CN117998594B - 5G power multi-service slice resource allocation method, device and system - Google Patents
5G power multi-service slice resource allocation method, device and system Download PDFInfo
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Abstract
本发明提供一种5G电力多业务切片资源分配方法、装置及系统，属于无线通信技术领域。该方法包括：获取电网的通信网络的历史数据和当前业务需求；基于历史数据和当前业务需求，预测各业务的网络资源需求；基于各业务的网络资源需求，获得初始网络资源分配策略，形成资源映射表；资源映射表用于记录每个业务对应的网络切片的资源分配信息；实时接收本地控制器发送的资源使用信息，并对初始网络资源分配策略进行优化，更新资源映射表；基于更新后的资源映射表，将优化后的网络资源分配策略下发至本地控制器，对电网的通信网络的资源进行分配。本发明能够合理地分配有限的网络资源，降低资源分配拥塞的发生概率，提高电力系统的运行效率。
The present invention provides a 5G power multi-service slice resource allocation method, device and system, which belongs to the field of wireless communication technology. The method includes: obtaining historical data and current business needs of the communication network of the power grid; predicting the network resource needs of each business based on the historical data and current business needs; obtaining the initial network resource allocation strategy based on the network resource needs of each business, and forming a resource mapping table; the resource mapping table is used to record the resource allocation information of the network slice corresponding to each business; receiving the resource usage information sent by the local controller in real time, and optimizing the initial network resource allocation strategy, and updating the resource mapping table; based on the updated resource mapping table, the optimized network resource allocation strategy is sent to the local controller to allocate the resources of the communication network of the power grid. The present invention can reasonably allocate limited network resources, reduce the probability of resource allocation congestion, and improve the operating efficiency of the power system.
Description
Technical Field
The present invention relates to the field of wireless communications technologies, and in particular, to a method, an apparatus, and a system for allocating 5G power multi-service slice resources.
Background
The 5G (5 th Generation Mobile Communication Technology, fifth generation mobile communication technology) communication Network merges Software-Defined Network (SDN) and Network function virtualization (Network Functions Virtualization, NFV) technologies, and implements a plurality of programmable, flexible and modularized logic sub-networks on the same physical Network for power industry users as required, each sub-Network can be tailored to the communication transmission requirements of a specific service, and the sub-networks are called Network Slices (NS).
With the development of 5G communication technology, the degree of intellectualization and networking of the power system is increasing. In the power system, the multi-service slicing technology can meet the requirements of different services, such as power scheduling, power transaction, intelligent home and the like. Based on the 5G communication technology, a customized 'industry private network' can be created for power industry users, the requirements on the safety, reliability and flexibility of power grid business are better met, differentiated service guarantee is realized, and the autonomous controllability of power grid enterprises on own business is improved.
In the related technology, information interaction data generated in the wireless communication process between a user terminal and a base station in an actual wireless communication scene are collected, preprocessed and matched with a data format input into a prediction network, and based on the LSTM of a cyclic neural network as a main part of the prediction network, the information interaction data is input into the trained prediction network to obtain a resource allocation scheme. But in the context of multi-service networks, we have transitioned from traditional approaches to multi-functional integrated demand response to demand response. The mixed demand of a plurality of complex services may cause resource allocation congestion, thereby affecting the normal deployment and operation of the network and seriously causing paralysis of the services. Therefore, how to reasonably allocate the limited network resources, reduce the occurrence probability of resource allocation congestion, and improve the operation efficiency of the power system is a problem to be solved urgently.
Disclosure of Invention
The embodiment of the invention provides a 5G power multi-service slice resource allocation method, device and system, which are used for reasonably allocating limited network resources, reducing the occurrence probability of resource allocation congestion and improving the operation efficiency of a power system.
In a first aspect, an embodiment of the present invention provides a method for allocating resources of 5G power multi-service slices, including:
acquiring historical data and current business requirements of a communication network of a power grid;
predicting network resource requirements of each service based on historical data and current service requirements;
acquiring an initial network resource allocation strategy based on network resource requirements of each service to form a resource mapping table, wherein the resource mapping table is used for recording resource allocation information of network slices corresponding to each service;
receiving resource use information sent by a local controller in real time;
Optimizing an initial network resource allocation strategy based on the resource use information, and updating a resource mapping table;
based on the updated resource mapping table, the optimized network resource allocation strategy is issued to the local controller, and the resources of the communication network of the power grid are allocated.
In a possible implementation manner of the first aspect, based on network resource requirements of each service, an initial network resource allocation policy is obtained, and a resource mapping table is formed, including:
Based on network resource requirements of each service, an initial network resource allocation strategy is obtained by utilizing a pre-established frequency spectrum resource quantity minimization model and a pre-established channel capacity maximization model, wherein the initial network resource allocation strategy comprises a frequency spectrum resource block and an allocation result of optimal power;
And storing the spectrum resource blocks of each network slice and the optimal power allocation result to form a resource mapping table.
In a possible implementation manner of the first aspect, the objective function of the spectrum resource quantity minimization model is expressed as:
Constraints of the spectrum resource quantity minimization model are expressed as:
Wherein P represents a power allocation vector, alpha n,i is an indication variable for allocating a channel N to a service node i, alpha n,k is 0 or 1;N represents the total number of channels, K represents the total number of service nodes, B n represents the number of frequency spectrum Resource Blocks (RBs) of the channel N, P i represents the power allocated to the service node i, h n,i represents the channel fading factor of the service node i on the channel N, and N 0 represents the noise power spectral density; representing minimum rate requirements of the service node i; Representing the maximum tolerance time delay from end to end of the channel where the service node i is located; representing the transmission delay of the service node i in the corresponding local controller; The time delay from the central controller to the local controller corresponding to the service node i is represented, and the service nodes are in one-to-one correspondence with the network slices.
In a possible implementation manner of the first aspect, optimizing an initial network resource allocation policy based on the resource usage information, and updating the resource mapping table includes:
based on the resource use information, comparing the resource use information with an initial network resource allocation strategy to obtain a comparison result;
based on the comparison result, marking the corresponding network slice on the resource mapping table;
and based on the marked network slice, semi-dynamically optimizing an initial network resource allocation strategy and updating a resource mapping table.
In a possible implementation manner of the first aspect, the comparison result includes a difference value between the resource usage information of the network slice and the initial network resource allocation policy;
Based on the comparison, marking the corresponding network slice on the resource mapping table, including:
If the difference value between the resource use information of the network slice and the initial network resource allocation strategy exceeds a threshold value, marking the network slice on the resource mapping table as a dynamic application slice;
if the difference value between the resource usage information of the network slice and the initial network resource allocation strategy does not exceed the threshold value, marking the network slice on the resource mapping table as a static application slice.
In a possible implementation manner of the first aspect, the marked network slice includes a dynamic application slice and a static application slice;
Based on the marked network slice, semi-dynamically optimizing an initial network resource allocation strategy, and updating a resource mapping table, wherein the method comprises the following steps:
based on the difference value between the resource use information of the dynamic application slice and the initial network resource allocation strategy, the initial network resource allocation strategy of the dynamic application slice is optimized, a resource mapping table is updated, a first reserved resource is set, the first reserved resource is used for carrying out dynamic application acquisition by a local controller corresponding to the dynamic application slice, and the initial network resource allocation strategy of the static application slice is kept unchanged.
In a possible implementation manner of the first aspect, based on the updated resource mapping table, the method issues an optimized network resource allocation policy to the local controller, allocates resources of a communication network of the power grid, including:
Processing the updated resource mapping table to obtain a data signal of an optimized network resource allocation strategy, wherein the optimized network resource allocation strategy comprises a network resource allocation strategy of a dynamic application slice, a network resource allocation strategy of a static application slice and a network resource allocation strategy of a first reserved resource;
the local controller is used for decoding the received data signals;
and if the decoding result is correct, opening the network slice of the corresponding service to the local controller.
In a possible implementation manner of the first aspect, the optimized network resource allocation policy includes a network resource allocation policy of a second reserved resource, where the second reserved resource is used for dynamic emergency application, and a priority of the dynamic emergency application is higher than a priority of the dynamic application.
In a second aspect, an embodiment of the present invention provides a 5G power multi-service slice resource allocation apparatus, including:
the acquisition module is used for historical data and current service requirements of a communication network of the power grid;
The prediction module is used for predicting the network resource requirements of each service based on the historical data and the current service requirements;
The system comprises an initial resource allocation module, a resource mapping table, a network slice and a network slice, wherein the initial resource allocation module is used for acquiring an initial network resource allocation strategy based on the network resource requirement of each service to form the resource mapping table;
the receiving module is used for receiving the resource use information sent by the local controller in real time;
the initial resource allocation updating module is used for optimizing an initial network resource allocation strategy based on the resource use information and updating a resource mapping table;
The resource allocation module is used for issuing the optimized network resource allocation strategy to the local controller based on the updated resource mapping table, and allocating the resources of the communication network of the power grid.
In a third aspect, an embodiment of the present invention provides a 5G power multi-service slicing resource allocation system, which is characterized by including a central controller, a slicing network and a local controller;
The central controller is used for executing the 5G power multi-service slice resource allocation method as in the first aspect, and uniformly managing and allocating the resources of the communication network of the power grid.
The local controller is used for extracting resource use information from real-time data and feedback information of the slicing network, and the slicing network comprises network slices corresponding to all services.
The embodiment of the invention provides a 5G power multi-service slicing resource allocation method, device and system, which are used for predicting network resource requirements of each service through historical data and current service requirements of a communication network of a power grid and carrying out mapping processing on the network resource requirements to form a resource mapping table related to an initial network resource allocation strategy, so that the occurrence probability of allocation congestion is reduced. And then, optimizing an initial network resource allocation strategy by utilizing the resource utilization information, realizing the optimized allocation of 5G network slice resources, reasonably allocating limited network resources and improving the operation efficiency of the power system.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is an application scenario schematic diagram of a 5G power multi-service slice resource allocation method provided by an embodiment of the present invention;
Fig. 2 is a schematic flow chart of a method for allocating resources of 5G power multi-service slices according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a 5G power multi-service slice resource allocation device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the following description will be made by way of specific embodiments with reference to the accompanying drawings.
The application scenario of the invention is shown in fig. 1, a central controller can be deployed on a core network or a cloud end, is responsible for resource management and allocation of a communication network of a power grid, and a local controller can be deployed on a base station or an access network, and is responsible for real-time control and adjustment of network slices. The information interaction between the central controller and the local controller can be realized through the existing communication protocol or the custom protocol. The central controller optimizes the network resource allocation strategy of the network slice according to the feedback information of the local controller, maps the optimized network resource allocation strategy, and the local controller executes the optimized network resource allocation strategy to dynamically adjust the allocation of each network slice resource of the virtual machine so as to adapt to the continuously changing service demands and network environments.
The invention realizes the dynamic allocation and adjustment of the 5G power multi-service slicing resources through the cooperative work of the central controller and the local controller, improves the resource utilization rate and the stability and reliability of a power system, reduces the occurrence probability of resource allocation congestion, and avoids the waste of network resources and the reduction of service quality.
Fig. 2 is a flowchart of an implementation of a method for allocating resources of 5G power multi-service slices according to an embodiment of the present invention, which is described in detail below:
A5G power multi-service slice resource allocation method comprises the following steps:
step 101, obtaining historical data and current service requirements of a communication network of a power grid.
An exemplary central controller may collect historical data for the communication network of the power grid, the historical data including resource usage information, traffic volume, etc. for each service. At the same time, current service demand information, such as data of the service volume, user behavior, etc., of each service is collected.
The central controller needs to take into account some anomalies when predicting the network resource demands of each service. For example, a certain network slice suddenly experiences a large resource consumption, a sudden increase in traffic, etc. Therefore, an abnormality detection and processing algorithm, such as a statistical method or a visual method, can be adopted to timely find and process abnormal data under the abnormal conditions, so as to ensure the reliability and stability of the data.
Step 102, predicting network resource requirements of each service based on the historical data and the current service requirements.
Exemplary services are power scheduling, power trading, smart home, etc. Aiming at the processed historical data of the same type of service, which is obtained in the step 101 by utilizing the type of service, the historical data is analyzed by adopting algorithms such as time sequence analysis, linear regression model and the like, and the resource demand of the type of service in a period of time in the future is predicted. And correcting the trend of the resource demand in a period of time in the future by utilizing the processed resource information of the current service demand to obtain the network resource demand of each service. In the correction process, the resource demand of the service in the future period can be compared with the current service demand, the prediction error and the difference can be found out, and the reason of the prediction error, such as service change, market change, technical change and the like, can be analyzed. The prediction model parameters are adjusted based on the cause of the prediction error, for example, the prediction accuracy is improved by changing the model parameters, introducing new variables or adjusting algorithms, and the like.
In this embodiment, the processed resource information of the current service requirement is utilized to correct the trend of the resource requirement in a period of time in the future, so as to improve the accuracy of the network resource requirement of each service, and provide a more reliable reference for the subsequent resource allocation.
Step 103, based on the network resource requirement of each service, obtaining an initial network resource allocation strategy to form a resource mapping table.
The resource mapping table is a global resource mapping table, and the resource allocation information of the network slice corresponding to each service is recorded. A resource mapping table is used to store data associated between slice identifiers and the amount of resources allocated, and this resource mapping table may be implemented using a database or distributed storage.
In this embodiment, step 103 includes obtaining an initial network resource allocation policy based on network resource requirements of each service by using a pre-established spectrum resource quantity minimizing model and a pre-established channel capacity maximizing model, where the initial network resource allocation policy includes a spectrum resource block and an allocation result of optimal power. And storing the spectrum resource blocks of the network slices corresponding to each service and the optimal power allocation result to form a resource mapping table.
And solving the distribution result of the optimal power of each network slice by using a pre-established channel capacity maximization model and information obtained from each service node in the physical network. Each service node in the physical network corresponds to each network slice in the network slice layer one by one.
The objective function of the channel capacity maximization model is expressed as:
C is the communication network channel capacity of a power grid, P si is the transmitting power from a local controller to an ith service node, P i is the power of the ith service node, P is the sum of the transmitting power of the local controller and the power of all service nodes, H si is the channel strength from the local controller to the ith service node, H id is the channel strength from the ith service node to a user end, gaussian noise from each service node to the user end is distributed according to (0, sigma 2), sigma is the standard deviation of the Gaussian noise from each service node to the user end, and n is the number of service nodes. The different service nodes mentioned above represent different types of services.
The constraints of the channel capacity maximization model are expressed as:
wherein 0<P si<P,0<Pi < P.
Comprehensively considering the quality of channels at two ends of the ith service node, and calculating the weight of the channel intensity by adopting a harmonic average value as follows:
w i represents the weight of the power of the ith service node, and the power of the ith service node is:
Where P r is the sum of the power of all traffic nodes.
And obtaining an allocation result of the spectrum resource blocks by using a pre-established spectrum resource quantity minimization model.
The power of each service node obtained above is involved in spectrum resource allocation. The objective function of the spectrum resource quantity minimization model is expressed as:
Constraints of the spectrum resource quantity minimization model are expressed as:
Wherein P represents a power allocation vector, alpha n,i is an indication variable for allocating a channel N to a service node i, alpha n,k is 0 or 1;N represents the total number of channels, K represents the total number of service nodes, B n represents the number of frequency spectrum Resource Blocks (RBs) of the channel N, P i represents the power allocated to the service node i, h n,i represents the channel fading factor of the service node i on the channel N, and N 0 represents the noise power spectral density; representing minimum rate requirements of the service node i; Representing the maximum tolerance time delay from end to end of the channel where the service node i is located; representing the transmission delay of the service node i in the corresponding local controller; The time delay from the central controller to the local controller corresponding to the service node i is represented, and the service nodes are in one-to-one correspondence with the network slices. The frequency spectrum resource blocks of the network slice are frequency spectrum resource blocks of channels allocated to the network slice, the bandwidth allocation variable characterizes the allocation condition of the frequency spectrum resource blocks, the dynamic allocation of the bandwidth is completed by adjusting the number of the Resource Blocks (RBs), and different RB numbers correspond to different subcarrier numbers.
And allocating the channel n to the service node i, wherein the channel has a preset corresponding relation with the service node i, alpha n,i is 0 if any channel n and any service node i do not accord with the preset corresponding relation, and alpha n,i is 1 if any channel n and any service node i accord with the preset corresponding relation.
The resource allocation controller is composed of the central controller and the local controller, the resource allocation controller maps the network slices onto the service nodes in the physical network by utilizing the resource allocation table, the power allocated to the service nodes is the power of the corresponding network slices, an optimal power allocation scheme for each service node is obtained, the frequency spectrum resource blocks allocated to the channels of the service nodes are the frequency resource blocks allocated to the channels of the corresponding network slices, an allocation scheme of frequency resources is obtained, and the resource allocation table is formed, so that effective management and allocation of resources are realized.
Illustratively, each row in the resource mapping table represents a network slice containing an identifier of the network slice and the type of resource allocated, e.g., spectrum resource, transmission rate, etc. Each column in the resource mapping table records the resource allocation information corresponding to the network slice, including spectrum resource block, transmitting power, network bandwidth, processing capacity, storage space, etc. And the creation and maintenance of the resource mapping table may be accomplished using a programming language or tool.
Further examples, a table or array may be created in which each row represents a network slice. In the table, the first column contains a network slice identifier, such as an ID or name. In a second or other subsequent column, the resources associated with the network slice are stored. Thus, by looking up a particular row in the resource mapping table, the resource corresponding to a given network slice identifier can be found. Likewise, by looking up a particular column in the table, all network slices that use a particular resource can be found.
It should be noted that the resource mapping table formed by using a table or an array is only an example, and is not a limitation on the form of the resource mapping table.
And 104, receiving the resource use information sent by the local controller in real time.
The central controller can receive the resource usage information fed back by the local controller, such as power, network flow, equipment state, user behavior and other related data of each service node, and analyze and process the information, and adjust or optimize the initial network resource allocation policy in the following process so as to improve the adaptation degree of the network resource allocation policy and the efficient operation of the system.
And 105, optimizing an initial network resource allocation strategy based on the resource use information, and updating a resource mapping table.
For example, for those network slices that often use a large amount of resources during peak hours, their scheduling policy may be adjusted to use less resources during off-peak hours to ensure that the new scheduling policy does not affect the stability and performance of the system.
In this embodiment, step 105 includes:
The method comprises the steps of obtaining a resource mapping table, comparing the resource using information with an initial network resource allocation strategy to obtain a comparison result, marking corresponding network slices on the resource mapping table based on the comparison result, and semi-dynamically optimizing the initial network resource allocation strategy based on the marked network slices to update the resource mapping table.
Illustratively, the comparison result includes a difference between the resource usage information of the network slice and the initial network resource allocation policy.
Based on the comparison result, marking the corresponding network slice on the resource mapping table comprises marking the network slice on the resource mapping table as a dynamic application slice if the difference value between the resource usage information of the network slice and the initial network resource allocation strategy exceeds a threshold value, and marking the network slice on the resource mapping table as a static application slice if the difference value between the resource usage information of the network slice and the initial network resource allocation strategy does not exceed the threshold value.
For example, if the difference between the power of the service node corresponding to the network slice and the power of the network slice set in the initial network resource allocation policy exceeds a first threshold, or the difference between the number of spectrum resource blocks of the service node corresponding to the network slice and the number of spectrum resource blocks of the network slice set in the initial network resource allocation policy exceeds a second threshold, the network slice on the resource mapping table is marked as a dynamic application slice. And if the difference value between the power of the service node corresponding to the network slice and the power of the network slice set in the initial network resource allocation strategy does not exceed a first threshold value, and the difference value between the number of the spectrum resource blocks of the service node corresponding to the network slice and the number of the spectrum resource blocks of the network slice set in the initial network resource allocation strategy does not exceed a second threshold value, marking the network slice on the resource mapping table as a static application slice.
The process can automatically mark as dynamic application slice by setting the trigger when the difference exceeds the threshold value, so that the resource adjustment is convenient to automatically carry out.
Illustratively, the marked network slices include dynamic application slices and static application slices.
Based on the marked network slice, the initial network resource allocation strategy is semi-dynamically optimized, and a resource mapping table is updated, wherein the resource mapping table is updated, the initial network resource allocation strategy of the dynamic application slice is optimized based on the difference value between the resource use information of the dynamic application slice and the initial network resource allocation strategy, the resource mapping table is updated, a first reserved resource is set, the first reserved resource is used for carrying out dynamic application and acquisition with a local controller corresponding to the dynamic application slice, and the initial network resource allocation strategy of the static application slice is kept unchanged.
Illustratively, if the difference between the resource usage information of the network slice and the initial network resource allocation policy exceeds a threshold, the size of the network slice is adjusted by scheduling. Adjusting the size of the network slice includes adjusting a power or a spectral resource block of the network slice. The difference values are all absolute values.
Because the service resource requirement of the dynamic application section part has larger change, after optimizing the resource allocation, if the allocated resource cannot meet the unexpected condition of the resource requirement of the service, the dynamic application section can be applied from the first reserved resource, thereby meeting the resource requirement of the service, avoiding the robbing of the service resource, reducing the occurrence probability of the congestion of the resource allocation and ensuring the stable operation of the power system and the normal operation of the service.
The optimized network resource allocation policy further comprises a network resource allocation policy of a second reserved resource, wherein the second reserved resource is used for dynamic emergency application, and the priority of the dynamic emergency application is higher than that of the dynamic application. And for dynamic application slices except for dynamic emergency application, setting and adjusting priority according to the preset service importance degree and the utilization rate of each resource.
And step 106, based on the updated resource mapping table, the optimized network resource allocation strategy is issued to the local controller, and the resources of the communication network of the power grid are allocated.
In this embodiment, step 106 includes:
The method comprises the steps of processing an updated resource mapping table to obtain a data signal of an optimized network resource allocation strategy, wherein the optimized network resource allocation strategy comprises a network resource allocation strategy for dynamically applying for slicing, a network resource allocation strategy for statically applying for slicing and a network resource allocation strategy for first reserved resources, sending the data signal to a local controller, decoding the received data signal by the local controller, receiving a decoding result sent by the local controller, checking the decoding result, and opening a corresponding network slice for the local controller if the decoding result is correct.
The data signals carry ultra-high reliability and low-delay communication (ultra reliable low latency communications, URLLC) service type indication and URLLC service frequency domain resources, the local controller is arranged to decode data packets of different time nodes by the received data signals, and only if the decoded service type corresponds to the service frequency domain resources, the local controller can receive corresponding control instructions, and can execute corresponding optimized network resource allocation strategies, so that the allocation of each network slice resource of the virtual machine is dynamically adjusted, and the problems of data delay and service conflict in the prior art are solved.
According to the embodiment of the invention, the network resource requirements of each service are predicted through the historical data and the current service requirements of the communication network of the power grid, and are mapped to form the resource mapping table related to the initial network resource allocation strategy, so that the occurrence probability of allocation congestion is reduced. And then, optimizing an initial network resource allocation strategy by utilizing the resource utilization information, realizing the optimized allocation of 5G network slice resources, reasonably allocating limited network resources and improving the operation efficiency of the power system.
Through the cooperative work of the central controller and the local controller, the dynamic allocation and adjustment of the 5G power multi-service slicing resources are realized, and the resource utilization rate and the stability and reliability of a power system are improved.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
The following are device embodiments of the invention, for details not described in detail therein, reference may be made to the corresponding method embodiments described above.
Fig. 3 is a schematic structural diagram of a 5G power multi-service slice resource allocation device according to an embodiment of the present invention, and for convenience of explanation, only a portion relevant to the embodiment of the present invention is shown, which is described in detail below:
As shown in fig. 3, the 5G power multi-service slice resource allocation apparatus 200 includes an acquisition module 201, a prediction module 202, an initial resource allocation module 203, a reception module 204, an initial resource allocation update module 205, and a resource allocation module 206.
The module 201 is obtained for historical data and current business requirements of the communication network of the power grid.
A prediction module 202, configured to predict a network resource requirement of each service based on the historical data and the current service requirement.
The initial resource allocation module 203 is configured to obtain an initial network resource allocation policy based on network resource requirements of each service to form a resource mapping table, where the resource mapping table is configured to record resource allocation information of a network slice corresponding to each service.
And the receiving module 204 is configured to receive the resource usage information sent by the local controller in real time.
The initial resource allocation update module 205 is configured to optimize an initial network resource allocation policy based on the resource usage information, and update a resource mapping table.
The resource allocation module 206 is configured to issue the optimized network resource allocation policy to the local controller based on the updated resource mapping table, and allocate the resources of the communication network of the power grid.
According to the embodiment of the invention, the network resource requirements of each service are predicted through the historical data and the current service requirements of the communication network of the power grid, and are mapped to form the resource mapping table related to the initial network resource allocation strategy, so that the occurrence probability of allocation congestion is reduced. And then, optimizing an initial network resource allocation strategy by utilizing the resource utilization information, realizing the optimized allocation of 5G network slice resources, reasonably allocating limited network resources and improving the operation efficiency of the power system.
In one possible implementation, the initial resource allocation module 203 is specifically configured to:
Based on network resource requirements of each service, an initial network resource allocation strategy is obtained by utilizing a pre-established frequency spectrum resource quantity minimization model and a pre-established channel capacity maximization model, wherein the initial network resource allocation strategy comprises a frequency spectrum resource block and an allocation result of optimal power;
And storing the spectrum resource blocks of each network slice and the optimal power allocation result to form a resource mapping table.
In one possible implementation, in the initial resource allocation module 203, the objective function of the spectrum resource quantity minimization model is expressed as:
Constraints of the spectrum resource quantity minimization model are expressed as:
Wherein P represents a power allocation vector, alpha n,i is an indication variable for allocating a channel N to a service node i, alpha n,k is 0 or 1;N represents the total number of channels, K represents the total number of service nodes, B n represents the number of frequency spectrum Resource Blocks (RBs) of the channel N, P i represents the power allocated to the service node i, h n,i represents the channel fading factor of the service node i on the channel N, and N 0 represents the noise power spectral density; representing minimum rate requirements of the service node i; Representing the maximum tolerance time delay from end to end of the channel where the service node i is located; representing the transmission delay of the service node i in the corresponding local controller; The time delay from the central controller to the local controller corresponding to the service node i is represented, and the service nodes are in one-to-one correspondence with the network slices.
In one possible implementation, the initial resource allocation update module 205 is specifically configured to:
based on the resource use information, comparing the resource use information with an initial network resource allocation strategy to obtain a comparison result;
based on the comparison result, marking the corresponding network slice on the resource mapping table;
and based on the marked network slice, semi-dynamically optimizing an initial network resource allocation strategy and updating a resource mapping table.
In one possible implementation, in the initial resource allocation update module 205, the comparison result includes a difference between the resource usage information of the network slice and the initial network resource allocation policy.
Based on the comparison, marking the corresponding network slice on the resource mapping table, including:
If the difference value between the resource use information of the network slice and the initial network resource allocation strategy exceeds a threshold value, marking the network slice on the resource mapping table as a dynamic application slice;
if the difference value between the resource usage information of the network slice and the initial network resource allocation strategy does not exceed the threshold value, marking the network slice on the resource mapping table as a static application slice.
In one possible implementation, in the initial resource allocation update module 205, the marked network slices include dynamic application slices and static application slices;
Based on the marked network slice, semi-dynamically optimizing an initial network resource allocation strategy, and updating a resource mapping table, wherein the method comprises the following steps:
based on the difference value between the resource use information of the dynamic application slice and the initial network resource allocation strategy, the initial network resource allocation strategy of the dynamic application slice is optimized, a resource mapping table is updated, a first reserved resource is set, the first reserved resource is used for carrying out dynamic application acquisition by a local controller corresponding to the dynamic application slice, and the initial network resource allocation strategy of the static application slice is kept unchanged.
In one possible implementation, the resource allocation module 206 is specifically configured to:
Processing the updated resource mapping table to obtain a data signal of an optimized network resource allocation strategy, wherein the optimized network resource allocation strategy comprises a network resource allocation strategy of a dynamic application slice, a network resource allocation strategy of a static application slice and a network resource allocation strategy of a first reserved resource;
the local controller is used for decoding the received data signals;
and if the decoding result is correct, opening the network slice of the corresponding service to the local controller.
In one possible implementation, the optimized network resource allocation policy includes a network resource allocation policy of a second reserved resource, where the second reserved resource is used for dynamic emergency application, and the priority of the dynamic emergency application is higher than the priority of the dynamic application.
The following are system embodiments of the present invention, and for details not described in detail therein, reference may be made to the corresponding method and apparatus embodiments described above.
The embodiment of the invention provides a 5G power multi-service slice resource distribution system, which only shows the parts relevant to the embodiment of the invention for convenience of explanation, and is described in detail as follows:
A5G power multi-service slicing resource distribution system comprises a central controller, a slicing network and a local controller.
The central controller is used for executing the 5G power multi-service slicing resource allocation method, and uniformly managing and allocating the resources of the communication network of the power grid.
The local controller is used for extracting resource use information from real-time data and feedback information of the slicing network, and the slicing network comprises network slices corresponding to all services.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the templates, elements, and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer-readable storage medium. Based on such understanding, the present invention may implement all or part of the flow of the method of the foregoing embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, where the computer program, when executed by a processor, may implement the steps of each of the foregoing embodiments of the 5G power multi-service slice resource allocation method. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium can include any entity or device capable of carrying computer program code, recording medium, USB flash disk, removable hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier wave signals, telecommunication signals, software distribution media, and so forth.
The foregoing embodiments are merely for illustrating the technical solution of the present invention, but not for limiting the same, and although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that the technical solution described in the foregoing embodiments may be modified or substituted for some of the technical features thereof, and that these modifications or substitutions should not depart from the spirit and scope of the technical solution of the embodiments of the present invention and should be included in the protection scope of the present invention.
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