline constraint is met; the scheduling strategy is simple, does not relate to a complex algorithm, and has strong operability.
Drawings
Fig. 1 is a schematic diagram of a cloud computing data resource scheduling model according to the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in fig. 1, a cloud computing data resource scheduling model includes a user interface, a task request manager, and a scheduling manager; the user interface is used for sending a task request submitted by a user to the task request manager, the task request manager is used for transmitting task request information to the scheduling manager, the scheduling manager schedules the task to the public cloud or the private cloud according to task requirements and by combining resource information of the public cloud and the private cloud stored in the scheduling manager, and the cloud computing data resource scheduling method is used for returning a result to the user after task processing is completed.
The task request information comprises task weight, task size, required data volume, required completion deadline and the like; the information of the public cloud resource and the private cloud resource comprises the computing capacity, the transmission capacity and the like of the two resources.
A scheduling method based on the cloud computing data resource scheduling model,
1) Resource description:
resources in the hybrid cloud are divided into public cloud resources and private cloud resources, and the resources mainly represent virtual machines.
Defining public cloud resources: r u Comprises the following steps:
R u ＝<C u ,L u > (1)
wherein, C u Computing capacity of public cloud resources is achieved, and computing time of tasks is influenced; l is u The transmission time of a task is influenced for the transmission capability.
Defining private cloud resources R r ：
R r ＝<C r ,L r > (2)
Wherein, C r The computing time of the task is influenced for the computing capacity of the private cloud resources; l is r The task transmission time is influenced for the transmission capability.
2) Task description:
task setting T i For one unit of task request, each resource processes one task at a time, then task T i Is defined as:
Ti＝<Tλ i ,TD i ,TC i ,TL i > (3)
wherein, T λ i The task priority weight value can be divided into a plurality of importance levels according to the importance degree of the task, the weight values are respectively set, and the task is processed with priority with high priority; TD (time division) i Is the deadline of the task; TC (tungsten carbide) i Is the task size; TL i The amount of information needed is calculated for the task.
3) The scheduling constraint describes:
according to task definition, a deadline constraint exists in task scheduling, and the completion time of a task in a hybrid cloud scheduling model must be calculated to meet the constraint.
Task T can be calculated by definition of task and hybrid cloud resource i Completion time t in public cloud and private cloud, respectively i R u 、t i R r The following were used:
the cutoff constraint is t i R u ≤TD i And t i R r ≤TD i 。
4) Deadline-first scheduling policy:
the deadline first scheduling policy is to preferentially schedule a task to a resource that completes the task faster. Firstly, the completion time of the task on public and private cloud resources is judged, the task is scheduled to the resource which can be completed as soon as possible, and the principle of private cloud priority is considered under the same condition. The associated optimization and constraints are described by the following equations:
minimum time formula:
public cloud deadline constraints:
private cloud deadline constraints:
the task request manager firstly schedules the task priority weighted value T lambda preferentially i The method comprises the steps of firstly judging the completion time of a task on public and private cloud resources, scheduling the task to the resource which can be completed as soon as possible, and giving consideration to the principle of priority of the private cloud under the same condition. The scheduling method provided by the invention is simple and practical, only needs to carry out condition judgment on the task, does not relate to integral differential operation, and has algorithm complexity.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (6)
1. A cloud computing data resource scheduling method is characterized in that: the method comprises the following steps:
1) Resource description:
defining public cloud resources: r u Comprises the following steps:
R u ＝＜C u ,L u ＞ (1)
wherein, C u Computing capacity of public cloud resources is achieved, and computing time of tasks is influenced; l is u The transmission time of the task is influenced for the transmission capacity;
defining privacyCloud resource R r ：
R r ＝＜C r ,L r ＞ (2)
Wherein, C r The computing time of the task is influenced for the computing capacity of the private cloud resources; l is r The task transmission time is influenced for the transmission capability.
2) And (3) task description:
task T i Is defined as follows:
Ti＝＜Tλ i ,TD i ,TC i ,TL i ＞ (3)
wherein, T λ i A task priority weight value; TD i Is the deadline of the task; TC (tungsten carbide) i Is the task size; TL i Calculating the required information amount for the task;
3) The scheduling constraint describes:
computing task T i Completion time t in public cloud and private cloud, respectively i R u 、t i R r The following were used:
4) A priority scheduling strategy:
the priority scheduling policy is: firstly, scheduling task priority weighted value T lambda in priority i The method comprises the following steps of firstly judging the completion time of a task on public and private cloud resources, dispatching the task to the resource capable of being completed as early as possible, considering the principle of priority of the private cloud under the same condition, and constraining and describing the following formula:
minimum time formula:
public cloud deadline constraints:
private cloud deadline constraints:
2. the method for scheduling the cloud computing data resources according to claim 1, wherein: the task size in the formula (3) is the task code amount.
3. The method for scheduling the cloud computing data resources according to claim 1, wherein: the priority principle of the private cloud is as follows: and if the completion time of the public cloud is the same as or similar to that of the private cloud, the task is preferentially scheduled to the private cloud, otherwise, the task is scheduled to the public cloud.
4. The cloud computing data resource scheduler of claim 1, wherein: the cloud computing data resource scheduling model comprises a user interface, a task request manager and a scheduling manager; the user interface is used for sending a task request submitted by a user to the request manager, the task request manager is used for transmitting task request information to the scheduling manager, the scheduling manager schedules the task to the public cloud or the private cloud by using a hybrid cloud scheduling method according to task requirements and in combination with resource information of the public cloud and the private cloud stored in the scheduling manager, and the result is returned to the user after the task processing is completed.
5. The method for scheduling the cloud computing data resources according to claim 4, wherein: the task request information comprises a priority weight value, a task size, a required data volume and a required completion deadline.
6. The method for scheduling the cloud computing data resources according to claim 4, wherein: the information of the public cloud and the private cloud resources comprises the computing capacity and the transmission capacity of the resources.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711104783.8A CN107797870A (en) | 2017-11-10 | 2017-11-10 | A kind of cloud computing data resource dispatching method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711104783.8A CN107797870A (en) | 2017-11-10 | 2017-11-10 | A kind of cloud computing data resource dispatching method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107797870A true CN107797870A (en) | 2018-03-13 |
Family
ID=61534784
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711104783.8A Pending CN107797870A (en) | 2017-11-10 | 2017-11-10 | A kind of cloud computing data resource dispatching method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107797870A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2021097778A1 (en) * | 2019-11-21 | 2021-05-27 | 苏州铭冠软件科技有限公司 | Cloud computing data resource scheduling method |
| WO2022041271A1 (en) * | 2020-08-31 | 2022-03-03 | 苏州铭冠软件科技有限公司 | Cloud data resource scheduling method considering time and expense in rail transit applications |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104102544A (en) * | 2014-06-30 | 2014-10-15 | 武汉理工大学 | Multi QoS (quality of service)-constrained parallel task scheduling cost optimizing method under mixed cloud environment |
| CN104657220A (en) * | 2015-03-12 | 2015-05-27 | 广东石油化工学院 | Model and method for scheduling for mixed cloud based on deadline and cost constraints |
| CN104902005A (en) * | 2015-04-13 | 2015-09-09 | 中国联合网络通信集团有限公司 | Method and system for resource scheduling in hybrid cloud, and private cloud |
| CN106603438A (en) * | 2016-12-21 | 2017-04-26 | 云南电网有限责任公司信息中心 | Cost-based hybrid cloud resource utilization and distribution evaluation method |
| CN107292419A (en) * | 2017-05-22 | 2017-10-24 | 四川大学 | The Cost Optimization strategy that dynamic Multi-workflow scheduling is performed in a kind of mixing cloud environment |
-
2017
- 2017-11-10 CN CN201711104783.8A patent/CN107797870A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104102544A (en) * | 2014-06-30 | 2014-10-15 | 武汉理工大学 | Multi QoS (quality of service)-constrained parallel task scheduling cost optimizing method under mixed cloud environment |
| CN104657220A (en) * | 2015-03-12 | 2015-05-27 | 广东石油化工学院 | Model and method for scheduling for mixed cloud based on deadline and cost constraints |
| CN104902005A (en) * | 2015-04-13 | 2015-09-09 | 中国联合网络通信集团有限公司 | Method and system for resource scheduling in hybrid cloud, and private cloud |
| CN106603438A (en) * | 2016-12-21 | 2017-04-26 | 云南电网有限责任公司信息中心 | Cost-based hybrid cloud resource utilization and distribution evaluation method |
| CN107292419A (en) * | 2017-05-22 | 2017-10-24 | 四川大学 | The Cost Optimization strategy that dynamic Multi-workflow scheduling is performed in a kind of mixing cloud environment |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2021097778A1 (en) * | 2019-11-21 | 2021-05-27 | 苏州铭冠软件科技有限公司 | Cloud computing data resource scheduling method |
| WO2022041271A1 (en) * | 2020-08-31 | 2022-03-03 | 苏州铭冠软件科技有限公司 | Cloud data resource scheduling method considering time and expense in rail transit applications |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20190324819A1 (en) | Distributed-system task assignment method and apparatus | |
| US10223165B2 (en) | Scheduling homogeneous and heterogeneous workloads with runtime elasticity in a parallel processing environment | |
| CN104657220B (en) | Scheduling model and method based on deadline and expense restriction in mixed cloud | |
| US10474504B2 (en) | Distributed node intra-group task scheduling method and system | |
| US20170346759A1 (en) | Optimizing placement of virtual machines | |
| CN110297699B (en) | Scheduling method, scheduler, storage medium and system | |
| CN109582448B (en) | Criticality and timeliness oriented edge calculation task scheduling method | |
| CN103338228A (en) | Cloud calculating load balancing scheduling algorithm based on double-weighted least-connection algorithm | |
| WO2013107012A1 (en) | Task processing system and task processing method for distributed computation | |
| CN108132827B (en) | Network slice resource mapping method, related equipment and system | |
| EP3537281B1 (en) | Storage controller and io request processing method | |
| CN103257896B (en) | A kind of Max-D job scheduling method under cloud environment | |
| US20170090962A1 (en) | Method for Mapping Between Virtual CPU and Physical CPU and Electronic Device | |
| CN108427602B (en) | Distributed computing task cooperative scheduling method and device | |
| CN111209091A (en) | Scheduling method of Spark task containing private data in mixed cloud environment | |
| WO2024021489A1 (en) | Task scheduling method and apparatus, and kubernetes scheduler | |
| CN103455375A (en) | Load-monitoring-based hybrid scheduling method under Hadoop cloud platform | |
| CN106201701A (en) | A kind of workflow schedule algorithm of band task duplication | |
| CN105373426A (en) | Method for memory ware real-time job scheduling of car networking based on Hadoop | |
| CN102402461A (en) | Balanced scheduling method based on operation scale | |
| CN107797870A (en) | A kind of cloud computing data resource dispatching method | |
| CN115640113A (en) | Multi-plane flexible scheduling method | |
| CN112099932A (en) | Optimal pricing method and system for soft-hard deadline task offloading in edge computing | |
| CN108121596A (en) | Data transmission method and device, storage medium, electronic equipment | |
| CN109189581B (en) | Job scheduling method and device |
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 |
Application publication date: 20180313 |
|
| RJ01 | Rejection of invention patent application after publication |