CN110167031A - A kind of resource allocation methods towards centralized base station, equipment and storage medium - Google Patents
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Abstract
The present invention provides a kind of resource allocation methods towards centralized base station, equipment and storage medium.This method includes the resource allocation request obtained to BTS service, includes the resource allocation requirements of BTS service in resource allocation request；Calculating meets each respective resource using information of calculate node after resource allocation requirements, selects calculate node according to resource using information, resource using information is for characterizing the balanced degree that the calculate node has distributed resource；Resource is distributed for BTS service according to resource allocation requirements in selected calculate node.The resource using information of calculate node after resource is distributed for BTS service by estimating, the practical calculate node that resource is distributed for the BTS service is selected according to the resource using information, it can be in the case where meeting the resource requirement of BTS service, take into account the balanced degree that calculate node has distributed resource, make it possible to realize the efficient utilization of calculate node resource, and can satisfy the requirement of real-time of wireless communication field.
Description
Technical Field
The present invention belongs to the field of communication technologies, and in particular, to a method, an apparatus, and a storage medium for resource allocation for a centralized base station.
Background
At present, research on a resource allocation algorithm under a centralized base station architecture is mainly developed in a centralized manner for a data center and a cloud computing environment, and due to the fact that user mobility causes 'tide' change of base station service, resource allocation and adjustment conditions become more complex, so that the resource allocation algorithm in the cloud computing cannot be directly applied to an access network of the centralized architecture.
There are two main methods for resource allocation under the centralized base station architecture, namely static allocation and dynamic allocation.
The static allocation aims at meeting the maximum requirement of the base station service task processing, allocates the computing resources capable of meeting the maximum requirement for the base station service, and simultaneously uses the minimum resources to accommodate all the computing tasks. Since the traffic load of the base station may change at any time, resources are allocated completely according to the maximum demand, which may result in that the computing resources are not fully utilized in most of the time.
The basic idea of dynamic allocation is to adopt a heuristic resource allocation algorithm of multiple iterations to seek a suboptimal solution of a resource allocation problem, and adjust resources by using a task migration mechanism so as to cope with the change of the actual base station service load. Specifically, the service migration mechanism refers to migrating a base station service from one computing node to another computing node to meet the actual requirements of the base station service and realize efficient utilization of resources. However, the dynamic allocation adopts a heuristic resource allocation algorithm, which requires multiple iterations, consumes more time in the process of seeking suboptimal solution, cannot meet the real-time requirement in the field of wireless communication, and is not suitable for actual base station resource allocation scheduling.
Disclosure of Invention
Therefore, an object of the present invention is to overcome the above-mentioned drawbacks of the prior art and to provide a method, an apparatus and a storage medium for allocating resources to a centralized base station.
The purpose of the invention is realized by the following technical scheme:
in one aspect, an embodiment of the present invention provides a method for allocating resources to a centralized base station, where the method includes: acquiring a resource allocation request for a base station service, wherein the resource allocation request comprises a resource allocation requirement of the base station service; calculating respective resource use information of each computing node of the base station after the resource allocation requirement is met, and selecting the computing node according to the resource use information, wherein the resource use information is used for representing the balance degree of the allocated resources of the computing node; and distributing resources for the base station service in the selected computing node according to the resource distribution requirement.
In the above method, the resource allocation requirement includes a storage resource requirement and/or an operation resource requirement.
In the above method, the resource usage information includes a resource utilization rate and a resource usage balance degree, and the resource usage balance degree is used to indicate a balance degree between the allocated storage resource and the allocated calculation resource.
In the above method, before calculating the respective resource usage information of each computing node of the base station after the resource allocation requirement is met, the method further includes: selecting m computing nodes satisfying the resource allocation requirement from n computing nodes, wherein n is the number of computing nodes of the base station, n is greater than 1, and m is a positive integer less than or equal to n;
calculating respective resource use information of each computing node of the base station after the resource allocation requirement is met, and selecting the computing node according to the resource use information, wherein the method comprises the following steps: calculating the resource utilization rate of each of the m computing nodes after the resource allocation requirement is met, and selecting s computing nodes from the m computing nodes according to the resource utilization rate, wherein s is smaller than or equal to m; calculating the respective resource use balance of the s computing nodes after the resource allocation requirements are met; and selecting one computing node from the s computing nodes according to the resource use balance degree.
In the above method, selecting s computing nodes from the m computing nodes according to the resource utilization rate includes: and determining the high-low order of the resource utilization rate of the m computing nodes according to the size of the resource utilization rate, and selecting s computing nodes from the m computing nodes according to the sequence of the resource utilization rate from high to low.
In the above method, selecting one compute node from the s compute nodes according to the resource usage balance degree includes: and selecting the computing node with the highest resource use balance degree from the s computing nodes according to the resource use balance degree.
In the above method, calculating the resource utilization rates of the m computing nodes that meet the resource allocation requirement includes: according to the formulaCalculating the resource utilization rate of the computing node j after the resource allocation requirement is met,representing the utilization rate of the computing resource of the computing node j at the time t,representing the utilization of the storage resources of the computing node j at time t,indicating the computational resource requirements of the base station traffic,and E represents a representation value of the resource utilization rate of the computing node j, and the smaller the value E is, the higher the resource utilization rate is.
In the above method, calculating the resource usage balance of each of the s computing nodes after the resource allocation requirement is met includes:
according to the formulaCalculating the resource usage balance degree of the computing node j after the resource allocation requirement is met,representing the utilization rate of the computing resource of the computing node j at the time t,representing the utilization of the storage resources of the computing node j at time t,indicating the computational resource requirements of the base station traffic,representing the memory resource requirement, Mid, of the base station trafficcpuRepresents the average value, Mid, of the utilization rates of the computational resources of all base station services on the compute node jmemAnd expressing the average value of the utilization rates of the storage resources of all the base station services on the computing node j, and expressing the resource use balance degree of the computing node j by var.
In still another aspect, an embodiment of the present invention provides a computing device, where the computing device includes a processor and a memory, where the memory stores a computer program for the processor to run, and the processor runs the computer program to implement the resource allocation method described above.
In still another aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and the computer program is executed to implement the resource allocation method described above.
Compared with the prior art, the invention has the advantages that: by estimating resource use information of the computing node after the resource is allocated to the base station service, namely the balance degree of the allocated resource of the computing node, and selecting the computing node which actually allocates the resource to the base station service according to the resource use information, the balance degree of the allocated resource of the computing node can be considered under the condition of meeting the resource requirement of the base station service, so that the efficient utilization of the computing node resource can be realized, and the real-time requirement in the field of wireless communication can be met.
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Embodiments of the invention are further described below with reference to the accompanying drawings, in which:
FIG. 1a is a schematic diagram illustrating unbalanced allocation of memory resources and CPU resources of a compute node according to an embodiment of the present invention;
FIG. 1b is a schematic diagram illustrating an unbalanced allocation of memory resources and CPU resources of another compute node according to an embodiment of the present invention;
FIG. 1c is a schematic diagram illustrating a balanced allocation of memory resources and CPU resources of a compute node according to an embodiment of the present invention;
FIG. 2a is a diagram illustrating a resource allocation process according to an embodiment of the present invention;
FIG. 2b is a diagram illustrating another resource allocation process according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a large top heap sort according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a network device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail by embodiments with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In an actual base station system, due to the diversity of communication services, the required amount of resources in different data processing processes may also be different. For example, for computing-type services (e.g., user data processing), the CPU utilization may be high, while for storage-type services (e.g., downloading audio or video), the storage and bandwidth resources may be in high demand. The conventional idea is to allocate resources with a single resource requirement (e.g. only with CPU resources or only with memory resources). Fig. 1a and fig. 1b are schematic diagrams illustrating resource allocation imbalance, where a rectangle represents the total amount of CPU and memory resources of a computing node, the computing node in fig. 1a supports two base station services with high memory requirements, i.e., a base station service 1 and a base station service 2, but the CPU resources are still remained, the computing node in fig. 1b runs two base station services, i.e., a base station service 3 and a base station service 4, and the CPU resources are fully occupied but a large amount of memory resources are remained. It can be seen that the existing resource allocation manner causes the waste of CPU and memory resources, and the problem of unbalanced resource allocation occurs, if the purpose of resource allocation balance shown in fig. 1c can be achieved, the resource utilization rate can be improved, the computing node in fig. 1c supports the base station service 1 and the base station service 5, and the CPU resources and the memory resources are occupied at the same time.
In view of the above, the embodiments of the present invention provide a resource allocation method for the characteristics of base station services and resource usage on compute nodes, and the main idea of the method is to comprehensively consider the usage of storage resources and computing resources, select compute nodes with high resource utilization and high balance for resource allocation, achieve flexible allocation of resources, achieve the purpose of improving resource utilization, save the number of compute nodes used, and avoid the resource waste caused by unbalanced allocation.
In the embodiment of the present invention, a base station service is taken as an example to describe a process of resource allocation, and in practical application, resource allocation may be performed on one or more base station services, where in a scenario where resource allocation is performed on multiple base station services, a resource allocation process for any one of the base station services is the same as the resource allocation process described in fig. 2a and fig. 2 b.
The resource allocation method provided in the embodiment of the present invention may be used in any one or more computing devices that manage resources of each computing node in a centralized architecture base station system, as shown in fig. 2a and fig. 2b, the main execution processes of the method are as follows:
step 201, a resource allocation request for a base station service is obtained, where the resource allocation request includes a resource allocation requirement of the base station service.
Specifically, the resource allocation requirements include storage resource requirements, or include computational resource requirements, or both storage resource requirements and computational resource requirements.
The storage resources comprise resources required by data storage such as a memory and the like, and the operation resources comprise resources required by operation such as a CPU and the like.
Step 202, calculating respective resource usage information of each computing node after the resource allocation requirement of the base station service is met, and selecting the computing node according to the resource usage information, wherein the resource usage information is used for representing the balance degree of the allocated resources of the computing node.
Specifically, the resource usage information includes a resource utilization rate (or a characteristic value thereof) and a resource usage balance degree (or a characteristic value thereof), and the resource usage balance degree is used to indicate a degree of balance between the allocated storage resource and the allocated calculation resource.
In the embodiment of the invention, in order to quantify the use conditions of the operation resources and the storage resources, the sizes of the resources requested by the base station service and the resources allocated by the computing nodes are uniformly measured by percentage. For example, the size of the resource request of the newly-built base station service i is represented as:
wherein,what is indicated is the size of the CPU resources (i.e. the operating resources) required for the new base station service i,what is shown is the size of the memory resource (i.e., storage resource) required by the new base station service i.
The resource utilization rate of the computing node j at the time t can be represented as:
wherein,is the CPU resource (i.e. computing resource) utilization of compute node j at time t,is the memory resource (i.e., storage resource) utilization rate of the computing node j at time t.
Assuming that the set of base station services on computing node j is θ (j), it can be derived:
wherein,is the CPU utilization rate of the base station service i on the computing node at the time t, and the formula (3) is the total CPU resource utilization rate of the computing node jIs the sum of the CPU utilization of all base station traffic running on compute node j. Similarly, the total memory resource utilization rate of the node j is calculatedThe sum of the utilization rates of the memory resources of all the base station services running on the computing node j is shown as the following formula:
in the embodiment of the invention, the purpose of resource allocation is to find a computing node which can meet the resource allocation requirement of the base station service, and after the resources are allocated to the base station service on the computing node, the resource utilization rate can be improved, so that the balance degree of the allocated resources of the computing node is the highest, namely the use of the computing resources and the storage resources is balanced, and any resource is not wasted.
Assuming that n computing nodes are in total in the centralized architecture base station system, where n is a positive integer greater than 1, m computing nodes meeting the resource allocation requirement are selected from the n computing nodes first, after the computing nodes not meeting the resource allocation requirement are removed, the respective resource use information of each computing node meeting the resource allocation requirement is calculated, where m is a positive integer less than or equal to n.
That is, the following constraint conditions are satisfied when the base station service i can be distributed to the preferred computing node j:
formula 5 shows the remaining computation resources and storage resources on the computation node to be allocated, which are needed to support the basic requirements of the base station service on the computation resources and storage resources.
And after the computing nodes which do not meet the resource allocation requirement are removed, selecting the computing node with the highest balance degree of the allocated resources in the computing nodes after the resources are allocated to the base station service according to the resource use information of each computing node.
Specifically, after the resource allocation requirements are met, the resource utilization rate of each of the m computing nodes is calculated, and s computing nodes are selected from the m computing nodes according to the resource utilization rate, wherein s is a positive integer less than or equal to m; calculating the respective resource use balance of the s computing nodes after the resource allocation requirement is met; and selecting one computing node from the s computing nodes according to the resource use balance degree.
Specifically, the resource utilization rate of the computing node j after meeting the resource allocation requirement is computed according to the resource model of the base station service constructed by the above formulas 1 to 4 and the usage condition model of the computing resource and the storage resource of the computing node and further according to the formula 6,
wherein,representing the utilization rate of the computing resource of the computing node j at the time t,representing the utilization of the storage resources of the computing node j at time t,indicating the computational resource requirements of the base station traffic,and E represents a representation value of the resource utilization rate of the computing node j, and the smaller the value E is, the higher the resource utilization rate is.
Specifically, according to formula 7, the resource usage balance of the node j is calculated after the resource allocation requirement is satisfied,
wherein,representing the utilization rate of the computing resource of the computing node j at the time t,representing the utilization of the storage resources of the computing node j at time t,indicating the computational resource requirements of the base station traffic,indicating the memory resource requirement, Mid, of the base station trafficcpuRepresents the average value, Mid, of the utilization rates of the computational resources of all base station services on the compute node jmemAnd expressing the average value of the utilization rates of the storage resources of all the base station services on the computing node j, and expressing the representation value of the resource use balance degree of the computing node j by var. In the formula 7, the storage resource and the operation resource are both in a percentage system mode, and the meter is calculated through the formula 7And calculating the variance of each dimension resource on the node, wherein the smaller var is, the higher the balance degree of the resource is.
In one embodiment, the process of selecting s compute nodes from the m compute nodes according to resource utilization is as follows: and determining the high-low order of the resource utilization rate of the m computing nodes according to the size of the resource utilization rate, and selecting s computing nodes from the m computing nodes according to the sequence of the resource utilization rate from high to low.
In one embodiment of the invention, a heap sorting algorithm is adopted to select s computing nodes with higher resource utilization rate from m computing nodes. As shown in fig. 3, a schematic diagram of ordering a large top heap is shown, assuming that the capacity of the large top heap is s, the large top heap is a data structure based on a binary tree, each circle in the large top heap represents a computing node, numbers in the circles represent resource utilization rates of the computing nodes, and the computing node with the highest resource utilization rate among the s computing nodes stored at the top of the heap can be obtained by sequentially comparing the resource utilization rates of the m computing nodes. The resource utilization rate calculated by formula 6 can be used to represent the resource utilization rate of the computing node. And selecting s computing nodes with smaller E values according to a heap sorting algorithm and storing the computing nodes into a large top heap with the capacity of s. And (3) selecting s elements from m elements by using a large top heap, wherein the algorithm complexity is O (mlogs), and the rapid preliminary screening of the computing nodes is realized.
In one embodiment of the present invention, the process of selecting one computing node from the s computing nodes according to the characteristic value of the resource usage balance degree is as follows: and selecting the computing node with the highest resource use balance degree from the s computing nodes according to the representation value of the resource use balance degree. In the embodiment, the difference of different base station services on the resource use requirements is fully considered, the resource utilization rate of the computing node is improved, and meanwhile, the resource use balance degree of the computing node can be well kept.
For example, a heap sorting algorithm is adopted to select the computing node with the highest resource usage balance from the s computing nodes. The capacity of the large top heap is an integer which is greater than or equal to 1, and the computing node with the highest resource use balance degree is stored at the top of the heap and is always among the s computing nodes. Because the computing nodes are preliminarily screened according to the resource utilization rate, the value of s is usually not very large, and the judgment of the resource utilization balance degree of the s computing nodes can be carried out by express delivery. And finally, selecting the computing node with the minimum var from the s computing nodes as a target node of the newly-built base station service to obtain a final resource allocation scheme of the base station service.
And 203, distributing resources for the base station service according to the resource distribution requirement in the selected computing node.
In the embodiment of the invention, when the resources are allocated to the base station service, the requirements of different base station services on the operation resources and the storage resources are fully considered, the calculation nodes are rapidly and primarily screened based on the resource utilization rate of the calculation nodes, the balance condition of the use of the two dimensional resources is measured through the variance of the use of the operation resources and the storage resources, the calculation node which can enable the balance degree of the use of the resources to be the highest is determined as the target node, and finally the target node is used for establishing the base station service. The resource allocation scheme provided by the embodiment of the invention improves the utilization rate of resources in each dimension, well keeps the balance of the use of operation resources and storage resources, and can be better suitable for resource scheduling allocation of a centralized architecture base station system.
Based on the same inventive concept, a computing device is further provided in the embodiments of the present invention, as shown in fig. 4, the computing device mainly includes a processor 401 and a memory 402, a computer program for the processor 401 to run is stored in the memory 402, and the processor 401 runs the computer program to implement the resource allocation method provided in the embodiments.
The memory 402 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store a list of options, etc. Further, the memory 402 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, memory 402 may optionally include memory located remotely from processor 401, which may be connected to an external device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and the computer program is executed to implement the resource allocation method provided by the embodiment of the present invention.
That is, as can be understood by those skilled in the art, all or part of the steps in the embodiments of the method for allocating resources described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Although the present invention has been described by way of preferred embodiments, the present invention is not limited to the embodiments described herein, and various changes and modifications may be made without departing from the scope of the present invention.
Claims (10)
1. A resource allocation method facing a centralized base station, wherein the method comprises the following steps:
acquiring a resource allocation request for a base station service, wherein the resource allocation request comprises a resource allocation requirement of the base station service;
calculating respective resource use information of each computing node of the base station after the resource allocation requirement is met, and selecting the computing node according to the resource use information, wherein the resource use information is used for representing the balance degree of the allocated resources of the computing node;
and distributing resources for the base station service in the selected computing node according to the resource distribution requirement.
2. The method of claim 1, wherein the resource allocation requirements comprise storage resource requirements and/or computational resource requirements.
3. The method of claim 2, wherein the resource usage information includes resource utilization and a resource usage balance representing a degree of balance of allocated storage resources and allocated computational resources.
4. The method of claim 3, wherein prior to said calculating respective resource usage information for each computing node of the base station after said resource allocation requirement is met, the method further comprises:
selecting m computing nodes satisfying the resource allocation requirement from n computing nodes, wherein n is the number of computing nodes of the base station, n is greater than 1, and m is a positive integer less than or equal to n;
calculating respective resource use information of each computing node of the base station after the resource allocation requirement is met, and selecting the computing node according to the resource use information, wherein the method comprises the following steps:
calculating the resource utilization rate of each of the m computing nodes after the resource allocation requirement is met, and selecting s computing nodes from the m computing nodes according to the resource utilization rate, wherein s is smaller than or equal to m;
calculating the respective resource use balance of the s computing nodes after the resource allocation requirements are met;
and selecting one computing node from the s computing nodes according to the resource use balance degree.
5. The method of claim 4, wherein selecting s compute nodes from the m compute nodes according to the resource utilization comprises:
and determining the high-low order of the resource utilization rate of the m computing nodes according to the size of the resource utilization rate, and selecting s computing nodes from the m computing nodes according to the sequence of the resource utilization rate from high to low.
6. The method of claim 4 or 5, wherein selecting one of the s computing nodes according to the resource usage balance comprises:
and selecting the computing node with the highest resource use balance degree from the s computing nodes according to the resource use balance degree.
7. The method of claim 4 or 5, wherein calculating the respective resource utilization of the m compute nodes after the resource allocation demand is met comprises:
according to the formulaCalculating the resource utilization rate of the computing node j after the resource allocation requirement is met,representing the utilization rate of the computing resource of the computing node j at the time t,representing the utilization of the storage resources of the computing node j at time t,indicating the computational resource requirements of the base station traffic,representing the storage resource requirement of the base station service, E representing the representation value of the resource utilization rate of the computing node j, and the smaller the value E, the higher the resource utilization rate。
8. The method of claim 4 or 5, wherein calculating the respective resource usage balance of the s compute nodes after the resource allocation requirement is met comprises:
according to the formulaCalculating the resource usage balance degree of the computing node j after the resource allocation requirement is met,representing the utilization rate of the computing resource of the computing node j at the time t,representing the utilization of the storage resources of the computing node j at time t,indicating the computational resource requirements of the base station traffic,representing the memory resource requirement, Mid, of the base station trafficcpuRepresents the average value, Mid, of the utilization rates of the computational resources of all base station services on the compute node jmemAnd expressing the average value of the utilization rates of the storage resources of all the base station services on the computing node j, and expressing the resource use balance degree of the computing node j by var.
9. A computing device comprising a processor and a memory, the memory having stored therein a computer program for execution by the processor, the processor executing the computer program to implement the resource allocation method of any one of claims 1 to 8.
10. A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, which when executed implements the resource allocation method of any one of claims 1 to 8.
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| CN111078537A (en) * | 2019-11-29 | 2020-04-28 | 珠海金山网络游戏科技有限公司 | Method for evaluating resource division of bundle package of Unity game |
| CN111078537B (en) * | 2019-11-29 | 2023-09-22 | 珠海金山数字网络科技有限公司 | Evaluation method for Unity game bundle package resource division |
| WO2021109036A1 (en) * | 2019-12-04 | 2021-06-10 | 华为技术有限公司 | Data processing method and apparatus |
| CN111858069A (en) * | 2020-08-03 | 2020-10-30 | 网易（杭州）网络有限公司 | Cluster resource scheduling method and device and electronic equipment |
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