CN105868004B - Scheduling method and scheduling device of service system based on cloud computing - Google Patents
Scheduling method and scheduling device of service system based on cloud computing Download PDFInfo
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Abstract
The invention provides a scheduling method and a scheduling device of a service system based on cloud computing. Through the analysis of the historical load, the future service situation is predicted, and therefore the virtual machine scheduling is scientifically and efficiently carried out. The invention can simplify the scheduling algorithm of the multi-service cloud system, more directly and efficiently schedule the multi-service cloud system, reduce the complexity of the scheduling algorithm, reduce the scheduling 'jitter' problem caused by the traditional scheduling algorithm and avoid the problem of service system performance reduction caused by unnecessary virtual machine migration during service peak.
Description
Technical Field
The invention relates to a cloud computing resource scheduling method, in particular to a scheduling method and a scheduling device of a service system based on cloud computing.
Background
Value-added service systems of telecom operators, such as service systems of short message centers, multimedia message centers, WAP gateways and the like, are important sources of income of operators, so that the construction of the value-added service systems is always valued by the operators. In the traditional construction scheme, each set of value added service system uses a special server resource. For example, the server used by the multimedia message center is shared by the multimedia message center. The server used by the short message center is shared by the short message center. An obvious disadvantage of the independent chimney type construction method is that the physical server resource is wasted seriously.
With the development of virtualization and cloud computing technologies, the independent and chimney-type construction mode of the value-added service system is gradually replaced by a cloud computing mode. In the cloud computing mode, resources are pooled, that is, a physical server is virtualized into a plurality of virtual machines by a virtualization technology, and a service system is borne on the virtual machines. Thus, after the resources of the physical servers are pooled, a layer of virtualization layer is added, so that the coupling relation between the service system and the physical servers is decoupled, and the multiplexing of a group of physical servers by a plurality of service systems becomes possible. The multi-service cloud system constructed by using the cloud computing technology not only improves the utilization rate of resources, but also provides possibility for saving energy, reducing consumption and reducing operation and maintenance cost.
The traffic system of a telecom operator has obvious tidal characteristics, such as peak load due to the strong communication demand of people in the daytime, and very significant drop load due to the reduced communication demand of people at night. Therefore, the multi-service cloud system adopting the cloud computing technology often performs intelligent virtual machine scheduling by virtue of the virtualized migration characteristic, so as to achieve the effects of reducing power consumption and reducing cost. A typical solution in the prior art is to distribute all the virtual machines carrying traffic evenly in each server of the resource pool during the day, and the system carries the traffic peak with the best performance status. When the load is low at night, the virtual machines bearing the services are compressed and transferred to the minimum servers to operate, and meanwhile, the idle physical servers which do not operate the virtual machines are powered off or in a dormant mode, so that the consumption of the servers on electric energy is reduced, and the purpose of reducing the cost is achieved.
However, the problem of the existing scheduling algorithm is that global consideration is lacked, only the resource load condition at the scheduling time is considered, and the difference between different service loads of a service system is not considered, which may cause the problem of scheduling jitter caused by the occurrence of scheduling again in the middle operation process of the system.
Disclosure of Invention
The technical problem to be solved in the embodiments of the present invention is to provide a scheduling method and a scheduling apparatus for a cloud computing-based service system, so as to reduce the complexity of a scheduling algorithm and reduce the problem of scheduling jitter caused by a conventional scheduling algorithm.
In order to solve the above technical problem, a scheduling method of a cloud computing-based service system provided in an embodiment of the present invention includes:
when the service system is switched to a scene mode, acquiring a pre-stored mapping relation table between a virtual machine and a physical server of the service system in the scene mode, wherein the mapping relation table records the mapping relation between the virtual machine and the physical server, which is obtained by the service system being scheduled according to a preset virtual machine scheduling algorithm in the scene mode at the last time, and the scene mode corresponds to a periodic time period of the service system;
and scheduling the virtual machine of the service system to a corresponding physical server according to the mapping relation in the mapping relation table.
Wherein, in the method, the first step of the method,
when the service system is switched to the scene mode, if the mapping relation table in the scene mode is not stored, the resource occupation condition of each physical server in the service system is periodically collected, and the migration scheduling of the virtual machine is executed according to a preset virtual machine scheduling algorithm;
and recording and storing the mapping relation table in the scene mode according to the mapping relation between the virtual machine and the physical server after the migration scheduling.
In the above method, the scheduling the virtual machine of the service system to the corresponding physical server according to the mapping relationship in the mapping relationship table includes:
waking up the physical server recorded in the mapping relation table, and scheduling the virtual machine recorded in the mapping relation table to the corresponding physical server according to the mapping relation in the mapping relation table; and the number of the first and second groups,
and powering off or sleeping the rest physical servers in the service system except the physical servers recorded in the mapping relation table.
In the above method, after the step of scheduling the virtual machine of the service system to the corresponding physical server according to the mapping relationship in the mapping relationship table, the method further includes:
periodically collecting the resource occupation condition of each physical server in the service system, and executing migration scheduling of the virtual machine according to the resource occupation condition and a preset virtual machine scheduling algorithm;
and after the migration scheduling of the virtual machine is executed, updating the mapping relation table according to the mapping relation between the current virtual machine of the service system and the physical server.
Wherein, in the method, the first step of the method,
the working time period of the service system comprises busy hour time periods and idle time periods which are preset and periodically presented;
the executing migration scheduling of the virtual machine according to the resource occupation situation and a predetermined virtual machine scheduling algorithm comprises:
when the scene mode is a busy hour scene corresponding to the busy hour period, transferring a part of virtual machines on the physical server with the resource occupancy rate exceeding a preset threshold to the physical server with the lowest resource occupancy rate in the service system according to a load balancing algorithm;
and when the scene mode is an idle-time scene corresponding to the idle-time period, migrating the virtual machines of the service system to the physical servers with the least number according to a knapsack algorithm.
The embodiment of the invention also provides a scheduling device of a service system based on cloud computing, which comprises:
the system comprises an acquisition unit, a scheduling unit and a processing unit, wherein the acquisition unit is used for acquiring a mapping relation table which is stored in advance and is used between a virtual machine and a physical server of the service system in a scene mode when the service system is switched to the scene mode, the mapping relation table records the mapping relation between the virtual machine and the physical server which is obtained by the service system in the scene mode according to the scheduling algorithm of the preset virtual machine at the last time, and the scene mode corresponds to a periodic time period of the service system;
and the first scheduling unit is used for scheduling the virtual machine of the service system to the corresponding physical server according to the mapping relation in the mapping relation table.
Wherein, in the scheduling device, the method further comprises:
the second scheduling unit is used for periodically collecting the resource occupation condition of each physical server in the service system and executing migration scheduling of the virtual machine according to a preset virtual machine scheduling algorithm if the mapping relation table in the scene mode is not stored when the service system is switched to the scene mode;
and the first updating unit is used for recording and storing the mapping relation table in the scene mode according to the mapping relation between the virtual machine after the migration scheduling and the physical server.
In the scheduling apparatus, the first scheduling unit includes:
the migration unit is used for awakening the physical server recorded in the mapping relation table and scheduling the virtual machine recorded in the mapping relation table to the corresponding physical server according to the mapping relation in the mapping relation table; and the number of the first and second groups,
and the energy-saving unit is used for carrying out power-off or dormancy processing on the rest physical servers in the service system except the physical servers recorded in the mapping relation table.
Wherein, in the scheduling device, the method further comprises:
the third scheduling unit is used for periodically acquiring the resource occupation condition of each physical server in the service system and executing the migration scheduling of the virtual machine according to the resource occupation condition and a preset virtual machine scheduling algorithm; and after the migration scheduling of the virtual machine is executed, updating the mapping relation table according to the mapping relation between the current virtual machine of the service system and the physical server.
In the scheduling device, the working time period of the service system includes busy time periods and idle time periods which are preset and are periodically presented;
the second scheduling unit or the third scheduling unit is further configured to migrate, according to a load balancing algorithm, a part of virtual machines on the physical server whose resource occupancy rate exceeds a predetermined threshold to the physical server with the lowest resource occupancy rate in the service system when the scene mode is a busy hour scene corresponding to the busy hour period; and when the scene mode is an idle-time scene corresponding to the idle-time period, migrating the virtual machines of the service system to the physical servers with the least number according to a knapsack algorithm.
Compared with the prior art, the scheduling method and the scheduling device of the cloud computing-based service system provided by the embodiment of the invention can simplify the scheduling algorithm of the service cloud system, can directly and efficiently schedule the service system, reduce the complexity of the scheduling algorithm, reduce the problem of scheduling jitter caused by the traditional scheduling algorithm, reduce or avoid the problem of performance reduction of the service system caused by unnecessary virtual machine migration during service peak, and improve the stability of the service system.
Drawings
Fig. 1 is a schematic flowchart of a scheduling method based on a service system according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a scheduling apparatus based on a service system according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
The multi-service cloud system constructed by using the cloud computing technology not only improves the utilization rate of resources, but also provides possibility for saving energy, reducing consumption and reducing operation and maintenance cost. There are significant tidal characteristics in the telecommunications carrier's business system, and one scheduling scheme adopted for such tidal characteristics is to power up all servers as the load increases during the day. And then averagely migrating all the virtual machines bearing the services to each server in the system by using a load balancing scheduling principle. At night, the virtual machines are compressed to run on the fewest servers using an energy-efficient scheduling algorithm scheme, typically using a knapsack algorithm.
The scheduling scheme lacks global consideration, only considers the resource load condition at the scheduling time, does not consider the difference of service system load, and brings the problem of scheduling jitter caused by scheduling again in the middle operation process of the system. For example, it is assumed that when the service system spreads the virtual machines to all servers according to the principle of CPU balancing, the considered CPU load is only the CPU load at the scheduling time point. Over time, the load peaks of the various traffic systems will gradually come. Because the load of each service system is different, for example, the CPU utilization rate reaches 45% at the peak time when the virtual machine bears the multimedia message center; if the virtual machines of two short message centers are scheduled to a physical server to run when the CPU utilization rate reaches 55% at a peak time, when the traffic load peak comes, the virtual machines are likely to be triggered to be scheduled again, and one running virtual machine is scheduled away, for example, the multimedia message virtual machine is migrated to other physical servers, so that scheduling jitter occurs. This scheduling jitter phenomenon is difficult to avoid in prior art scheduling algorithms.
In the traditional scheduling of the multi-service cloud system of the operator, because the difference of the load of each service system is not considered, and the load of the service system is not predicted, the scheduling migration of the virtual machine bearing the service system is executed by the cloud management system due to the overhigh load of the physical server when the service peak is easily caused. However, the performance of the whole service system is reduced due to the performance reduction of the virtual machine during migration, which results in instability of the whole service system.
In order to solve the above problems, embodiments of the present invention provide a new scheduling algorithm to reduce or avoid the occurrence of the above scheduling jitter, and a specific idea is to predict future service conditions by analyzing historical loads, so as to perform virtual machine scheduling scientifically and efficiently. By adopting the scheduling method of the embodiment of the invention, the scheduling algorithm of the multi-service cloud system can be simplified, the multi-service cloud system can be more directly and efficiently scheduled, the complexity of the scheduling algorithm is reduced, the problem of scheduling jitter caused by the traditional scheduling algorithm is reduced, and the problem of service system performance reduction caused by unnecessary virtual machine migration during service peak is avoided.
After research on the existing service system, it is found that when the service system is running, if a load balancing scheduling algorithm is used for scheduling in the daytime, a steady state is finally achieved, that is, the virtual machine is not migrated any more due to the load change of the service system, and at this time, the virtual machine is called as a steady state. And mapping the relationship between all the physical servers and all the virtual machines running on the physical servers according to the membership relationship. A steady-state mapping table is formed, corresponding to the daytime mode.
Similarly, at night, the virtual machine is compressed to the physical servers to be operated as few as possible by adopting an energy-saving algorithm including a knapsack algorithm. After the compression is finished, a steady state is achieved, the virtual machine and the running physical server are mapped, and meanwhile, a mapping relation table at the moment is recorded, and the mapping relation table corresponds to a night mode.
When the business system is switched from the night mode to the day mode, the scheduler directly migrates the virtual machine to the affiliated physical server according to the mapping relation table of the virtual machine and the physical server in the day mode recorded before. Such scheduling is equivalent to restoring the system to the last steady state. Since the load of various existing service systems including telecommunication service systems is continuous in a period of time and has specific periodicity and regularity, yesterday steady state, today steady state, or maximum probability steady state can be generally predicted, which is the most basic principle of the scheduling method of the embodiment of the present invention.
Similarly, when the daytime mode is switched to the nighttime mode, the migration scheduling of the virtual machine can be performed according to the mapping relation table recorded before in the steady state in the nighttime mode.
The scheduling method provided by the embodiment of the invention predicts the load and virtual machine distribution of the next period according to the load and virtual machine distribution of the previous period, takes the historical load condition into consideration, can accurately and directly transfer the virtual machine to a steady state as soon as possible, has extremely simple scheduling algorithm, and has accurate and efficient scheduling effect. Referring to fig. 1, a scheduling method for a service system based on cloud computing according to an embodiment of the present invention may be applied to a multi-service system, where the service system includes a plurality of physical servers and a plurality of virtual machines, and the virtual machines are used for processing different services in the service system, and the scheduling method includes the following steps:
Here, the operation time period of the service system includes busy time periods and idle time periods which are preset and periodically presented. And the scene corresponding to the busy hour period is a busy hour scene, and the scene corresponding to the idle hour period is an idle scene. Specifically, the scene mode in step 11 may be the daytime mode mentioned above, that is, the busy hour scene mode corresponding to the busy hour time period of the service system, or may be the night mode, that is, the idle hour scene mode corresponding to the idle hour time period of the service system.
And step 12, scheduling the virtual machine of the service system to a corresponding physical server according to the mapping relation in the mapping relation table.
Here, in step 12, executing the scheduling process according to the mapping relationship in the mapping relationship table may specifically include: waking up the physical server recorded in the mapping relation table, if the physical server is already in a wake-up state, directly executing the next step, and if the physical server is in a power-off or sleep state, waking up the physical server; then, according to the mapping relation in the mapping relation table, scheduling the virtual machines recorded in the mapping relation table to the corresponding physical servers; and after the scheduling is finished, performing power-off or dormancy processing on the rest physical servers in the service system except the physical servers recorded in the mapping relation table so as to save energy consumption.
Through the above steps, when the service system switches from one scene mode to another scene mode, according to the pre-recorded mapping relationship table in the last scene mode, the present embodiment quickly restores the mapping relationship between the virtual machine and the physical server of the service system to the situation in the last scene mode, that is, quickly reaches a steady state, so as to simplify the processing of the scheduling algorithm and reduce or avoid the scheduling jitter steady state.
In step 11, if the stored mapping relationship table in the scene mode cannot be found when the service system is switched to the scene mode, it indicates that the service system may enter the scene mode for the first time, and at this time, the resource occupation condition of each physical server in the service system may be periodically collected based on the membership of the current virtual machine and physical server in the service system, and migration scheduling of the virtual machine is performed according to a predetermined virtual machine scheduling algorithm, so that the virtual machine reaches a steady state. And after each migration scheduling, recording and storing the mapping relation table in the scene mode according to the mapping relation between the virtual machine after the migration scheduling and the physical server, and if the mapping relation table exists, updating the mapping relation table according to the mapping relation between the virtual machine after the migration scheduling and the physical server.
Because the load of the service system is not always constant, after the steady state in the previous scene mode is restored, the virtual machine may need to be scheduled and migrated continuously according to the current change condition of the service load, so as to adapt to the new change. At this time, after the step 12, the embodiment of the present invention may further include the following steps: periodically collecting the resource occupation condition of each physical server in the service system, and executing migration scheduling of the virtual machine according to the resource occupation condition and a preset virtual machine scheduling algorithm; and then, after the migration scheduling of the virtual machine is executed, updating the mapping relation table according to the mapping relation between the current virtual machine of the service system and the physical server.
In the embodiment of the present invention, when the migration scheduling of the virtual machine is executed according to the resource occupation situation and according to the predetermined virtual machine scheduling algorithm, different processes may be performed for different scenarios, for example:
when the scene mode is a busy hour scene corresponding to the busy hour period, transferring a part of virtual machines on the physical server with the resource occupancy rate exceeding a preset threshold to the physical server with the lowest resource occupancy rate in the service system according to a load balancing algorithm;
when the scene mode is an idle-time scene corresponding to the idle-time period, migrating the virtual machines of the service system to the physical servers with the least number according to a knapsack algorithm.
Through the method, the embodiment of the invention can simplify the migration scheduling of the virtual machine of the service system, reduce or avoid the scheduling jitter steady state and improve the performance and the stability of the service system.
Based on the method, the embodiment of the invention also provides a device for implementing the method. Referring to fig. 2, a scheduling apparatus of a cloud computing-based service system according to an embodiment of the present invention includes:
an obtaining unit 21, configured to obtain a mapping relationship table between a virtual machine and a physical server of the service system in a pre-stored scene mode when the service system is switched to the scene mode, where the mapping relationship table records a mapping relationship between the virtual machine and the physical server, where the virtual machine and the physical server are obtained by the service system being scheduled according to a predetermined virtual machine scheduling algorithm in the scene mode at the last time, and the scene mode corresponds to a periodic time period of the service system;
and the first scheduling unit 22 is configured to schedule the virtual machine of the service system to the corresponding physical server according to the mapping relationship in the mapping relationship table.
Further, the scheduling apparatus may further include:
the second scheduling unit is used for periodically collecting the resource occupation condition of each physical server in the service system and executing migration scheduling of the virtual machine according to a preset virtual machine scheduling algorithm if the mapping relation table in the scene mode is not stored when the service system is switched to the scene mode;
and the first updating unit is used for recording and storing the mapping relation table in the scene mode according to the mapping relation between the virtual machine after the migration scheduling and the physical server.
Specifically, the first scheduling unit 22 may include:
the migration unit is used for awakening the physical server recorded in the mapping relation table and scheduling the virtual machine recorded in the mapping relation table to the corresponding physical server according to the mapping relation in the mapping relation table; and the number of the first and second groups,
and the energy-saving unit is used for carrying out power-off or dormancy processing on the rest physical servers in the service system except the physical servers recorded in the mapping relation table.
In order to adapt to the change of the service load of the service system, the scheduling device may further include:
the third scheduling unit is used for periodically acquiring the resource occupation condition of each physical server in the service system and executing the migration scheduling of the virtual machine according to the resource occupation condition and a preset virtual machine scheduling algorithm; and after the migration scheduling of the virtual machine is executed, updating the mapping relation table according to the mapping relation between the current virtual machine of the service system and the physical server.
Specifically, the working time period of the service system may include a busy time period and an idle time period which are preset and periodically presented. At this time, the second scheduling unit or the third scheduling unit is further configured to migrate, according to a load balancing algorithm, a part of virtual machines on the physical server whose resource occupancy rate exceeds a predetermined threshold to the physical server with the lowest resource occupancy rate in the service system when the scene mode is a busy hour scene corresponding to the busy hour period; and when the scene mode is an idle-time scene corresponding to the idle-time period, migrating the virtual machines of the service system to the physical servers with the least number according to a knapsack algorithm.
The present invention will be described in more detail by way of a more specific example of a scheduling method. The scheduling method is divided into four stages, namely an initial day stage, an initial night stage, a normal day stage and a normal night stage.
Initial day phase:
the method comprises the following steps: as an initial state, the service system randomly disperses the Virtual Machines (VMs) to each physical server Host (Host) according to a load balancing scheduling algorithm principle (an optional algorithm is a random dispersion algorithm), and establishes a mapping relationship table between the VMs and the Host at the daytime stage.
Step two: and carrying out dynamic scheduling according to the load condition. The telecom operator's policy, which is typically that the CPU usage of Host exceeds 70%, requires VM scheduling. Therefore, the cloud management scheduling device detects the CPU utilization rate of each Host in real time, and if the CPU utilization rate exceeds 70% of the hosts, the VM occupying the highest CPU is selected and migrated to the Host with the lightest load. And meanwhile, updating a mapping relation table between the VM and the Host in the daytime.
And repeatedly executing the second step until the day mode is converted into the night mode.
Initial night phase:
the method comprises the following steps: as an initial state, the service system compresses a VM (virtual machine) to a minimum Host (physical Host) according to an energy-saving scheduling algorithm principle (an optional algorithm is a knapsack algorithm), and establishes a mapping relation table between the VM and the Host in the night phase.
Normal daytime phase
The method comprises the following steps: when the night mode is switched to the day mode, the VM is rapidly scheduled to the corresponding Host according to the mapping relation table established before for the VM and the day phase of the Host.
Step two: and detecting the CPU occupancy rate of each Host in real time, if the CPU occupancy rate exceeds 70 percent of the Host, selecting the VM occupying the highest CPU on the Host, migrating the VM to the Host with the lightest load, and updating the mapping relation table between the VM and the Host in the daytime.
And the second step is executed periodically until the mode is switched between day and night and the scheduling strategy is switched.
Normal night phase:
the method comprises the following steps: and according to the mapping relation table of the VM and the Host at the night stage, the VM is quickly scheduled to the corresponding Host, and the idle Host is subjected to dormancy or power-off operation, so that the power and the air conditioner refrigeration consumption are saved.
In summary, the scheduling algorithm and the scheduling apparatus provided in the embodiments of the present invention can effectively schedule the multi-service cloud system of the operator, and on the basis of ensuring the system performance, the scheduling algorithm can be simplified, energy saving and consumption reduction are achieved, and the performance and reliability of the service system are provided, which has higher practicability.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (11)
1. A scheduling method of a business system based on cloud computing is characterized by comprising the following steps:
when the business system switches a scene mode to a busy hour scene corresponding to a busy hour period, acquiring a mapping relation table which is stored in advance and is between a virtual machine and a physical server of the business system under the busy hour scene;
scheduling the virtual machine of the service system to a corresponding physical server according to the mapping relation in the mapping relation table in the busy hour scene;
when the business system switches a scene mode to an idle time scene corresponding to an idle time period, acquiring a mapping relation table between a virtual machine and a physical server of the business system under the idle time scene, wherein the mapping relation table is stored in advance;
scheduling the virtual machine of the service system to a corresponding physical server according to the mapping relation in the mapping relation table in the idle time scene;
the mapping relation table under the busy hour scene and the mapping relation table under the idle hour scene respectively record mapping relations between virtual machines and physical servers, which are obtained by the service system in the busy hour scene and the idle hour scene according to scheduling of a preset virtual machine scheduling algorithm, at the last time, and the busy hour scene and the idle hour scene respectively correspond to periodic busy hour time periods and idle hour time periods of the service system.
2. The method of claim 1,
when the business system is switched to a scene mode, if the mapping relation table in the scene mode is not stored, the resource occupation condition of each physical server in the business system is periodically collected, and the migration scheduling of the virtual machine is executed according to a preset virtual machine scheduling algorithm;
and recording and storing the mapping relation table in the scene mode according to the mapping relation between the virtual machine and the physical server after the migration scheduling.
3. The method of claim 1, wherein the scheduling the virtual machines of the business system to the corresponding physical servers according to the mapping relationship in the mapping relationship table comprises:
waking up the physical server recorded in the mapping relation table, and scheduling the virtual machine recorded in the mapping relation table to the corresponding physical server according to the mapping relation in the mapping relation table; and the number of the first and second groups,
and powering off or sleeping the rest physical servers in the service system except the physical servers recorded in the mapping relation table.
4. The method of claim 1, wherein after the step of scheduling the virtual machines of the business system to the corresponding physical servers according to the mapping in the mapping table, the method further comprises:
periodically collecting the resource occupation condition of each physical server in the service system, and executing migration scheduling of the virtual machine according to the resource occupation condition and a preset virtual machine scheduling algorithm;
and after the migration scheduling of the virtual machine is executed, updating the mapping relation table according to the mapping relation between the current virtual machine of the service system and the physical server.
5. The method of claim 2 or 4,
the working time period of the service system comprises busy hour time periods and idle time periods which are preset and periodically presented;
the executing migration scheduling of the virtual machine according to the resource occupation situation and a predetermined virtual machine scheduling algorithm comprises:
when the scene mode is a busy hour scene corresponding to the busy hour period, transferring a part of virtual machines on the physical server with the resource occupancy rate exceeding a preset threshold to the physical server with the lowest resource occupancy rate in the service system according to a load balancing algorithm;
and when the scene mode is an idle-time scene corresponding to the idle-time period, migrating the virtual machines of the service system to the physical servers with the least number according to a knapsack algorithm.
6. A scheduling apparatus of a cloud computing-based business system, comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring a mapping relation table between a virtual machine and a physical server of the service system under a pre-stored busy hour scene when the service system switches a scene mode to the busy hour scene corresponding to a busy hour period, and acquiring the mapping relation table between the virtual machine and the physical server of the service system under a pre-stored idle hour scene when the service system switches the scene mode to the idle hour scene corresponding to the idle hour period;
the first scheduling unit is used for scheduling the virtual machine of the service system to a corresponding physical server according to the mapping relation in the mapping relation table under the busy hour scene, and scheduling the virtual machine of the service system to a corresponding physical server according to the mapping relation in the mapping relation table under the idle hour scene;
the mapping relation table under the busy hour scene and the mapping relation table under the idle hour scene respectively record mapping relations between virtual machines and physical servers, which are obtained by the service system in the busy hour scene and the idle hour scene according to scheduling of a preset virtual machine scheduling algorithm, at the last time, and the busy hour scene and the idle hour scene respectively correspond to periodic busy hour time periods and idle hour time periods of the service system.
7. The scheduling apparatus of claim 6, further comprising:
the second scheduling unit is used for periodically collecting the resource occupation condition of each physical server in the service system and executing migration scheduling of the virtual machine according to a preset virtual machine scheduling algorithm if the mapping relation table in the scene mode is not stored when the service system is switched to the scene mode;
and the first updating unit is used for recording and storing the mapping relation table in the scene mode according to the mapping relation between the virtual machine after the migration scheduling and the physical server.
8. The scheduling device as claimed in claim 7, wherein the working time period of the service system includes busy time periods and idle time periods which are preset and periodically presented; the second scheduling unit is further configured to migrate, according to a load balancing algorithm, a part of virtual machines on the physical server whose resource occupancy rate exceeds a predetermined threshold to the physical server with the lowest resource occupancy rate in the service system when the scene mode is a busy hour scene corresponding to the busy hour period; and when the scene mode is an idle-time scene corresponding to the idle-time period, migrating the virtual machines of the service system to the physical servers with the least number according to a knapsack algorithm.
9. The scheduling apparatus of claim 6, wherein the first scheduling unit comprises:
the migration unit is used for awakening the physical server recorded in the mapping relation table and scheduling the virtual machine recorded in the mapping relation table to the corresponding physical server according to the mapping relation in the mapping relation table; and the number of the first and second groups,
and the energy-saving unit is used for carrying out power-off or dormancy processing on the rest physical servers in the service system except the physical servers recorded in the mapping relation table.
10. The scheduling apparatus of claim 6, further comprising:
the third scheduling unit is used for periodically acquiring the resource occupation condition of each physical server in the service system and executing the migration scheduling of the virtual machine according to the resource occupation condition and a preset virtual machine scheduling algorithm; and after the migration scheduling of the virtual machine is executed, updating the mapping relation table according to the mapping relation between the current virtual machine of the service system and the physical server.
11. The scheduling apparatus as claimed in claim 10, wherein the operation time period of the service system comprises busy time period and idle time period which are preset and periodically presented;
the third scheduling unit is further configured to migrate, according to a load balancing algorithm, a part of virtual machines on the physical server whose resource occupancy rate exceeds a predetermined threshold to the physical server with the lowest resource occupancy rate in the service system when the scene mode is a busy hour scene corresponding to the busy hour period; and when the scene mode is an idle-time scene corresponding to the idle-time period, migrating the virtual machines of the service system to the physical servers with the least number according to a knapsack algorithm.
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| CN201510035570.9A CN105868004B (en) | 2015-01-23 | 2015-01-23 | Scheduling method and scheduling device of service system based on cloud computing |
| PCT/CN2015/098308 WO2016115956A1 (en) | 2015-01-23 | 2015-12-22 | Scheduling method and scheduling device for business system based on cloud computing |
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| CN201510035570.9A CN105868004B (en) | 2015-01-23 | 2015-01-23 | Scheduling method and scheduling device of service system based on cloud computing |
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| CN107145216A (en) * | 2017-05-05 | 2017-09-08 | 北京景行锐创软件有限公司 | A kind of dispatching method |
| CN107247617B (en) * | 2017-05-17 | 2020-11-24 | 北京神州数码云科信息技术有限公司 | Virtual machine resource allocation method, trial platform and readable storage medium |
| US10417035B2 (en) | 2017-12-20 | 2019-09-17 | At&T Intellectual Property I, L.P. | Virtual redundancy for active-standby cloud applications |
| CN110609747A (en) * | 2019-08-29 | 2019-12-24 | 联想(北京)有限公司 | Information processing method and electronic equipment |
| CN112631744A (en) * | 2019-09-24 | 2021-04-09 | 阿里巴巴集团控股有限公司 | Process processing method and device, electronic equipment and computer readable storage medium |
| CN111104203B (en) * | 2019-12-13 | 2023-04-28 | 广东省华南技术转移中心有限公司 | Virtual machine decentralized scheduling method and device, electronic equipment and storage medium |
| CN112667392B (en) * | 2020-12-09 | 2024-01-23 | 南方电网数字电网研究院有限公司 | Cloud computing resource allocation method and device, computer equipment and storage medium |
| CN112866131B (en) * | 2020-12-30 | 2023-04-28 | 神州绿盟成都科技有限公司 | Traffic load balancing method, device, equipment and medium |
| CN118473942B (en) * | 2024-07-08 | 2024-09-17 | 西安电子科技大学 | Version cutting method for agile VMware virtualization resource pool |
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