CN103279385A - Method and system for scheduling cluster tasks in cloud computing environment - Google Patents

Method and system for scheduling cluster tasks in cloud computing environment Download PDF

Info

Publication number
CN103279385A
CN103279385A CN201310215619XA CN201310215619A CN103279385A CN 103279385 A CN103279385 A CN 103279385A CN 201310215619X A CN201310215619X A CN 201310215619XA CN 201310215619 A CN201310215619 A CN 201310215619A CN 103279385 A CN103279385 A CN 103279385A
Authority
CN
China
Prior art keywords
task
module
tasks
scheduling
carried
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
Application number
CN201310215619XA
Other languages
Chinese (zh)
Inventor
刘兴辉
王雪山
邵文韬
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
BEIJING TEAMSUN SOFTWARE TECHNOLOGY Co Ltd
Beijing Teamsun Technology Co Ltd
Original Assignee
BEIJING TEAMSUN SOFTWARE TECHNOLOGY Co Ltd
Beijing Teamsun Technology Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by BEIJING TEAMSUN SOFTWARE TECHNOLOGY Co Ltd, Beijing Teamsun Technology Co Ltd filed Critical BEIJING TEAMSUN SOFTWARE TECHNOLOGY Co Ltd
Priority to CN201310215619XA priority Critical patent/CN103279385A/en
Publication of CN103279385A publication Critical patent/CN103279385A/en
Pending legal-status Critical Current

Links

Abstract

The invention discloses a method and a system for scheduling cluster tasks in a cloud computing environment. The method includes steps that S1, a user operates on a management terminal, one or a plurality of cluster tasks are carried out by the aid of operation of a controller, and all the tasks are added into a task pool module; S2, the tasks in the task pool module are classified and decomposed by a task classification and analysis module; S3, decomposed tasks are added into a task queue module by a controller module; S4, a resource scheduling module takes out the tasks from the task queue module and schedules resources, and the tasks are scheduled to be executed by specified nodes; and S5, the target nodes execute the decomposed tasks and feed execution results to the controller module. The method and the system have the advantages that the tasks can be efficiently scheduled, and reliable running of a cluster system is guaranteed.

Description

Cluster task dispatching method and system in a kind of cloud computing environment
Technical field
The present invention relates to the computer information technology field, particularly cluster task dispatching method and system in a kind of cloud computing environment.
Background technology
Cloud computing can be made up of with the resource that is virtualized by dynamic update a series of, these resources are shared by the user of all cloud computings and can be easily by accesss to netwoks, the user need not to grasp the technology of cloud computing, only need lease the resource of cloud computing according to the needs of individual or group.
Cluster (cluster) technology is a kind of newer technology, by Clustering, can obtain in the higher relatively income aspect performance, reliability, the dirigibility paying under the situation of lower cost, and its task scheduling then is the core technology in the group system.Cluster be one group separate, by the interconnected computing machine of express network, they have constituted a group, and are managed with the pattern of triangular web.When client and cluster interacted, cluster similarly was an independently server.
Distributed Calculation is a computer science, the problem how its research could solve a very huge computing power of needs is divided into many little parts, then these parts are distributed to many computing machines and handle, these result of calculations are integrated obtain final result at last.
Task scheduling has different describing methods in different fields, and generally in distributed system, the fundamental element that constitutes scheduling has three, i.e. concurrent application, certain strategy of resource system and application call resource institute foundation and rule.Scheduling problem is exactly on the basis of satisfying concurrent application and resource system constraint condition, designs an efficient scheduling system and manages application program and how to call these resources, and make the total system performance index reach optimum or near-optimization.Task scheduling problem in the distributed system is exactly according to certain scheduling rule and scheduling strategy, a group job of a group task of forming concurrent program or formation operating load, be assigned on a plurality of computing nodes in the system, in the hope of obtaining system's feasibility preferably according to certain execution sequential.
Summary of the invention
The object of the present invention is to provide the method and system of cluster task scheduling in a kind of cloud computing environment, in order to realize task scheduling efficiently, ensure the reliability service of group system, prerequisite is under distributed computing environment, system is made up of a plurality of calculating nodes, if do not consider to calculate the performance difference between node, each calculates node can both carry out corresponding task.
According to an aspect of the present invention, provide cluster task dispatching method in a kind of cloud computing environment, may further comprise the steps:
S1, user operate at management end, utilize the controller module operation to carry out one or more cluster tasks, and task all is added in the task pool module;
S2, classification of task parsing module are classified to the task in the task pool module and are decomposed;
Task after S3, controller module will decompose adds the task queue module;
S4, scheduling of resource module are carried out scheduling of resource from task queue module taking-up task, and task scheduling is carried out to specified node;
S5, destination node are carried out the task after decomposing, and execution result is fed back to controller module.
Preferably, described classification of task parsing module is classified to the task in the task pool module according to task identification.
Preferably, described scheduling of resource module is taken out task with first in first out from the task queue module.
Preferably, could carry out after other task executions are finished if certain task depends on, then this task is waited in formation, has the task of dependence just to carry out the task scheduling execution after the task on the target computing node is complete.
Preferably, if the task after decomposing is a plurality of tasks that dependence is arranged, then execution result can be fed back respectively, having only all task action result all is successfully, could be set to success by originating task, if the previous tasks of dependence task is carried out failure, then follow-up work directly is arranged to failure and is removed from formation, and originating task is set to failure.
According to a further aspect in the invention, provide cluster task dispatching system in a kind of cloud computing environment, having comprised:
Controller module is used for receiving the user in the operation of management end, and one or more cluster tasks are carried out in operation, and task all is added in the task pool module; Task after the decomposition of classification of task parsing module is added in the task queue module; The receiving target node is carried out the task action result of decomposing the back task;
The task pool module is used for receiving the cluster task that controller module distributes;
The classification of task parsing module is for the task in the task pool module being classified and decomposing;
The task queue module is used under the control of controller module, receives the task after the classification of task parsing module decomposes;
The scheduling of resource module is used for carrying out scheduling of resource from task queue module taking-up task, and task scheduling is carried out to specified node.
Preferably, described classification of task parsing module is classified to the task in the task pool module according to task identification.
Preferably, described scheduling of resource module is taken out task with first in first out from the task queue module.
Preferably, could carry out after other task executions are finished if certain task depends on, then this task is waited in formation, has the task of dependence just to carry out the task scheduling execution after the task on the target computing node is complete.
Preferably, if the task after decomposing is a plurality of tasks that dependence is arranged, then execution result can be fed back respectively, having only all task action result all is successfully, could be set to success by originating task, if the previous tasks of dependence task is carried out failure, then follow-up work directly is arranged to failure and is removed from formation, and originating task is set to failure.
Description of drawings
Fig. 1 illustration cluster task dispatching method process flow diagram in a kind of cloud computing environment of providing of the embodiment of the invention;
Fig. 2 illustration the structural drawing of cluster task dispatching system in a kind of cloud computing environment of providing of the embodiment of the invention.
Embodiment
For above-mentioned purpose of the present invention, feature and advantage are become apparent more, the present invention is further detailed explanation below in conjunction with the drawings and specific embodiments.
Cluster task dispatching method in a kind of cloud computing environment that the embodiment of the invention provides may further comprise the steps:
S1, user operate at management end, utilize the controller module operation to carry out one or more cluster tasks, and task all is added in the task pool module;
S2, classification of task parsing module are classified to the task in the task pool module and are decomposed;
Wherein, for empty, can there be one or more tasks simultaneously when having task in the task pool module.Preferably, the classification of task parsing module is classified to the task in the task pool module according to task identification, it is the rule that the classification of task parsing module preestablishes task type identification and decomposes, decompose according to the task names task that identifies to carry out the classification back, according to decomposition rule task is decomposed, the task of decomposing is that one or more can specifically allowing carried out the specific tasks that destination host is carried out, if the task after decomposing is a plurality of subtasks, these a plurality of tasks of generalized case have dependence, and whether the execution of next task will rely on a task complete;
Task after S3, controller module will decompose adds the task queue module;
Wherein, if the user constantly assigns a task, after will constantly being decomposed, the task after the decomposition joins in the formation to be scheduled;
S4, scheduling of resource module are carried out scheduling of resource from task queue module taking-up task, and task scheduling is carried out to specified node;
Preferably, the scheduling of resource module is first in first out from the base rule of task queue module taking-up task;
Preferably, could carry out after other task executions are finished if certain task depends on, then this task is waited in formation, has the task of dependence just to carry out the task scheduling execution after the task on the target computing node is complete;
S5, destination node are carried out the task after decomposing, and execution result is fed back to controller module.
Preferably, if the task action result success, then controller module arranges success with originating task, if the task action result failure, then controller module is arranged to failure with originating task, and the executing state of originating task feeds back to the user at last.
Preferably, if the task after decomposing is a plurality of tasks that dependence is arranged, then execution result can be fed back respectively, having only all task action result all is successfully, could be set to success by originating task, if the previous tasks of dependence task is carried out failure, then follow-up work directly is arranged to failure and is removed from formation, and originating task is set to failure.
Accompanying drawing 1 illustration cluster task dispatching method process flow diagram in a kind of cloud computing environment of providing of the embodiment of the invention, as shown in Figure 1, described method comprises step:
The user operates at management end, and one or more cluster tasks are carried out in operation, and task all is added in the task pool, will carry out a task at node A as the user, carries out two tasks in Node B, and three tasks of T1, T2 and T3 are added in the task pool;
Task pool has three tasks, the classification of task parsing module is classified to the task in the task pool and is decomposed, the classification of task parsing module is classified according to task identification, it is its rule that preestablishes task type identification and decompose, three tasks are respectively VMT_update, VMi_create and VMi_delete, VMT is different with the VMI classification, decompose according to the task names task that identifies to carry out the classification back, according to decomposition rule task is decomposed (resolving into two task t1 and t2 that dependence is arranged as vmi_create), t1 and t2 are the specific tasks that will be carried out by destination host, t1 relies on t2, and whether the execution of t2 will rely on a task t1 complete;
Task after controller module will decompose adds the task queue module, and the task of adding formation at present has u1, t1, t2, d1;
The scheduling of resource module is carried out scheduling of resource from task queue module taking-up task, task scheduling is carried out to specified node, the base rule that the scheduling of resource module is taken out task from the task queue module is the principle of first in first out, order is u1, t1, d1, the t2 task depends on could be carried out after the t1 task executions is finished, then the t2 task is waited in formation, and u1 carries out to the A node, and t1, t2, d2 carry out to the B node;
The A node is carried out the task u1 after decomposing, execution result is fed back to controller module, if the execution result of task u1 success, then controller module originating task T1 is set to success, if the execution result of task u1 failure, then controller module originating task T1 is set to failure, and the executing state of originating task T1 feeds back to the user at last.Task after T2 decomposes is a plurality of tasks that dependence is arranged, t1 and t2 execution result feed back one by one, having only all tasks to carry out all is success, originating task T2 could be arranged success, if the previous tasks t1 of dependence task carries out failure, then follow-up work t2 directly is arranged to failure and removes from formation, and the T2 originating task is set to failure.
Except said method, the embodiment of the invention also provides cluster task dispatching system in a kind of cloud computing environment.As shown in Figure 2, illustration the structural drawing of cluster task dispatching system in a kind of cloud computing environment of providing of the embodiment of the invention.
Cluster task dispatching system in a kind of cloud computing environment that the embodiment of the invention provides comprises:
Controller module is used for receiving the user in the operation of management end, and one or more cluster tasks are carried out in operation, and task all is added in the task pool module; Task after the decomposition of classification of task parsing module is added in the task queue module; The receiving target node is carried out the task action result of decomposing the back task;
The task pool module is used for receiving the cluster task that controller module distributes;
The classification of task parsing module is for the task in the task pool module being classified and decomposing;
Wherein, for empty, can there be one or more tasks simultaneously when having task in the task pool module.Preferably, the classification of task parsing module is classified to the task in the task pool module according to task identification, it is the rule that the classification of task parsing module preestablishes task type identification and decomposes, decompose according to the task names task that identifies to carry out the classification back, according to decomposition rule task is decomposed, the task of decomposing is that one or more can specifically allowing carried out the specific tasks that destination host is carried out, if the task after decomposing is a plurality of subtasks, these a plurality of tasks of generalized case have dependence, and whether the execution of next task will rely on a task complete;
The task queue module is used under the control of controller module, receives the task after the classification of task parsing module decomposes;
Wherein, if the user constantly assigns a task, after will constantly being decomposed, the task after the decomposition joins in the formation to be scheduled;
The scheduling of resource module is used for carrying out scheduling of resource from task queue module taking-up task, and task scheduling is carried out to specified node;
Preferably, the scheduling of resource module is first in first out from the base rule of task queue module taking-up task;
Preferably, if certain task depends on and could carry out after other task executions are finished then this task is waited in formation, there is the task of dependence just to carry out task scheduling after the task on the target computing node is complete and carries out.
Preferably, if the task action result success, then controller module arranges success with originating task, if the task action result failure, then controller module is arranged to failure with originating task, and the executing state of originating task feeds back to the user at last.
Preferably, if the task after decomposing is a plurality of tasks that dependence is arranged, then execution result can be fed back respectively, having only all task action result all is successfully, could be set to success by originating task, if the previous tasks of dependence task is carried out failure, then follow-up work directly is arranged to failure and is removed from formation, and originating task is set to failure.
It more than is the detailed description that the preferred embodiments of the present invention are carried out, but those of ordinary skill in the art is to be appreciated that, within the scope of the present invention, and guided by the spirit, various improvement, interpolation and replacement all are possible, for example use that the different programming language (as C, C++, Java etc.) of algorithm, use that can realize functional purpose of the same race is realized etc.These are all in the protection domain that claim of the present invention limits.

Claims (10)

1. cluster task dispatching method in the cloud computing environment may further comprise the steps:
S1, user operate at management end, utilize the controller module operation to carry out one or more cluster tasks, and task all is added in the task pool module;
S2, classification of task parsing module are classified to the task in the task pool module and are decomposed;
Task after S3, controller module will decompose adds the task queue module;
S4, scheduling of resource module are carried out scheduling of resource from task queue module taking-up task, and task scheduling is carried out to specified node;
S5, destination node are carried out the task after decomposing, and execution result is fed back to controller module.
2. the method for claim 1 is characterized in that, described classification of task parsing module is classified to the task in the task pool module according to task identification.
3. the method for claim 1 is characterized in that, described scheduling of resource module is taken out task with first in first out from the task queue module.
4. the method for claim 1, it is characterized in that, could carry out after other task executions are finished if certain task depends on, then this task is waited in formation, has the task of dependence just to carry out the task scheduling execution after the task on the target computing node is complete.
5. the method for claim 1, it is characterized in that, if the task after decomposing is a plurality of tasks that dependence is arranged, then execution result can be fed back respectively, having only all task action result all is successfully, could be set to success by originating task, if the previous tasks of dependence task is carried out failure, then follow-up work directly is arranged to failure and is removed from formation, and originating task is set to failure.
6. cluster task dispatching system in the cloud computing environment comprises:
Controller module is used for receiving the user in the operation of management end, and one or more cluster tasks are carried out in operation, and task all is added in the task pool module; Task after the decomposition of classification of task parsing module is added in the task queue module; The receiving target node is carried out the task action result of decomposing the back task;
The task pool module is used for receiving the cluster task that controller module distributes;
The classification of task parsing module is for the task in the task pool module being classified and decomposing;
The task queue module is used under the control of controller module, receives the task after the classification of task parsing module decomposes;
The scheduling of resource module is used for carrying out scheduling of resource from task queue module taking-up task, and task scheduling is carried out to specified node.
7. system as claimed in claim 6 is characterized in that, described classification of task parsing module is classified to the task in the task pool module according to task identification.
8. system as claimed in claim 6 is characterized in that, described scheduling of resource module is taken out task with first in first out from the task queue module.
9. system as claimed in claim 6, it is characterized in that, could carry out after other task executions are finished if certain task depends on, then this task is waited in formation, has the task of dependence just to carry out the task scheduling execution after the task on the target computing node is complete.
10. system as claimed in claim 6, it is characterized in that, if the task after decomposing is a plurality of tasks that dependence is arranged, then execution result can be fed back respectively, having only all task action result all is successfully, could be set to success by originating task, if the previous tasks of dependence task is carried out failure, then follow-up work directly is arranged to failure and is removed from formation, and originating task is set to failure.
CN201310215619XA 2013-06-01 2013-06-01 Method and system for scheduling cluster tasks in cloud computing environment Pending CN103279385A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201310215619XA CN103279385A (en) 2013-06-01 2013-06-01 Method and system for scheduling cluster tasks in cloud computing environment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201310215619XA CN103279385A (en) 2013-06-01 2013-06-01 Method and system for scheduling cluster tasks in cloud computing environment

Publications (1)

Publication Number Publication Date
CN103279385A true CN103279385A (en) 2013-09-04

Family

ID=49061920

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201310215619XA Pending CN103279385A (en) 2013-06-01 2013-06-01 Method and system for scheduling cluster tasks in cloud computing environment

Country Status (1)

Country Link
CN (1) CN103279385A (en)

Cited By (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103942109A (en) * 2014-05-04 2014-07-23 江苏物联网研究发展中心 Self-adaptation task scheduling method based on multi-core DSP
CN104657212A (en) * 2015-02-13 2015-05-27 北京亚信数据有限公司 Task scheduling method and system
CN104750549A (en) * 2015-04-13 2015-07-01 飞狐信息技术(天津)有限公司 Computational task processing device, method and system
CN104965689A (en) * 2015-05-22 2015-10-07 浪潮电子信息产业股份有限公司 Hybrid parallel computing method and device for CPUs/GPUs
CN105224396A (en) * 2015-10-14 2016-01-06 深圳市金证科技股份有限公司 A kind of business data processing method and device
CN105260242A (en) * 2015-10-29 2016-01-20 无锡天脉聚源传媒科技有限公司 Task processing method and device
CN105589745A (en) * 2015-12-18 2016-05-18 中国科学院软件研究所 Unbalanced task allocation supported dynamic vulnerability discovery system and method
CN105930246A (en) * 2016-04-08 2016-09-07 天翼阅读文化传播有限公司 High available database monitoring method capable of intelligently distributing tasks
WO2016206564A1 (en) * 2015-06-26 2016-12-29 阿里巴巴集团控股有限公司 Operation scheduling method, device and distribution system
CN106502798A (en) * 2016-11-15 2017-03-15 合肥工业大学 A kind of task scheduling system and method suitable for portable medical
CN107491347A (en) * 2016-06-12 2017-12-19 阿里巴巴集团控股有限公司 A kind of method and apparatus for live migration of virtual machine
CN107735771A (en) * 2015-06-09 2018-02-23 机械地带有限公司 Distributed expandable workload is tested
CN107766136A (en) * 2017-09-30 2018-03-06 南威软件股份有限公司 A kind of method of task cluster management and running
CN107943577A (en) * 2016-10-12 2018-04-20 百度在线网络技术(北京)有限公司 Method and apparatus for scheduler task
CN108182111A (en) * 2018-01-23 2018-06-19 百度在线网络技术(北京)有限公司 Task scheduling system, method and apparatus
CN108449383A (en) * 2018-02-11 2018-08-24 西南电子技术研究所(中国电子科技集团公司第十研究所) Distributed thin cloud computing system mobile in real time
CN108762932A (en) * 2018-05-31 2018-11-06 安徽四创电子股份有限公司 A kind of cluster task scheduling system and processing method
CN108985629A (en) * 2018-07-17 2018-12-11 阿里巴巴集团控股有限公司 The execution method, apparatus and server of service node in business chain
CN109003429A (en) * 2018-08-14 2018-12-14 瑞斯康微电子(深圳)有限公司 A kind of meter register method and device in task based access control pond
CN109144744A (en) * 2017-06-28 2019-01-04 北京京东尚科信息技术有限公司 Task processing system, method and apparatus
CN109857557A (en) * 2019-01-16 2019-06-07 北京明略软件系统有限公司 The distributed computing method and system, computer readable storage medium of relationship discovery
CN110347514A (en) * 2017-01-20 2019-10-18 腾讯科技(深圳)有限公司 Event-handling method and device
CN112101891A (en) * 2020-07-30 2020-12-18 杭州正策信息科技有限公司 Data processing method applied to project declaration system
WO2021120550A1 (en) * 2019-12-19 2021-06-24 Huawei Technologies Co., Ltd. Methods and apparatus for resource scheduling of resource nodes of a computing cluster or a cloud computing platform

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101261591A (en) * 2008-04-28 2008-09-10 艾诺通信系统(苏州)有限责任公司 Multi- nuclear DSP system self-adapting task scheduling method
CN101951411A (en) * 2010-10-13 2011-01-19 戴元顺 Cloud scheduling system and method and multistage cloud scheduling system
CN101986272A (en) * 2010-11-05 2011-03-16 北京大学 Task scheduling method under cloud computing environment
CN102508716A (en) * 2011-09-29 2012-06-20 用友软件股份有限公司 Task control device and task control method
CN102902573A (en) * 2012-09-20 2013-01-30 北京搜狐新媒体信息技术有限公司 Task processing method and device based on shared resources

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101261591A (en) * 2008-04-28 2008-09-10 艾诺通信系统(苏州)有限责任公司 Multi- nuclear DSP system self-adapting task scheduling method
CN101951411A (en) * 2010-10-13 2011-01-19 戴元顺 Cloud scheduling system and method and multistage cloud scheduling system
CN101986272A (en) * 2010-11-05 2011-03-16 北京大学 Task scheduling method under cloud computing environment
CN102508716A (en) * 2011-09-29 2012-06-20 用友软件股份有限公司 Task control device and task control method
CN102902573A (en) * 2012-09-20 2013-01-30 北京搜狐新媒体信息技术有限公司 Task processing method and device based on shared resources

Cited By (32)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103942109A (en) * 2014-05-04 2014-07-23 江苏物联网研究发展中心 Self-adaptation task scheduling method based on multi-core DSP
CN103942109B (en) * 2014-05-04 2017-02-15 江苏物联网研究发展中心 Self-adaptation task scheduling method based on multi-core DSP
CN104657212B (en) * 2015-02-13 2018-02-16 北京亚信数据有限公司 A kind of method and system of task scheduling
CN104657212A (en) * 2015-02-13 2015-05-27 北京亚信数据有限公司 Task scheduling method and system
CN104750549A (en) * 2015-04-13 2015-07-01 飞狐信息技术(天津)有限公司 Computational task processing device, method and system
CN104965689A (en) * 2015-05-22 2015-10-07 浪潮电子信息产业股份有限公司 Hybrid parallel computing method and device for CPUs/GPUs
CN107735771A (en) * 2015-06-09 2018-02-23 机械地带有限公司 Distributed expandable workload is tested
US10521268B2 (en) 2015-06-26 2019-12-31 Alibaba Group Holding Limited Job scheduling method, device, and distributed system
WO2016206564A1 (en) * 2015-06-26 2016-12-29 阿里巴巴集团控股有限公司 Operation scheduling method, device and distribution system
CN105224396B (en) * 2015-10-14 2019-10-18 深圳市金证科技股份有限公司 A kind of business data processing method and device
CN105224396A (en) * 2015-10-14 2016-01-06 深圳市金证科技股份有限公司 A kind of business data processing method and device
CN105260242A (en) * 2015-10-29 2016-01-20 无锡天脉聚源传媒科技有限公司 Task processing method and device
CN105589745A (en) * 2015-12-18 2016-05-18 中国科学院软件研究所 Unbalanced task allocation supported dynamic vulnerability discovery system and method
CN105930246A (en) * 2016-04-08 2016-09-07 天翼阅读文化传播有限公司 High available database monitoring method capable of intelligently distributing tasks
CN107491347B (en) * 2016-06-12 2021-04-27 阿里巴巴集团控股有限公司 Method and equipment for virtual machine live migration
CN107491347A (en) * 2016-06-12 2017-12-19 阿里巴巴集团控股有限公司 A kind of method and apparatus for live migration of virtual machine
CN107943577A (en) * 2016-10-12 2018-04-20 百度在线网络技术(北京)有限公司 Method and apparatus for scheduler task
US10409639B2 (en) 2016-11-15 2019-09-10 Hefei University Of Technology Task scheduling system with a work breakdown structure and method suitable for mobile health
CN106502798A (en) * 2016-11-15 2017-03-15 合肥工业大学 A kind of task scheduling system and method suitable for portable medical
CN106502798B (en) * 2016-11-15 2017-09-22 合肥工业大学 A kind of task scheduling system and method suitable for portable medical
CN110347514A (en) * 2017-01-20 2019-10-18 腾讯科技(深圳)有限公司 Event-handling method and device
CN109144744A (en) * 2017-06-28 2019-01-04 北京京东尚科信息技术有限公司 Task processing system, method and apparatus
CN107766136A (en) * 2017-09-30 2018-03-06 南威软件股份有限公司 A kind of method of task cluster management and running
CN108182111A (en) * 2018-01-23 2018-06-19 百度在线网络技术(北京)有限公司 Task scheduling system, method and apparatus
CN108449383A (en) * 2018-02-11 2018-08-24 西南电子技术研究所(中国电子科技集团公司第十研究所) Distributed thin cloud computing system mobile in real time
CN108762932A (en) * 2018-05-31 2018-11-06 安徽四创电子股份有限公司 A kind of cluster task scheduling system and processing method
CN108985629A (en) * 2018-07-17 2018-12-11 阿里巴巴集团控股有限公司 The execution method, apparatus and server of service node in business chain
CN109003429A (en) * 2018-08-14 2018-12-14 瑞斯康微电子(深圳)有限公司 A kind of meter register method and device in task based access control pond
CN109857557A (en) * 2019-01-16 2019-06-07 北京明略软件系统有限公司 The distributed computing method and system, computer readable storage medium of relationship discovery
WO2021120550A1 (en) * 2019-12-19 2021-06-24 Huawei Technologies Co., Ltd. Methods and apparatus for resource scheduling of resource nodes of a computing cluster or a cloud computing platform
CN112101891A (en) * 2020-07-30 2020-12-18 杭州正策信息科技有限公司 Data processing method applied to project declaration system
CN112101891B (en) * 2020-07-30 2021-05-04 杭州正策信息科技有限公司 Data processing method applied to project declaration system

Similar Documents

Publication Publication Date Title
CN103279385A (en) Method and system for scheduling cluster tasks in cloud computing environment
CN102508639B (en) Distributed parallel processing method based on satellite remote sensing data characteristics
Fakhfakh et al. Workflow scheduling in cloud computing: a survey
Nanduri et al. Job aware scheduling algorithm for mapreduce framework
CN102387173A (en) MapReduce system and method and device for scheduling tasks thereof
CN102012840A (en) Batch data scheduling method and system
CN102662725A (en) Event-driven high concurrent process virtual machine realization method
De et al. Task management in the new ATLAS production system
CN103685492A (en) Dispatching method, dispatching device and application of Hadoop trunking system
Djebbar et al. Optimization of tasks scheduling by an efficacy data placement and replication in cloud computing
CN104778235A (en) Tree traversal searching method based on MapReduce cloud calculation model
CN104102533A (en) Bandwidth aware based Hadoop scheduling method and system
CN102253837A (en) Object tree-based software framework designing technology
Malathy et al. Performance improvement in cloud computing using resource clustering
CN102214094A (en) Executing operations via asynchronous programming model
CN104008001B (en) Virtual machine dynamic migrating method applied to mass data support
Priya et al. A survey on multiprocessor scheduling using evolutionary technique
Cicerre et al. A hierarchical process execution support for grid computing
KR101556541B1 (en) Apparatus and method for complex event processing based high load path
Zhou et al. Resource allocation in cloud computing based on clustering method
Gargiulo et al. A multi-agent and dynamic programming algorithm for aeronautical maintenance planning
Xue et al. Research and design of performance monitoring tool for hadoop clusters
Lin et al. Tree-based task scheduling model and dynamic load-balancing algorithm for P2P computing
Shakil et al. A latency-aware max-min algorithm for resource allocation in cloud
Sun et al. The Optimization of Hadoop Scheduling Algorithms on Distributed System for Processing Traffic Information

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into 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: 20130904