CN109857518B - Method and equipment for distributing network resources - Google Patents
Method and equipment for distributing network resources Download PDFInfo
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- CN109857518B CN109857518B CN201910017051.8A CN201910017051A CN109857518B CN 109857518 B CN109857518 B CN 109857518B CN 201910017051 A CN201910017051 A CN 201910017051A CN 109857518 B CN109857518 B CN 109857518B
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Abstract
The invention is suitable for the technical field of Internet, and provides a method and equipment for allocating network resources, wherein the method comprises the following steps: the method comprises the steps of obtaining an available server list of a target service system, dividing the available server list into a plurality of server clusters, and configuring a resource regulator for each server cluster; calling a resource regulator to acquire the hardware resource quantity of each server in use in the server cluster, and establishing a hardware resource pool of the server cluster; dividing a hardware resource pool into a first resource area and a second resource area based on a preset initial allocation proportion; calculating an actual occupation ratio according to the first occupancy rate and the second occupancy rate; if the absolute value of the difference between the first resource area and the second resource area is larger than the preset adjusting threshold value, the actual occupation proportion is set as the initial distribution proportion, and the first resource area and the second resource area are adjusted. The invention manages the hardware resources in the server cluster through the resource regulator, and dynamically allocates the resource areas of the two services, thereby improving the utilization rate of the resources.
Description
Technical Field
The invention belongs to the technical field of internet, and particularly relates to a method and equipment for allocating network resources.
Background
With the continuous development of cloud service technologies, more and more users realize functions such as capacity expansion of a storage area and local computing capability reinforcement through a cloud server, for example, different systems are built through renting the cloud server, so that corresponding function tests are completed, or program compiling or pressure testing is performed through the rapid implementation computing capability of the cloud server system. Under the condition that extra hardware resources do not need to be purchased, resource cloud sharing is achieved through cloud services.
In the existing cloud server technology, virtual machine leasing and real-time computing services respond to service requests of users through two independent server clusters, and because the demands of the users are dynamically changed, the leasing requests of the cloud servers are less at some moments, the requests of the real-time computing services at the moments are more, and the two sets of systems are not beneficial to resource allocation under the condition that the two sets of systems are mutually independent, so that the resource utilization rate of the systems is reduced, and the service demands of the users cannot be met.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for allocating network resources, so as to solve the problems that in the existing cloud server technology, a virtual machine lease and a real-time computing service respond to a service request of a user through two independent server clusters, a resource utilization rate of a system is low, and a service requirement of the user cannot be met.
A first aspect of an embodiment of the present invention provides a method for allocating network resources, including:
the method comprises the steps of obtaining an available server list of a target service system, dividing all active servers in the available server list into a plurality of server clusters, and configuring a resource regulator for each server cluster;
calling the resource regulator to collect the hardware resource amount of each server in use in the server cluster, and establishing a hardware resource pool of the server cluster;
dividing the hardware resource pool into a first resource area for responding to virtual host rental service and a second resource area for responding to real-time cloud computing service based on a preset initial allocation proportion;
acquiring a first occupancy rate of the first resource area and a second occupancy rate of the second resource area through the resource regulator, and calculating an actual occupancy ratio according to the first occupancy rate and the second occupancy rate;
if the absolute value of the difference between the actual occupation proportion and the initial distribution proportion is larger than a preset adjustment threshold, setting the actual occupation proportion as the initial distribution proportion, and adjusting the first resource area and the second resource area based on the actual occupation proportion.
A second aspect of the embodiments of the present invention provides a device for allocating network resources, including:
the resource regulator configuration unit is used for acquiring an available server list of a target service system, dividing all the servers in use in the available server list into a plurality of server clusters, and configuring resource regulators for the server clusters;
the hardware resource pool establishing unit is used for calling the resource regulator to acquire the hardware resource quantity of each server in use in the server cluster and establishing a hardware resource pool of the server cluster;
the hardware resource pool dividing unit is used for dividing the hardware resource pool into a first resource area used for responding to virtual host leasing service and a second resource area used for responding to real-time cloud computing service based on a preset initial distribution proportion;
the actual occupation ratio acquiring unit is used for acquiring a first occupancy rate of the first resource area and a second occupancy rate of the second resource area through the resource regulator and calculating the actual occupation ratio according to the first occupancy rate and the second occupancy rate;
a hardware resource adjusting unit, configured to set the actual occupancy proportion as an initial allocation proportion if an absolute value of a difference between the actual occupancy proportion and the initial allocation proportion is greater than a preset adjustment threshold, and adjust the first resource region and the second resource region based on the actual occupancy proportion.
A third aspect of embodiments of the present invention provides a terminal device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the first aspect when executing the computer program.
A fourth aspect of embodiments of the present invention provides a computer-readable storage medium storing a computer program which, when executed by a processor, performs the steps of the first aspect.
The method and the equipment for allocating the network resources provided by the embodiment of the invention have the following beneficial effects:
in the embodiment of the invention, all the servers in use in the target service system are divided into a plurality of server clusters, and the corresponding resource regulator is configured for each server cluster, so that the hardware resources in the server clusters can be divided according to the initial allocation proportion through the resource regulators, and in the operation process, the resource regulators can acquire the actual occupancy rates of all the resource areas and determine the actual occupancy proportion according to the first occupancy rate and the second occupancy rate so as to judge whether the current resource allocation is reasonable, and if the actual occupancy proportion is not consistent with the initial allocation proportion, the dynamic adjustment is carried out, so that the aim of dynamically allocating the network resources is fulfilled. Compared with the existing network resource allocation mode, the server for virtual host lease and the server for real-time cloud computing are distributed in the same server cluster, even the same server can respond to two different service requests, hardware resources in the server cluster are managed through the resource regulator, resource areas of the two services are dynamically allocated, and the resource utilization rate is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a flowchart of an implementation of a method for allocating network resources according to a first embodiment of the present invention;
fig. 2 is a flowchart illustrating a detailed implementation of a method S104 for allocating network resources according to a second embodiment of the present invention;
fig. 3 is a flowchart of a detailed implementation of a method S101 for allocating network resources according to a third embodiment of the present invention;
fig. 4 is a flowchart of a specific implementation of a method for allocating network resources according to a fourth embodiment of the present invention;
fig. 5 is a flowchart of a specific implementation of a method for allocating network resources according to a fifth embodiment of the present invention;
fig. 6 is a block diagram illustrating a configuration of an apparatus for allocating network resources according to an embodiment of the present invention;
fig. 7 is a schematic diagram of a terminal device according to another 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 described in further detail below with reference to the accompanying drawings and embodiments. 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 the embodiment of the invention, all the servers in use in the target service system are divided into a plurality of server clusters, and each server cluster is configured with a corresponding resource regulator, and then the hardware resources in the server clusters can be divided according to the initial allocation proportion through the resource regulators.
In the embodiment of the invention, the execution subject of the process is the terminal equipment. The terminal devices include but are not limited to: the device comprises a server, a computer, a smart phone, a tablet computer and the like, and can execute the allocation operation of network resources. In particular, the allocation device of the network resource may be an upper computer device of a service system, and is configured to manage operations, abnormality identification, and the like of all servers in the service system, and manage a topology structure of the service system. Fig. 1 shows a flowchart of an implementation of a method for allocating network resources according to a first embodiment of the present invention, which is detailed as follows:
in S101, an available server list of a target service system is obtained, all active servers in the available server list are divided into a plurality of server clusters, and a resource adjuster is configured for each server cluster.
In this embodiment, the service system includes multiple active servers, and the active servers respond to service requests initiated by each user terminal, so that the service system may divide the active servers according to a geographic area, that is, when the user terminal sends a service request, the service request carries location information of the user terminal, and then the gateway device determines a corresponding active server based on the location information, and redirects the service request again, so as to be able to directionally send the service request to the active server processed by the geographic area; of course, the service system may also distribute the service requests according to the load condition of each active server. The service system may obtain the current operation state of each server at a preset detection period, and add the active server that normally operates and has idle hardware resources into the available server list, that is, it indicates that the active server in the available server list may be used to respond to the service request initiated by the user terminal.
In this embodiment, the terminal device, that is, the allocation device of the hardware resource, may obtain the available server list from the database of the target service system, so as to divide all the servers in use into a plurality of server clusters based on a preset dividing manner of the target service system for the servers in use, where each server cluster includes at least one server in use. As described above, if the target server system divides the active servers based on the geographic area, the terminal device may integrate the active servers belonging to the same geographic area or adjacent geographic areas into the same server cluster based on the geographic area. If the target service system divides the active servers based on the load conditions, the terminal device may be divided into a plurality of server clusters according to the current load conditions of the respective active servers. If the target service system allocates the service request to different servers in use based on the service type, the terminal device may select one server for responding to different types of servers, and integrate the selected server into one server cluster, so that the server cluster may respond to the service requests of all service types.
In this embodiment, the terminal device may be configured to manage network resources of a plurality of different service systems, and if a certain service system meets the allocation trigger condition, the terminal device may identify the service system as a target service system, and perform an operation of allocating network resources to an active server in the target service system. For example, if a certain service system performs capacity expansion operation and a new active server is added, the terminal device will perform network resource division on the active server in the service system again. For another example, the terminal device may be provided with a detection period, and if the terminal device detects that the current time reaches a time node of the preset detection period, the operation of S1 is triggered.
In this embodiment, in order to facilitate concurrent management of different clusters, so as to improve timeliness and accuracy of network resource management, the terminal device configures one resource regulator for each server cluster. The resource regulator may be a stand-alone physical device or a virtual device. If the resource regulator is a virtual device, the terminal device may select an active server in the server cluster as the target server, and determine, for example, an active server with the best processing capability score as the target server according to the hardware resource parameters of the active servers. The terminal equipment controls the target server, creates a sub-thread under the main thread of the target server, sets the sub-thread as a virtual device for running a resource adjusting process based on a preset resource adjusting program, and completes configuration operation of the resource adjuster.
In S102, the resource adjuster is invoked to collect the amount of hardware resources of each of the servers in use in the server cluster, and a hardware resource pool of the server cluster is established.
In this embodiment, in order to facilitate the allocation of network resources of the server cluster, the terminal device may identify hardware resources included in the server cluster as a whole, so that the terminal device only needs to perform resource division on the unified whole hardware resource pool, and does not need to perform resource division on a single server, thereby improving the management efficiency. Based on this, the terminal device needs to acquire the hardware resource amount of each active server, configure a resource identification code related to the server cluster for the hardware resource amount of each active server, and establish an addressing correspondence table of the resource identification code, so that the active server corresponding to the resource identification code and the resource address of the active server can be determined according to the addressing correspondence table. And the terminal equipment identifies the hardware resources formed by all the resource identification codes as a hardware resource pool related to the server cluster.
In this embodiment, the hardware resources include resources related to hardware processing capabilities, such as a memory resource, a bandwidth resource, and a thread resource, and all the hardware resources may be occupied online by other user terminals, that is, available network resources belonging to the service system. The terminal equipment can configure corresponding hardware resource pools for different types of hardware resources.
In S103, the hardware resource pool is divided into a first resource area for responding to virtual host rental service and a second resource area for responding to real-time cloud computing service based on a preset initial allocation ratio.
In this embodiment, the virtual host service is mainly a rental service, that is, a user may select a target server from a target service system, create a virtual host in the target server, and set up a corresponding system, and set up a resource requirement when applying for the virtual host, and during a rental period, the resource of the virtual host is always occupied, and cannot respond to other services, which is an occupation manner that cannot be time-division multiplexed. The real-time cloud computing service is a resource occupation mode capable of time division multiplexing, wherein a user uploads big data analysis, program codes, test cases and the like which need to be operated to a server of the cloud service, the server of the cloud service operates the object and outputs a corresponding operation result, the operation result is stored in an OBS (object based service), EFS (extensible firmware system) or database mode and the like, and occupied resources are released after the operation is finished. Based on the two different service types, the hardware resources of the server cluster need to be divided, that is, each server cluster in the cloud service system can respond to both the virtual host service and the real-time cloud computing service, and the two types of services are uniformly managed on the physical layer, so that the flexible allocation of resources is facilitated.
In this embodiment, the terminal device is configured with an initial allocation ratio, i.e., a ratio between network resources for responding to the cloud computing service and network resources for responding to the virtual host lease service. The initial allocation ratio may be manually configured by a user. Then, the terminal device may divide the hardware resources of the hardware resource pool according to the initial allocation proportion to obtain a first resource region and a second resource region.
Optionally, the terminal device may obtain a historical service record, count the number of times of service of the virtual host and the number of times of service of the cloud computing service based on the historical service record, determine an average amount of occupied resources of the virtual host service and an average amount of occupied resources of the cloud computing service, and calculate the initial proportion based on the four parameters, that is, the number of times of virtual host lease, the average amount of occupied resources of virtual host lease, the number of times of service of the cloud computing service, and the average amount of occupied resources of the cloud computing service.
Optionally, the terminal device may import each historical service record into the adjusted RNN neural network, and determine the initial ratio through the neural network. The historical service record comprises service types, namely information such as service duration, resource occupation and the like, which is used for determining whether the historical service record belongs to virtual host rental service or cloud computing service, so that the neural network can predict the proportion of two services in a target service system at the current time, and the accuracy of the initial distribution proportion is improved.
In S104, a first occupancy rate of the first resource zone and a second occupancy rate of the second resource zone are collected by the resource adjuster, and an actual occupancy ratio is calculated according to the first occupancy rate and the second occupancy rate.
In this embodiment, after the terminal device divides the hardware resource pool, that is, the hardware resource in the corresponding area in each server is used for responding to which service type is fixed, of course, if a part of the hardware resources in a certain server is divided into the first occupied area, and another part of the hardware resources is divided into the second occupied area, the server in use may be used for responding to the cloud rental service and the cloud computing service, and the service type responded by the server in use may be determined based on the attribute of the local hardware resource.
In this embodiment, the terminal device may receive the resource adjuster feedback about the first occupancy of the first resource region and about the second occupancy of the second resource region, so as to determine whether the initial allocation ratio is reasonable in real time, and then may determine the actual occupancy ratio for responding to the two types of services according to the first occupancy and the second occupancy. If the absolute value of the difference between the actual occupation proportion and the initial proportion is smaller than or equal to a preset adjustment threshold, the actual occupation proportion is closer to the preset distribution proportion, and the actual occupation proportion and the initial proportion are within an acceptable floating range; otherwise, if the absolute value of the difference between the two is greater than the preset adjustment threshold, the hardware resource pool needs to be reallocated, and the relevant operation of S105 is executed.
In S105, if the absolute value of the difference between the actual occupancy proportion and the initial allocation proportion is greater than a preset adjustment threshold, setting the actual occupancy proportion as the initial allocation proportion, and adjusting the first resource region and the second resource region based on the actual occupancy proportion.
In this embodiment, when detecting that the absolute value of the difference between the actual occupation proportion and the initial allocation proportion in a certain server cluster is greater than the preset adjustment threshold, the terminal device needs to re-partition the hardware resources of the hardware resource pool in the server cluster, where the operation of re-partitioning is as follows: the terminal equipment determines the amount of the hardware resources required to be adjusted according to the actual occupation proportion, detects the amount of idle hardware resources contained in the first resource area and the second resource area, and adjusts the amount of the resources contained in the two resource areas based on the adjusted amount of the hardware resources and the amount of the idle hardware resources so that the ratio of the adjusted amount of the hardware resources in the first resource area to the amount of the hardware resources in the second resource area meets the actual occupation proportion.
In this embodiment, in order to avoid repeated adjustment and reasonably perform initial resource allocation during subsequent capacity expansion operation when the next detection period arrives, the terminal device sets the actual occupation proportion obtained by this time as the initial allocation proportion, so as to achieve the purpose of dynamically adjusting the initial allocation proportion.
It can be seen from the above that, in the method for allocating network resources provided in the embodiment of the present invention, all active servers in a target service system are divided into a plurality of server clusters, a corresponding resource adjuster is configured for each server cluster, and then hardware resources in the server clusters can be divided according to an initial allocation proportion through the resource adjusters, during an operation process, the resource adjusters can acquire actual occupancy rates of respective resource areas, and determine an actual occupancy proportion according to the first occupancy rate and the second occupancy rate, so as to determine whether current resource allocation is reasonable, and if the actual occupancy proportion is not consistent with the initial allocation proportion, dynamic adjustment is performed, so that a purpose of dynamically allocating network resources is achieved. Compared with the existing network resource allocation mode, the server for virtual host leasing and the server for real-time cloud computing are arranged in the same server cluster, even the same server can respond to two different service requests, hardware resources in the server cluster are managed through the resource regulator, resource areas of the two services are dynamically allocated, and the resource utilization rate is improved.
Fig. 2 shows a flowchart of a specific implementation of the method S104 for allocating network resources according to a second embodiment of the present invention. Referring to fig. 2, with respect to the embodiment described in fig. 1, a method S104 for allocating network resources provided in this embodiment includes: s1041 to S1044, which are specifically detailed as follows:
further, the acquiring, by the resource adjuster, a first occupancy rate of the first resource region and a second occupancy rate of the second resource region, and calculating an actual occupancy ratio according to the first occupancy rate and the second occupancy rate includes:
in S1041, if a preset acquisition condition is satisfied, acquiring a plurality of actual resource occupation parameters of each of the servers in use in the server cluster at a preset acquisition frequency; the actual resource occupation parameters include: the first occupation parameter is used for responding to the virtual host rental service, and the second occupation parameter is used for responding to the real-time cloud computing service.
In this embodiment, the terminal device is configured with an acquisition condition of an actual resource occupation parameter, and if it is detected that the current time or the network state of the current target service system satisfies the preset acquisition condition, the relevant operation of S1041 is executed. Specifically, the acquisition condition may be a time condition, that is, the terminal device is configured with an acquisition cycle or multiple acquisition nodes, and if it is detected that the current time meets the time condition, the acquisition process of the actual resource occupation parameter is triggered, and it is determined whether the allocation ratio needs to be adjusted. Optionally, the acquisition condition may be an actual occupied amount, that is, the terminal device sets a plurality of resource amount nodes according to the resource amount allocated to the first resource area and the second resource area, and if it is detected that the actual occupied amount of a certain resource area reaches the corresponding resource amount node at the current time, the relevant operation of S1041 is executed. The administrator may perform the relevant operation of S1041 by sending a collection instruction or other manual trigger.
In this embodiment, when it is determined that the current acquisition condition is satisfied, the terminal device may obtain, through the resource adjuster of each server cluster, the actual resource occupation parameters of all the servers in use in the corresponding cluster, thereby implementing multi-thread concurrent acquisition and improving the acquisition efficiency of the actual resource occupation parameters. On the other hand, in order to improve the acquisition accuracy, particularly for the real-time cloud computing service, the floating range of the instantaneous resource occupancy rate is large, so that the terminal device can control the resource regulator to acquire a plurality of real-time resource occupancy parameters for each in-use server at a preset acquisition frequency, the accuracy of the real-time resource occupancy parameters can be improved, and the influence caused by instantaneous floating is reduced.
Because the resources occupied by the virtual host lease service and the real-time cloud computing service are distributed based on the hardware resource pool of the whole server cluster, and the hardware resource distribution of each in-use server in the specific cluster is transparent for the terminal equipment, in order to count the real-time resource distribution condition of the whole cluster, the real-time resource quantity respectively occupied by the in-use server with respect to the two services can be detected when the terminal equipment collects the actual occupied resource quantity of the current time, and therefore the actual occupation proportion of the whole cluster can be determined through the actual occupied resource quantity of all in-use servers in the cluster.
In S1042, a first occupation mean and a first occupation standard deviation of the first resource area are calculated according to the plurality of first occupation parameters of each active server.
In S1043, a second occupancy mean and a second occupancy standard deviation of the second resource region are calculated according to the plurality of second occupancy parameters of each of the servers in use.
In this embodiment, the terminal device obtains actual resource occupancy rates of the active servers in the server cluster in multiple acquisition cycles, so that the total actual occupancy parameters of the acquisition cycles with respect to the first resource area may be determined according to the first occupancy parameters of all the active servers in the same acquisition cycle. Likewise, for each acquisition cycle, all of the first occupancy variables of the active servers in the cycle can be superimposed in order to determine the total actual occupancy variable for the first resource area in the cycle. Therefore, the terminal device may calculate a first average occupancy and a first standard deviation occupancy of the first resource region corresponding to the plurality of different acquisition periods. The second resource region may also be calculated in the above manner, which is not described herein again.
In S1044, importing the first occupancy mean value, the first occupancy label difference, the second occupancy mean value, and the second occupancy standard difference into an actual occupancy calculation model, and determining the actual occupancy ratio; the actual occupancy rate calculation model specifically comprises the following steps:
wherein, the actual occupancy rate is the actual occupancy proportion;
is a first occupancy mean; xi VM Is the first occupancy standard deviation;
is the second occupancy mean; xi Count Is the second occupancy standard deviation; VMmax is the amount of hardware resources of the first resource zone; countmax is the amount of hardware resources of the second resource region.
In this embodiment, the terminal device imports the four parameters obtained by the above calculation into a calculation model of the actual occupancy rate, and determines that the actual occupancy rate is obtained by the calculation related to the current acquisition operation. Because the actual occupancy rate not only considers the first occupancy mean value and the second occupancy mean value, but also introduces the occupancy standard deviation, the influence caused by the floating rate is reduced, and the accuracy of the actual occupancy rate is improved.
In the embodiment of the invention, when the acquisition condition is met, the plurality of actual resource occupation parameters are acquired, so that the actual resource occupation rate of the server cluster can be calculated through the plurality of actual resource occupation parameters, and the accuracy of the actual resource occupation rate is improved.
Fig. 3 shows a flowchart of a specific implementation of the method S101 for allocating network resources according to a third embodiment of the present invention. Referring to fig. 3, with respect to the embodiment described in fig. 1, a method S101 for allocating network resources provided in this embodiment includes: s1011 to S1013, which are specifically described below:
further, the dividing all the active servers in the available server list into a plurality of server clusters, and configuring a resource adjuster for each server cluster includes:
in S1011, an installation location of each of the active servers is obtained, and each of the active servers is marked on a preset map interface according to the installation location.
In this embodiment, the terminal device may perform division of the server cluster based on the installation location of each in-use server. In this case, the target service system may allocate the service request to the server cluster of the geographic zone according to the geographic zone described by the user terminal, so that the hop of the intermediate route may be reduced, thereby improving the speed of the service response.
In this embodiment, if the on-demand server can be configured with a positioning module, the local installation position can be obtained by the positioning module, and the installation position is fed back to the terminal device. If the active server is not provided with a positioning module, the installation location can be determined based on the gateway address from the gateway address where the active server is located. And marking each active server on a preset map interface by the terminal equipment according to the installation position so as to divide the active servers into clusters. Particularly, the terminal device can call an API (application programming interface) of the third-party map application, output the interface of the third-party map application on the local display module and mark each in-use server, so that a map program does not need to be rewritten, and the required development amount is reduced.
In S1012, a traversal frame is performed on the map interface through a preset cluster window, and all the active servers in the same cluster window are identified as belonging to the same server cluster.
In this embodiment, the terminal device may frame the servers in use through the cluster window according to the preset cluster window, so that the distance between the installation positions of the servers in the same server cluster is smaller than or equal to the preset distance threshold. Specifically, the terminal device may control the cluster window to slide on the map interface, so as to implement traversal framing, and the active servers in the same cluster window are identified as the same server cluster.
In S1013, the resource regulator is configured for each server cluster.
In this embodiment, in order to facilitate concurrent management of different clusters, so as to improve timeliness and accuracy of network resource management, the terminal device configures one resource regulator for each server cluster.
In the embodiment of the invention, the terminal equipment realizes the division of the server cluster according to the installation position of each in-use server, thereby improving the distribution operation of the subsequent service request and improving the distribution efficiency of the service request.
Fig. 4 shows a flowchart of a specific implementation of a method for allocating network resources according to a fourth embodiment of the present invention. Referring to fig. 4, with respect to the embodiment described in fig. 1 to fig. 3, in the method for allocating network resources provided in this embodiment, after the calculating the actual occupancy ratio according to the first occupancy and the second occupancy, the method further includes: s401 to S402, the details are as follows:
in S401, the initial allocation proportion and the actual occupation proportion obtained at each acquisition time are used as training samples, and the training samples are introduced into a multilayer feedforward neural network to calculate an expected allocation proportion.
In this embodiment, the terminal device is preset with a multi-layer feedforward RNN neural network, and can improve the accuracy of the initial allocation ratio according to the preset initial allocation ratio and the actual occupation ratio of each period, so that the terminal device generates a plurality of training samples based on the initial allocation ratio and the actual occupation ratio, introduces the training samples into the RNN neural network, and calculates the expected allocation ratio. If a new server cluster is detected or a capacity expansion request is received, the hardware resource pool may be partitioned according to the expected allocation proportion.
It should be noted that, because there are differences between the number of service requests and the service types of the server clusters, that is, the expected allocation ratio is different for different server clusters, it can match the service request situation of the user terminal of the server cluster.
In S402, if a system capacity expansion instruction is received, determining the amount of hardware resources of the capacity expansion server, and performing a hardware resource partitioning operation on the amount of hardware resources of the capacity expansion server according to the expected allocation proportion.
In this embodiment, if the terminal device receives a system capacity expansion instruction, that is, a new capacity expansion server is added to the server cluster, the hardware resources of the capacity expansion server need to be divided. Therefore, the terminal device may determine a first capacity expansion resource amount for the cloud host lease service and a second capacity expansion resource amount for the real-time cloud computing service according to the expected distribution ratio and the hardware resource amount of the capacity expansion server, and divide the hardware resources based on the two capacity expansion resource amounts.
In the embodiment of the invention, the expected distribution proportion is predicted according to the initial distribution proportion and the plurality of real-time occupation proportions, and the capacity expansion service period is divided based on the expected distribution proportion, so that the accuracy rate of the division operation is improved.
Fig. 5 is a flowchart illustrating a specific implementation of a method for allocating network resources according to a fifth embodiment of the present invention. Referring to fig. 5, with respect to the embodiments described in fig. 1 to fig. 3, the method for allocating network resources provided in this embodiment further includes: S501-S502, the details are as follows:
in S501, a resource report instruction is broadcast to each resource regulator, so that each resource regulator acquires the resource occupancy rate of the corresponding server cluster.
In this embodiment, in order to determine whether each server cluster needs to perform server capacity expansion, the terminal device sends a resource reporting instruction to each resource regulator, and collects resource occupation conditions in the server cluster to which the terminal device belongs through each resource regulator. The terminal device may set a trigger condition, such as a condition trigger and an event trigger, and if the preset trigger condition is currently met, execute the relevant operation of S501.
In S502, if any of the resource occupancy rates is greater than a preset capacity expansion threshold, sending capacity expansion prompting information to a terminal of an administrator.
In this embodiment, if the terminal device detects that the resource occupancy rate is less than or equal to the preset capacity expansion threshold, it indicates that the network resource of the server cluster is not in a saturated state, and may continue to respond to the service request of the user terminal; if the resource occupancy rate is greater than the capacity expansion threshold value, the server is in a saturated state, and capacity expansion prompt information is generated and sent to the terminal of the administrator, so that the administrator can expand the server cluster.
In the embodiment of the invention, the terminal equipment detects the resource occupation condition of the server cluster and automatically generates the capacity expansion prompt information, thereby improving the capacity expansion response efficiency.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by functions and internal logic of the process, and should not limit the implementation process of the embodiments of the present invention in any way.
Fig. 6 is a block diagram illustrating a configuration of an allocation apparatus for network resources according to an embodiment of the present invention, where the allocation apparatus for network resources includes units for performing steps in the corresponding embodiment of fig. 1. Please refer to fig. 1 and fig. 1 for the corresponding description of the embodiment. For convenience of explanation, only the portions related to the present embodiment are shown.
Referring to fig. 6, the apparatus for allocating network resources includes:
a resource regulator configuring unit 61, configured to obtain an available server list of a target service system, divide all active servers in the available server list into a plurality of server clusters, and configure a resource regulator for each server cluster;
a hardware resource pool establishing unit 62, configured to invoke the resource regulator to collect hardware resource amounts of the servers in use in the server cluster, and establish a hardware resource pool of the server cluster;
the hardware resource pool dividing unit 63 is used for dividing the hardware resource pool into a first resource area for responding to virtual host lease service and a second resource area for responding to real-time cloud computing service based on a preset initial allocation proportion;
an actual occupancy ratio obtaining unit 64, configured to collect, by the resource adjuster, a first occupancy rate of the first resource region and a second occupancy rate of the second resource region, and calculate an actual occupancy ratio according to the first occupancy rate and the second occupancy rate;
a hardware resource adjusting unit 65, configured to set the actual occupancy ratio as an initial allocation ratio if an absolute value of a difference between the actual occupancy ratio and the initial allocation ratio is greater than a preset adjustment threshold, and adjust the first resource region and the second resource region based on the actual occupancy ratio.
Optionally, the actual occupancy ratio acquiring unit 64 includes:
the acquisition triggering unit is used for acquiring a plurality of actual resource occupation parameters of each active server in the server cluster at a preset acquisition frequency if a preset acquisition condition is met; the actual resource occupation parameters include: the first occupation parameter is used for responding to the virtual host lease service, and the second occupation parameter is used for responding to the real-time cloud computing service;
the first occupation parameter calculation unit is used for calculating a first occupation mean value and a first occupation standard deviation of the first resource area according to the plurality of first occupation parameters of each active server;
a second occupation parameter calculation unit, configured to calculate a second occupation average and a second occupation standard deviation of the second resource region according to the plurality of second occupation parameters of each of the active servers;
the actual occupancy ratio calculation unit is used for importing the first occupancy mean value, the first occupancy labeling difference, the second occupancy mean value and the second occupancy standard difference into an actual occupancy ratio calculation model to determine the actual occupancy ratio; the actual occupancy rate calculation model specifically comprises:
wherein, the actual occupancy rate is the actual occupancy proportion;
is a first occupancy mean; xi VM Is the first occupancy standard deviation;
is the second occupancy mean; xi shape Count Is the second occupancy standard deviation; VMmax is firstThe amount of hardware resources of the resource zone; countmax is the amount of hardware resources in the second resource region.
Optionally, the resource adjuster configuration unit 61 includes:
the installation position acquisition unit is used for acquiring the installation position of each in-use server and marking each in-use server on a preset map interface according to the installation position;
the server cluster identification unit is used for traversing and framing on the map interface through a preset cluster window and identifying all the servers in use in the same cluster window as belonging to the same server cluster;
and the resource regulator creating unit is used for configuring the resource regulator for each server cluster.
Optionally, the apparatus for allocating network resources further includes:
the expected distribution proportion calculation unit is used for taking the initial distribution proportion and the actual occupation proportion obtained at each acquisition moment as training samples, introducing the training samples into a multilayer feedforward neural network, and calculating the expected distribution proportion;
and the capacity expansion operation response unit is used for determining the hardware resource amount of the capacity expansion server if a system capacity expansion instruction is received, and executing hardware resource division operation on the hardware resource amount of the capacity expansion server according to the expected distribution proportion.
Optionally, the apparatus for allocating network resources further includes:
a resource occupancy rate acquisition unit, configured to broadcast a resource report instruction to each resource regulator, so that each resource regulator acquires the resource occupancy rate of the corresponding server cluster;
and the capacity expansion prompting information sending unit is used for sending capacity expansion prompting information to a terminal of an administrator if any one of the resource occupancy rates is greater than a preset capacity expansion threshold value.
Therefore, in the allocation device for network resources provided in the embodiments of the present invention, the server for virtual host lease and the server for real-time cloud computing are disposed in the same server cluster, and even the same server can respond to two different service requests, manage hardware resources in the server cluster through the resource regulator, and dynamically allocate resource areas of the two services, thereby improving the utilization rate of resources.
Fig. 7 is a schematic diagram of a terminal device according to another embodiment of the present invention. As shown in fig. 7, the terminal device 7 of this embodiment includes: a processor 70, a memory 71 and a computer program 72 stored in said memory 71 and executable on said processor 70, such as an allocation program of network resources. The processor 70, when executing the computer program 72, implements the steps in the above-mentioned embodiments of the method for allocating network resources, such as S101 to S105 shown in fig. 1. Alternatively, the processor 70, when executing the computer program 72, implements the functions of the units in the above-described device embodiments, such as the functions of the modules 61 to 65 shown in fig. 6.
Illustratively, the computer program 72 may be divided into one or more units, which are stored in the memory 71 and executed by the processor 70 to accomplish the present invention. The unit or units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 72 in the terminal device 7. For example, the computer program 72 may be divided into a resource regulator configuration unit, a hardware resource pool establishing unit, a hardware resource pool dividing unit, an actual occupancy ratio acquiring unit, and a hardware resource adjusting unit, and the specific functions of the units are as described above.
The terminal device 7 may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor 70, a memory 71. It will be appreciated by those skilled in the art that fig. 7 is merely an example of a terminal device 7 and does not constitute a limitation of the terminal device 7 and may comprise more or less components than shown, or some components may be combined, or different components, for example the terminal device may further comprise input output devices, network access devices, buses, etc.
The Processor 70 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 71 may be an internal storage unit of the terminal device 7, such as a hard disk or a memory of the terminal device 7. The memory 71 may also be an external storage device of the terminal device 7, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the terminal device 7. Further, the memory 71 may also include both an internal storage unit and an external storage device of the terminal device 7. The memory 71 is used for storing the computer programs and other programs and data required by the terminal device. The memory 71 may also be used to temporarily store data that has been output or is to be output.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (8)
1. A method for allocating network resources, comprising:
the method comprises the steps of obtaining an available server list of a target service system, dividing all active servers in the available server list into a plurality of server clusters, and configuring a resource regulator for each server cluster;
calling the resource regulator to collect the hardware resource amount of each server in use in the server cluster, and establishing a hardware resource pool of the server cluster;
dividing the hardware resource pool into a first resource area for responding to virtual host lease service and a second resource area for responding to real-time cloud computing service based on a preset initial allocation proportion, wherein the method comprises the following steps: acquiring historical service records and calculating an initial distribution proportion;
acquiring a first occupancy rate of the first resource area and a second occupancy rate of the second resource area through the resource regulator, and calculating an actual occupancy ratio according to the first occupancy rate and the second occupancy rate;
if the absolute value of the difference between the actual occupation proportion and the initial distribution proportion is larger than a preset adjustment threshold, setting the actual occupation proportion as the initial distribution proportion, and adjusting the first resource region and the second resource region based on the actual occupation proportion;
the acquiring a first occupancy rate of the first resource zone and a second occupancy rate of the second resource zone through the resource regulator, and calculating an actual occupancy ratio according to the first occupancy rate and the second occupancy rate include:
if the preset acquisition condition is met, acquiring a plurality of actual resource occupation parameters of each server in use in the server cluster at a preset acquisition frequency; the actual resource occupation parameters include: the first occupation parameter is used for responding to the virtual host lease service, and the second occupation parameter is used for responding to the real-time cloud computing service;
calculating a first occupation average value and a first occupation standard deviation of the first resource area according to a plurality of first occupation parameters of each server in use;
calculating a second occupation mean value and a second occupation standard deviation of the second resource area according to the plurality of second occupation parameters of each server in use;
importing the first occupancy mean value, the first occupancy labeling difference, the second occupancy mean value and the second occupancy standard difference into an actual occupancy rate calculation model to determine the actual occupancy proportion;
the actual occupancy rate calculation model specifically comprises the following steps:
wherein, the actual occupancy ratio is the actual occupancy ratio;
is a first occupancy mean; xi VM Is the first occupancy standard deviation;
is the second occupancy mean; xi shape Count Is the second occupancy standard deviation; VMmax is the amount of hardware resources of the first resource zone; countmax is the amount of hardware resources in the second resource region.
2. The allocation method according to claim 1, wherein the dividing all active servers in the list of available servers into a plurality of server clusters, and configuring a resource regulator for each server cluster comprises:
acquiring the installation position of each in-use server, and marking each in-use server on a preset map interface according to the installation position;
traversing and framing on the map interface through a preset cluster window, and identifying all the servers in use in the same cluster window as belonging to the same server cluster;
and configuring the resource regulator for each server cluster.
3. The allocation method according to any one of claims 1-2, characterized in that after said calculating an actual occupancy proportion from said first occupancy and said second occupancy, it further comprises:
taking the initial distribution proportion and the actual occupation proportion obtained at each acquisition moment as training samples, introducing the training samples into a multilayer feedforward neural network, and calculating an expected distribution proportion;
and if a system capacity expansion instruction is received, determining the hardware resource amount of the capacity expansion server, and executing hardware resource partitioning operation on the hardware resource amount of the capacity expansion server according to the expected distribution proportion.
4. The allocation method according to any one of claims 1-2, further comprising:
broadcasting a resource reporting instruction to each resource regulator so that each resource regulator acquires the resource occupancy rate of the corresponding server cluster;
and if any resource occupancy rate is greater than a preset capacity expansion threshold value, sending capacity expansion prompt information to a terminal of an administrator.
5. An apparatus for allocating network resources, comprising:
the resource regulator configuration unit is used for acquiring an available server list of a target service system, dividing all the servers in use in the available server list into a plurality of server clusters, and configuring a resource regulator for each server cluster;
the hardware resource pool establishing unit is used for calling the resource regulator to acquire the hardware resource quantity of each server in use in the server cluster and establishing a hardware resource pool of the server cluster;
the hardware resource pool dividing unit is used for dividing the hardware resource pool into a first resource area used for responding to virtual host leasing service and a second resource area used for responding to real-time cloud computing service based on a preset initial distribution proportion, and comprises: acquiring historical service records and calculating an initial distribution proportion;
the actual occupation ratio acquiring unit is used for acquiring a first occupancy rate of the first resource area and a second occupancy rate of the second resource area through the resource regulator and calculating the actual occupation ratio according to the first occupancy rate and the second occupancy rate;
a hardware resource adjusting unit, configured to set the actual occupation proportion as an initial allocation proportion and adjust the first resource region and the second resource region based on the actual occupation proportion if an absolute value of a difference between the actual occupation proportion and the initial allocation proportion is greater than a preset adjustment threshold;
the actual occupation ratio acquiring unit includes:
the acquisition triggering unit is used for acquiring a plurality of actual resource occupation parameters of each active server in the server cluster at a preset acquisition frequency if a preset acquisition condition is met; the actual resource occupation parameters include: the first occupation parameter is used for responding to the virtual host lease service, and the second occupation parameter is used for responding to the real-time cloud computing service;
a first occupation parameter calculation unit, configured to calculate a first occupation average and a first occupation standard deviation of the first resource region according to the plurality of first occupation parameters of each of the active servers;
a second occupation parameter calculation unit, configured to calculate a second occupation average and a second occupation standard deviation of the second resource region according to the plurality of second occupation parameters of each of the active servers;
the actual occupancy ratio calculation unit is used for importing the first occupancy mean value, the first occupancy labeling difference, the second occupancy mean value and the second occupancy standard difference into an actual occupancy ratio calculation model to determine the actual occupancy ratio; the actual occupancy rate calculation model specifically comprises the following steps:
wherein, the actual occupancy ratio is the actual occupancy ratio;
is a first occupancy mean; xi VM Is the first occupancy standard deviation;
is a second occupancy mean; xi Count Is the second occupancy standard deviation; VMmax is the amount of hardware resources of the first resource zone; countmax is the amount of hardware resources in the second resource region.
6. The allocation device according to claim 5, wherein the resource regulator configuration unit comprises:
the installation position acquisition unit is used for acquiring the installation position of each in-use server and marking each in-use server on a preset map interface according to the installation position;
the server cluster identification unit is used for traversing and framing on the map interface through a preset cluster window and identifying all the servers in use in the same cluster window as belonging to the same server cluster;
and the resource regulator creating unit is used for configuring the resource regulator for each server cluster.
7. A terminal device, characterized in that the terminal device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, the processor executing the computer program with the steps of the method according to any of claims 1 to 4.
8. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of a method according to any one of claims 1 to 4.
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| PCT/CN2019/091499 WO2020143164A1 (en) | 2019-01-08 | 2019-06-17 | Network resource allocation method and device |
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| CN110795233B (en) * | 2019-09-18 | 2022-04-05 | 北京你财富计算机科技有限公司 | Distributed resource allocation method and device and electronic equipment |
| CN110750312A (en) * | 2019-10-17 | 2020-02-04 | 中科寒武纪科技股份有限公司 | Hardware resource configuration method and device, cloud side equipment and storage medium |
| CN111211998A (en) * | 2019-12-12 | 2020-05-29 | 北京淇瑀信息科技有限公司 | Resource allocation method and device capable of elastically expanding capacity and electronic equipment |
| CN110995856B (en) * | 2019-12-16 | 2022-09-13 | 上海米哈游天命科技有限公司 | Method, device and equipment for server expansion and storage medium |
| CN113315719A (en) * | 2020-02-27 | 2021-08-27 | 阿里巴巴集团控股有限公司 | Traffic scheduling method, device, system and storage medium |
| CN111538597B (en) * | 2020-04-27 | 2024-02-27 | 贝壳技术有限公司 | Resource allocation method, device, computer readable storage medium and electronic equipment |
| CN111708629B (en) * | 2020-04-30 | 2023-09-19 | 咪咕文化科技有限公司 | Resource allocation method and device, electronic equipment and storage medium |
| CN111562985B (en) * | 2020-05-09 | 2024-03-22 | 上海商汤智能科技有限公司 | Resource management method and device, electronic equipment and storage medium |
| CN113938392B (en) * | 2020-07-09 | 2023-11-14 | 亚信科技（南京）有限公司 | Resource allocation method, device, electronic equipment and computer readable storage medium |
| CN112367708B (en) * | 2020-10-30 | 2023-05-26 | 新华三技术有限公司 | Network resource allocation method and device |
| CN112473141A (en) * | 2020-12-14 | 2021-03-12 | 网易（杭州）网络有限公司 | Game cluster management method and device |
| CN112631730A (en) * | 2020-12-30 | 2021-04-09 | 中国建设银行股份有限公司 | Model processing method and device, equipment and computer readable storage medium |
| CN113342885B (en) * | 2021-06-15 | 2022-08-12 | 深圳前海微众银行股份有限公司 | Data import method, device, equipment and computer program product |
| CN115550315B (en) * | 2022-08-10 | 2023-08-29 | 北京中关村软件园发展有限责任公司 | Digital cloud service management method and system based on next generation internet |
| CN116069513B (en) * | 2023-04-04 | 2023-06-23 | 上海钐昆网络科技有限公司 | Cost determination method, device, electronic equipment and storage medium |
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