5G network green energy routing optimization method and system, and storage medium

Abstract

The invention relates to the technical field of 5G network communication, and discloses a 5G network green energy routing optimization method and system and a storage medium, and the method comprises the steps: generating an initial routing strategy through combining first energy state data of each green energy node, and feeding back the initial routing strategy to a user side; data transmission can be guided to preferentially select a green energy node path with sufficient and efficient energy, so that the utilization rate of green energy in the whole 5G network data transmission is improved. Furthermore, the task transmission data is intelligently scheduled in combination with the green energy path preference data sent by the user side, so that green energy nodes in the 5G network can be more effectively utilized, the dependence on traditional energy in a peak period is reduced, and the sense of mastering and participation of the user on the use of the green energy is enhanced. Finally, the task scheduling result and the environmental protection benefit data are sent to the user side, the participation sense and long-term power of the user can be enhanced, and the willingness of continuously using the green energy is further stimulated.

Description

Technical Field

[0001] The present invention relates to the field of 5G network communication technology, and in particular to a 5G network green energy routing optimization method, system and storage medium. Background Art

[0002] At present, with the increasing global attention to environmental protection and sustainable development, the use of green energy is rapidly promoted in various fields. However, the current traffic routing method in communication networks is still mainly based on the requirements of network performance and user service quality, and the use of green energy has not been fully utilized. 5G networks have introduced considerations for green energy in their design, especially through traffic scheduling and optimized routing, reducing dependence on traditional non-renewable energy and improving the efficiency of green energy use. However, how to further motivate users to actively participate in the use of green energy and give timely feedback is an important part of achieving sustainable development goals.

[0003] Existing technologies usually only focus on optimizing network performance and improving service quality, but rarely consider the sustainability of energy use and the subjective initiative of users in energy selection. In the 5G era, the network can not only provide users with extremely high transmission speeds and ultra-low latency, but also have smarter and more dynamic energy management capabilities. Summary of the invention

[0004] In view of this, the present invention provides a 5G network green energy routing optimization method, system and storage medium to solve the problem that the prior art usually only focuses on network performance optimization and service quality improvement, and pays less attention to the sustainability of energy use and the subjective initiative of users in energy selection.

[0005] In a first aspect, the present invention provides a 5G network green energy routing optimization method, which is used in a 5G core network system, the 5G core network system is connected to a user terminal, the 5G core network system includes a session management function module, a network storage function module and a policy control function module, and the session management function module is respectively connected to the network storage function module and the policy control function module; the method includes:

[0006] When the session management function module receives the green energy usage instruction sent by the user end, the first energy status data of each green energy node in the 5G network is obtained through the network storage function module; based on the first energy status data of each green energy node, the initial routing strategy is generated by the policy control function module, and the initial routing strategy is sent to the user end; when the network storage function module receives the green energy path preference data and task transmission data sent by the user end, based on the green energy path preference data, the task transmission data is intelligently scheduled by the network storage function module and the policy control function module to obtain the task scheduling results and environmental protection benefit data, and the green energy path preference data is determined according to the initial routing strategy; the task scheduling results and environmental protection benefit data are sent to the user end.

[0007] The 5G network green energy routing optimization method provided by the present invention obtains the first energy status data of each green energy node in the 5G network through the network storage function module, and can understand the supply of green energy in real time. Further, the initial routing strategy is generated in combination with the first energy status data of each green energy node and fed back to the user end, which can guide the data transmission to give priority to the green energy node path with sufficient energy and high efficiency, thereby improving the utilization rate of green energy in the entire 5G network data transmission and optimizing the network energy structure. Further, the task transmission data is intelligently scheduled in combination with the green energy path preference data sent by the user end, which can more effectively utilize the green energy nodes in the 5G network and reduce the dependence on traditional energy during peak hours. At the same time, it meets the personalized needs of users for the green energy use path, so that users can participate in the application process of green energy in the network according to their own wishes, and enhance the user's sense of control and participation in the use of green energy. Finally, the task scheduling results and environmental protection benefit data are sent to the user end, so that the user can timely understand the completion of its data transmission task based on the green energy path and the environmental protection benefits generated, enhance the user's sense of participation and long-term motivation, and further stimulate its willingness to continue to use green energy. Therefore, by implementing the present invention, through user incentives and feedback mechanisms, combined with intelligent scheduling and node priority management, users can not only obtain actual incentives, but also enhance their awareness and pride through environmental feedback and achievement display, which greatly improves the utilization rate of green energy and promotes green energy optimization in 5G networks.

[0008] In an optional implementation, based on the first energy state data of each green energy node, an initial routing strategy is generated using a strategy control function module, and the initial routing strategy is sent to a user end, including:

[0009] Based on the first energy status data of each green energy node, each green energy path in the 5G network is evaluated using the policy control function module to obtain multiple evaluation results; an initial routing strategy is generated based on the multiple evaluation results; and the initial routing strategy is sent to the user end.

[0010] The 5G network green energy routing optimization method provided by the present invention uses the first energy status data of each green energy node to evaluate each green energy path in the 5G network, which can comprehensively consider the actual energy status of the green energy nodes involved in each path, and realize a comprehensive and accurate evaluation of the green energy path. Further, by combining multiple evaluation results to generate an initial routing strategy, a personalized routing strategy that meets the current network energy layout and user needs can be formulated according to the actual conditions of different paths, so that the routing selection is more in line with the actual supply of green energy and network transmission requirements, and the pertinence and effectiveness of the routing strategy are improved. Finally, by sending the initial routing strategy to the user end, it can effectively guide users to give priority to those green energy paths that have more advantages in energy utilization, promote the widespread application of green energy in 5G networks, and enhance the enthusiasm and initiative of users to participate in green energy network transmission.

[0011] In an optional implementation, when the network storage function module receives the green energy path preference data and the task transmission data sent by the user end, based on the green energy path preference data, the network storage function module and the policy control function module are used to intelligently schedule the task transmission data to obtain the task scheduling results and environmental benefit data, including:

[0012] When the network storage function module receives the green energy path preference data and task transmission data sent by the user end, it obtains the second energy status data of each green energy node in the 5G network; based on the green energy path preference data and the second energy status data of each green energy node, the network storage function module and the policy control function module are used to intelligently schedule the task transmission data to obtain the task scheduling results and environmental protection benefit data.

[0013] The 5G network green energy routing optimization method provided by the present invention combines the green energy path preference data and the second energy state data of each green energy node to intelligently schedule the task transmission data, comprehensively considers the user demand and the actual energy supply state, and can more accurately assign tasks to suitable green energy paths, achieve the optimal match between task transmission and green energy utilization, and improve the accuracy and effectiveness of task scheduling. Finally, the task scheduling results and environmental protection benefit data are fed back to the user end, so that the user can timely understand the specific scheduling of the task sent by the user based on the selected green energy path and the environmental protection benefits generated thereby, so that the user has a clear understanding of the effect of his network behavior on green energy utilization, and further enhances the user's enthusiasm for continuing to select green energy paths for task transmission. Therefore, by implementing the present invention, by reasonably utilizing the green energy path preference data and the actual energy state data of each green energy node, the task transmission is more dependent on the green energy path to complete, thereby effectively improving the utilization rate of green energy, highlighting the environmental protection benefits, and helping to promote the 5G network to develop in a more green and environmentally friendly direction during operation, and reduce dependence on traditional energy.

[0014] In an optional implementation, based on the green energy path preference data and the second energy state data of each green energy node, the task transmission data is intelligently scheduled using the network storage function module and the policy control function module to obtain the task scheduling results and environmental benefit data, including:

[0015] The network storage function module sends the green energy path preference data and the second energy status data of each green energy node to the policy control function module; based on the green energy path preference data and the second energy status data of each green energy node, the policy control function module is used to optimize the initial routing strategy to obtain the target routing strategy, and the target routing strategy is sent to the network storage function module; based on the target routing strategy, the network storage function module is used to intelligently schedule the task transmission data to obtain the task scheduling result; based on the target routing strategy and the task scheduling result, the network storage function module is used to determine the environmental protection benefit data.

[0016] The 5G network green energy routing optimization method provided by the present invention can generate a target routing strategy that is more in line with the actual situation and more targeted by considering the user's personalized preferences and the current actual energy status of the green energy nodes, thereby greatly improving the accuracy and adaptability of the routing strategy.

[0017] In an optional implementation, the method further includes: determining reward data based on the green energy path preference data and sending the reward data to the user end.

[0018] The 5G network green energy routing optimization method provided by the present invention determines reward data through green energy path preference data and sends the reward data to the user end, which can enhance the user's environmental awareness and participation in environmental protection.

[0019] In a second aspect, the present invention provides a 5G network green energy routing optimization method, which is used for a user terminal, and the user terminal is connected to a 5G core network system; the method comprises:

[0020] Send green energy usage instructions to the 5G core network system, so that the 5G core network system generates an initial routing strategy based on the green energy usage instructions; receive the initial routing strategy sent by the 5G core network system; determine the green energy path preference data based on the initial routing strategy; obtain task transmission data and send the task transmission data and the green energy path preference data to the 5G core network system, so that the 5G core network system performs intelligent scheduling of the task transmission data based on the green energy path preference data and obtains the task scheduling results and environmental protection benefit data; receive the task scheduling results and environmental protection benefit data sent by the 5G core network system.

[0021] The 5G network green energy routing optimization method provided by the present invention combines user incentives and feedback mechanisms with intelligent scheduling and node priority management. Users can not only obtain actual incentives, but also enhance their awareness and sense of pride through environmental protection feedback and achievement demonstrations, thereby greatly improving the utilization rate of green energy and promoting green energy optimization in 5G networks.

[0022] In an optional implementation, the method further includes: receiving reward data sent by the 5G core network system.

[0023] In a third aspect, the present invention provides a 5G network green energy routing optimization system, the system comprising: a 5G core network system and a user terminal, the 5G core network system comprising a session management function module, a network storage function module and a policy control function module, the session management function module is respectively connected to the network storage function module and the policy control function module;

[0024] The 5G core network system is used to execute the 5G network green energy routing optimization method of the first aspect or any corresponding implementation manner thereof; the user end is used to execute the 5G network green energy routing optimization method of the second aspect or any corresponding implementation manner thereof.

[0025] The 5G network green energy routing optimization system provided by the present invention greatly improves the utilization rate of green energy and promotes green energy optimization in the 5G network by executing the 5G network green energy routing optimization method in the 5G core network system and the user terminal respectively.

[0026] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the 5G network green energy routing optimization method of the above-mentioned first aspect or any corresponding embodiment thereof, or to execute the 5G network green energy routing optimization method of the above-mentioned second aspect or any corresponding embodiment thereof.

[0027] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions, wherein the computer instructions are used to enable a computer to execute the 5G network green energy routing optimization method of the above-mentioned first aspect or any corresponding embodiment thereof, or to execute the 5G network green energy routing optimization method of the above-mentioned second aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 is a structural block diagram of a 5G network green energy routing optimization system according to an embodiment of the present invention;

[0030] Figure 2 is a flow chart of a 5G network green energy routing optimization method according to an embodiment of the present invention;

[0031] Figure 3 is a flow chart of another 5G network green energy routing optimization method according to an embodiment of the present invention;

[0032] Figure 4 is a flow chart of another 5G network green energy routing optimization method according to an embodiment of the present invention;

[0033] Figure 5 is a schematic diagram of a flow chart of an incentive mechanism for users to select a green energy path according to an embodiment of the present invention;

[0034] Figure 6 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0036] The prior art has the following disadvantages:

[0037] 1. Lack of user incentive mechanism: In the existing 5G network architecture and traffic scheduling mechanism, users do not have the opportunity to directly participate in the selection of green energy paths, and there is a lack of incentive mechanisms to encourage users to make choices based on energy types. This leads to an unclear connection between user behavior and energy consumption, and it is difficult for users to actively participate in the use of green energy.

[0038] 2. Insufficient user feedback on environmental protection behavior: In existing technologies, users lack intuitive feedback on the impact of their network path selection on green energy use, and cannot understand whether their choice reduces carbon emissions. This information opacity weakens users' environmental awareness and fails to encourage them to continue to choose green energy paths in subsequent use.

[0039] 3. Limited user choice: Existing technologies usually do not allow users to make independent choices based on the availability of green energy when using non-real-time services. Users' requirements for network services are more focused on performance and latency, ignoring environmental protection and energy consumption considerations. This limits users' opportunities to balance service quality and environmental protection behavior.

[0040] 4. Insufficient user participation: The existing network architecture and service design rarely involve users' choice of energy types. Users' behavior is limited to consuming network resources, and they have no motivation to actively choose green energy paths, and they are not even aware of the impact of their behavior on energy consumption. The lack of an incentive mechanism also makes users unwilling to sacrifice a certain service delay or comfort for energy conservation and environmental protection.

[0041] According to an embodiment of the present invention, an embodiment of a 5G network green energy routing optimization method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0042] In this embodiment, a 5G network green energy routing optimization method is provided, which can be used for example Figure 1The 5G core network system 11 shown, wherein the 5G core network system 11 is connected to the user terminal 12, and the 5G core network system 11 includes a session management function module 111, a network storage function module 112 and a policy control function module 113. Specifically, the session management function module 111 is connected to the network storage function module 112 and the policy control function module 113 respectively.

[0043] Figure 2 is a flow chart of a 5G network green energy routing optimization method according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0044] Step S201, when the session management function module receives the green energy usage instruction sent by the user terminal, the first energy status data of each green energy node in the 5G network is obtained through the network storage function module.

[0045] Among them, the session management function (SMF) is responsible for the establishment, modification and release of sessions, including tunnel maintenance between UPF and AN nodes; the network storage function module (NFRepository Function, NRF) represents a function module that provides registration and discovery functions, which enables network functions (NF) to discover each other and communicate through API interfaces.

[0046] Furthermore, the green energy usage instruction indicates that the user corresponding to the user end has chosen to use the green energy path when using non-real-time services; 5G network refers to the 5G core network (Core Network), which is the brain of the mobile communication network, responsible for managing and controlling the entire network, mainly including switches / routers and other network elements with certain functional entities.

[0047] Furthermore, the first energy status data is used to characterize the green energy power supply status of each green energy node, especially the power supply proportion of renewable energy such as solar energy and wind energy.

[0048] Specifically, when the user uses a non-real-time service and selects to use a green energy path, the user enters a green energy use instruction in the user terminal 12. Then, the user terminal 12 sends the received green energy use instruction to the session management function module 111.

[0049] Furthermore, after receiving the green energy usage instruction in the session management function module 111, an acquisition instruction is sent to the network storage function module 112, so that the network storage function module 112, under the control of the acquisition instruction, obtains the green energy power supply status of each green energy node in the 5G network, especially the power supply proportion of renewable energy such as solar energy and wind energy.

[0050] Step S202: Based on the first energy state data of each green energy node, an initial routing strategy is generated by using a strategy control function module, and the initial routing strategy is sent to the user end.

[0051] Among them, the Policy Control Function (PCF) module is responsible for the 5G core network control plane function of policy control, which mainly manages the QoS of each service data flow in the 5G core network.

[0052] Specifically, the network storage function module 112 sends the acquired first energy status data of each green energy node to the session management function module 111 .

[0053] Further, the session management function module 111 sends the first energy state data of each green energy node to the policy control function module 113 .

[0054] Furthermore, the policy control function module 113 may generate a corresponding initial routing policy according to the received first energy state data of each green energy node. Further, the initial routing policy may give priority to nodes with a higher proportion of green energy for data transmission, thereby reducing the consumption of traditional energy.

[0055] Step S203, when the network storage function module receives the green energy path preference data and task transmission data sent by the user end, based on the green energy path preference data, the network storage function module and the policy control function module are used to intelligently schedule the task transmission data to obtain the task scheduling results and environmental protection benefit data.

[0056] Among them, the green energy path preference data can be determined according to the initial routing strategy, and may include the user's priority for the green energy path and the tolerable delay period; the task transmission data represents the non-real-time task data selected by the user; the environmental benefit data represents the environmental effect of the green energy path selected by the user, such as the proportion of network functions using green energy on the green energy path, and how much traditional energy use has been reduced compared with the past.

[0057] Specifically, the user terminal 12 receives the initial routing policy fed back by the policy control function module 113 and displays the initial routing policy to the user, so that the user can set the priority and tolerable delay period for the green energy path according to the initial routing policy.

[0058] Furthermore, the user terminal 12 sends the received green energy path preference data and task transmission data input by the user to the network storage function module 112 .

[0059] Furthermore, the network storage function module 112 receives the green energy path preference data and task transmission data sent by the user terminal 12, and can, based on the green energy path preference data, combine with the policy control function module 113 to intelligently schedule the transmission of the task transmission data in the 5G network, and obtain the corresponding task scheduling results and corresponding environmental benefit data.

[0060] Step S204, sending the task scheduling results and environmental benefit data to the user end.

[0061] Specifically, the 5G core network system 11 can feed back the obtained task scheduling results and environmental benefit data to the user end 12.

[0062] The 5G network green energy routing optimization method provided in this embodiment obtains the first energy status data of each green energy node in the 5G network through the network storage function module, and can understand the supply of green energy in real time. Further, the initial routing strategy is generated in combination with the first energy status data of each green energy node and fed back to the user end, which can guide the data transmission to give priority to the green energy node path with sufficient energy and high efficiency, thereby improving the utilization rate of green energy in the entire 5G network data transmission and optimizing the network energy structure. Further, the task transmission data is intelligently scheduled in combination with the green energy path preference data sent by the user end, which can more effectively utilize the green energy nodes in the 5G network and reduce the dependence on traditional energy during peak hours. At the same time, it meets the user's personalized needs for the green energy use path, so that the user can participate in the application process of green energy in the network according to his own wishes, and enhance the user's sense of control and participation in the use of green energy. Finally, the task scheduling results and environmental protection benefit data are sent to the user end, so that the user can timely understand the completion of its data transmission task based on the green energy path and the environmental protection benefits generated, enhance the user's sense of participation and long-term motivation, and further stimulate its willingness to continue to use green energy. Therefore, by implementing the present invention, through user incentives and feedback mechanisms, combined with intelligent scheduling and node priority management, users can not only obtain actual incentives, but also enhance their awareness and pride through environmental feedback and achievement display, which greatly improves the utilization rate of green energy and promotes green energy optimization in 5G networks.

[0063] In this embodiment, a 5G network green energy routing optimization method is provided, which can be used for example Figure 1 The 5G core network system 11 is shown, wherein the 5G core network system 11 is connected to the user terminal 12. Figure 3 is a flow chart of a 5G network green energy routing optimization method according to an embodiment of the present invention. Figure 3 As shown, the process includes the following steps:

[0064] Step S301: When the session management function module receives the green energy usage instruction sent by the user terminal, the network storage function module obtains the first energy status data of each green energy node in the 5G network. Figure 2 Step S201 of the illustrated embodiment will not be described in detail here.

[0065] Step S302: Based on the first energy state data of each green energy node, an initial routing strategy is generated by using a strategy control function module, and the initial routing strategy is sent to the user end.

[0066] Specifically, the above step S302 includes:

[0067] Step S3021, based on the first energy status data of each green energy node, use the policy control function module to evaluate each green energy path in the 5G network to obtain multiple evaluation results.

[0068] Specifically, when the policy control function module 113 receives the first energy status data of each green energy node sent by the network storage function module 112, it can combine the first energy status data of each green energy node to comprehensively evaluate each green energy path. Among them, the evaluation mainly considers the green energy proportion of the nodes involved in the path, and uses the green energy-related data of each node as an important basis for evaluating whether each path is a green energy path and the degree of greenness.

[0069] Furthermore, through comprehensive analysis of factors such as the green energy ratio of nodes involved in each path, the policy control function module 113 can obtain multiple evaluation results for each green energy path in the 5G network. These evaluation results can clearly show the advantages and disadvantages of each path in terms of green energy utilization, such as which paths have a higher proportion of green energy and are more in line with environmental protection and energy-saving requirements, and which paths have a relatively low degree of green energy utilization, thereby providing sufficient reference for the subsequent selection of the optimal routing strategy.

[0070] Step S3022: Generate an initial routing strategy based on multiple evaluation results.

[0071] Specifically, according to the obtained multiple evaluation results, the paths with higher proportion of green energy are preferentially selected to set corresponding routing strategies.

[0072] Step S3023: Send the initial routing policy to the user end.

[0073] Specifically, the policy control function module 113 sends the generated initial routing policy to the user terminal 12. Based on the initial routing policy, the network elements used by the user can be modified to transmit data in network elements with a higher proportion of green energy, thereby reducing dependence on non-green energy.

[0074] Step S303, when the network storage function module receives the green energy path preference data and task transmission data sent by the user end, based on the green energy path preference data, the network storage function module and the policy control function module are used to intelligently schedule the task transmission data to obtain the task scheduling results and environmental protection benefit data.

[0075] Specifically, the above step S303 includes:

[0076] Step S3031, when the network storage function module receives the green energy path preference data and task transmission data sent by the user terminal, it obtains the second energy status data of each green energy node in the 5G network.

[0077] Specifically, after receiving the initial routing policy fed back by the policy control function module 113, the user terminal 12 can present the initial routing policy to the user according to the initial routing policy, so that the user can set the priority and tolerable delay period for the green energy path according to the initial routing policy.

[0078] Furthermore, the user terminal 12 sends the received green energy path preference data and task transmission data input by the user to the network storage function module 112 .

[0079] Furthermore, after the network storage function module 112 receives the green energy path preference data and task transmission data sent by the user terminal 12, in order to meet the user's green energy path preference and the scheduling of the corresponding task transmission data, it is necessary to comprehensively consider the real-time green energy power supply conditions of each green energy node in the 5G network, etc. Therefore, the second energy status data of each green energy node in the 5G network continues to be obtained through the network storage function module 112.

[0080] Step S3032, based on the green energy path preference data and the second energy state data of each green energy node, the task transmission data is intelligently scheduled using the network storage function module and the policy control function module to obtain the task scheduling results and environmental benefit data.

[0081] Specifically, based on comprehensive consideration of the green energy path preference data and the second energy status data of each green energy node, the policy control function module 113 and the network storage function module 112 can be combined to intelligently schedule the transmission of the task transmission data in the 5G network, and obtain the corresponding task scheduling results and corresponding environmental benefit data.

[0082] In some optional implementations, the above step S3032 includes:

[0083] Step a1: the network storage function module sends the green energy path preference data and the second energy state data of each green energy node to the policy control function module.

[0084] Step a2, based on the green energy path preference data and the second energy state data of each green energy node, the initial routing strategy is optimized using the strategy control function module to obtain the target routing strategy, and the target routing strategy is sent to the network storage function module.

[0085] Step a3: Based on the target routing strategy, the network storage function module is used to intelligently schedule the task transmission data to obtain the task scheduling result.

[0086] Step a4, based on the target routing strategy and the task scheduling result, the environmental protection benefit data is determined using the network storage function module.

[0087] First, the network storage function module 112 sends the received green energy path preference data and the second energy state data of each green energy node to the policy control function module 113 .

[0088] Furthermore, the strategy control function module 113 can adjust the initial routing strategy according to the green energy path preference data and the second energy state data of each green energy node and give priority to paths with a higher green energy ratio to generate an optimal routing strategy, namely, a target routing strategy.

[0089] Furthermore, the policy control function module 113 feeds back the target routing policy to the user terminal 12 .

[0090] Further, the client 12 sends the received target routing policy to the network storage function module 112 .

[0091] Secondly, based on the target routing strategy, the network storage function module 112 can intelligently schedule task transmission data according to the availability of each green energy node, give priority to transmission during periods of sufficient green energy and obtain corresponding task scheduling results. Through reasonable task scheduling, the 5G core network system 11 can more effectively utilize the green energy nodes in the 5G network and reduce dependence on traditional energy during peak hours. Furthermore, it can maximize the use of green energy and achieve green energy-saving effects while ensuring that the user experience is not affected.

[0092] Finally, after the task scheduling is completed, the network storage function module 112 can determine the environmental benefits of the corresponding green path in combination with the target routing strategy and the task scheduling result, such as how much carbon dioxide emissions are reduced.

[0093] Step S304: sending the task scheduling results and environmental benefit data to the user end.

[0094] Specifically, the 5G core network system 11 can send the obtained task scheduling results and environmental benefit data to the user terminal 12.

[0095] Step S305 , determining reward data based on the green energy path preference data and sending the reward data to the user end.

[0096] Among them, the reward data may include reward data in the form of traffic discounts, point rewards, or carbon emission reduction certificates.

[0097] Specifically, after the task scheduling results are fed back to the user terminal 12, the 5G core network system 11 can also give additional rewards based on the user's green energy priority, that is, green energy path preference data, that is, send corresponding reward data to the user terminal 12, thereby enhancing the user's environmental awareness and participation in environmental protection.

[0098] The 5G network green energy routing optimization method provided in this embodiment uses the first energy status data of each green energy node to evaluate each green energy path in the 5G network, which can comprehensively consider the actual energy status of the green energy nodes involved in each path, and realize a comprehensive and accurate evaluation of the green energy path. Further, by combining multiple evaluation results to generate an initial routing strategy, a personalized routing strategy that meets the current network energy layout and user needs can be formulated according to the actual conditions of different paths, so that the routing selection is more in line with the actual supply of green energy and network transmission requirements, and the pertinence and effectiveness of the routing strategy are improved. Finally, by sending the initial routing strategy to the user end, it can effectively guide users to give priority to those green energy paths that have more advantages in energy utilization, promote the widespread application of green energy in 5G networks, and enhance the enthusiasm and initiative of users to participate in green energy network transmission.

[0099] In this embodiment, a 5G network green energy routing optimization method is provided, which can be used for example Figure 1 The user terminal 12 shown is connected to the 5G core network system 11. Figure 4 is a flow chart of a 5G network green energy routing optimization method according to an embodiment of the present invention. Figure 4 As shown, the process includes the following steps:

[0100] Step S401, sending a green energy usage instruction to the 5G core network system, so that the 5G core network system generates an initial routing strategy based on the green energy usage instruction.

[0101] Specifically, the user terminal 12 sends a green energy usage instruction to the 5G core network system 11.

[0102] Further, the 5G core network system 11 can generate a corresponding initial routing strategy based on the received green energy usage instruction. The specific generation process refers to the description of step S302 above and will not be repeated here.

[0103] Step S402, receiving the initial routing strategy sent by the 5G core network system.

[0104] Specifically, the 5G core network system 11 feeds back the generated 5G core network system 11 to the user end 12.

[0105] Step S403: determining green energy path preference data based on the initial routing strategy.

[0106] Specifically, after the user terminal 12 receives the initial routing strategy fed back by the policy control function module 113, the initial routing strategy can be displayed to the user according to the initial routing strategy, so that the user can set the priority and tolerable delay period of the green energy path according to the initial routing strategy, thereby forming corresponding green energy path preference data.

[0107] Step S404, obtain task transmission data and send the task transmission data and green energy path preference data to the 5G core network system, so that the 5G core network system intelligently schedules the task transmission data based on the green energy path preference data and obtains task scheduling results and environmental benefit data.

[0108] Specifically, the user terminal 12 receives the task transmission data input by the user, and sends the task transmission data and the green energy path preference data to the 5G core network system 11.

[0109] Further, the 5G core network system 11 can intelligently schedule the task transmission data according to the received 5G core network system 11 and obtain the task scheduling results and environmental benefit data. The specific process can refer to the description of the above step S303 and will not be repeated here.

[0110] Step S405, receiving the task scheduling results and environmental benefit data sent by the 5G core network system.

[0111] Specifically, the 5G core network system 11 feeds back the obtained task scheduling results and environmental protection benefit data to the user end 12.

[0112] Step S406, receiving reward data sent by the 5G core network system.

[0113] Specifically, the determination of the reward data in the 5G core network system 11 refers to the description of step S305 above, which will not be repeated here.

[0114] The 5G network green energy routing optimization method provided in this embodiment, through the user incentive and feedback mechanism, combined with intelligent scheduling and node priority management, can not only enable users to obtain actual incentives, but also enhance their awareness and sense of pride through environmental protection feedback and achievement display, thereby greatly improving the utilization rate of green energy and promoting green energy optimization in 5G networks.

[0115] In this embodiment, a 5G network green energy routing optimization system is provided. Figure 1 As shown, the 5G network green energy routing optimization system includes: a 5G core network system 11 and a user terminal 12.

[0116] Specifically, the 5G core network system 11 includes a session management functional module 111, a network storage functional module 112 and a policy control functional module 113.

[0117] The session management function module 111 is connected to the network storage function module 112 and the policy control function module 113 respectively.

[0118] Furthermore, the specific functional description of the 5G core network system 11 and the user terminal 12 refers to the 5G network green energy routing optimization method provided in the above-mentioned embodiment of the present invention, and will not be repeated here.

[0119] The 5G network green energy routing optimization system provided in this embodiment greatly improves the utilization rate of green energy and promotes green energy optimization in the 5G network by executing the 5G network green energy routing optimization method in the 5G core network system and the user terminal respectively.

[0120] In one example, a method for optimizing green energy routing in a 5G network based on user incentives and feedback is provided. By introducing a user incentive and feedback mechanism, user behavior is fully utilized to optimize the use of green energy in the 5G network. The incentive mechanism increases the user's enthusiasm for choosing green energy paths, and the feedback mechanism enhances the user's sense of participation and long-term motivation through a transparent display of environmental protection results. The green energy priority scheduling mechanism for non-real-time tasks maximizes the use of green energy through a flexible scheduling algorithm without affecting the user experience. This example can not only reduce dependence on traditional energy, but also promote the popularization and application of green energy through user behavior. Specifically including:

[0121] 1. Incentive mechanism for users to choose green energy path

[0122] This example proposes an incentive mechanism. When using non-real-time services, users can choose to use green energy paths. SMF obtains the energy status and green energy ratio of each node through NRF based on the user's choice and notifies PCF to adjust the user strategy to generate the optimal routing strategy. The routing strategy will give priority to nodes with a higher proportion of green energy for transmission, thereby reducing the consumption of traditional energy. To achieve this goal, NRF will regularly or in real time obtain the green energy supply status of each node in the core network, especially the power supply ratio of renewable energy such as solar energy and wind energy. Then PCF will evaluate the paths in the network based on this information, give priority to paths with a higher proportion of green energy to set routing strategies, thereby modifying the network elements used by users, and transmitting data in network elements with a higher proportion of green energy, so as to reduce dependence on non-green energy. The specific process is as follows: Figure 5 shown.

[0123] The system records the user's selection behavior and provides rewards such as traffic discounts, point rewards, or carbon emission reduction certificates, thereby enhancing the user's environmental awareness and participation in environmental protection.

[0124] 2. Feedback Mechanism of Environmental Protection Behavior

[0125] The feedback mechanism of environmental protection behavior can show users the environmental protection effect of the green energy path they choose, such as the proportion of network functions using green energy on the green energy path, how much traditional energy is reduced compared with the past, etc. Users can not only see the reduction in carbon emissions caused by their choices, but also understand their cumulative use of green energy through graphics or data. This feedback mechanism can further motivate users to continue to choose green energy paths.

[0126] The specific process is:

[0127] 1. After the user completes the task, the system shows the user the environmental benefits of choosing the green path through the application interface or SMS notification, such as how much carbon dioxide emissions have been reduced.

[0128] 2. The system will cumulatively record the user's environmental protection behavior and regularly show the user their total green energy usage and contribution to the environment.

[0129] 3. Green Energy Priority Scheduling for Non-real-time Tasks

[0130] For non-real-time tasks, this example proposes a green energy priority scheduling mechanism that allows users to set renewable energy preferences and tolerated service delay time periods. The system will flexibly adjust the transmission time and path of the task based on the user's choice and the real-time power supply of the green energy node. This solution ensures data transmission during the period when green energy is sufficient, reducing the use of traditional energy.

[0131] Advantages of green energy priority dispatch:

[0132] 1. Flexibility: Users can customize the delay time period, and the system automatically schedules tasks when there is sufficient green energy supply.

[0133] 2. Resource optimization: Through reasonable task scheduling, the system can more effectively utilize green energy nodes in the 5G network and reduce dependence on traditional energy during peak hours.

[0134] 3. Balance user experience and environmental protection goals: Maximize the use of green energy to achieve green energy-saving effects without affecting user experience.

[0135] The specific process is:

[0136] 1. When initiating a non-real-time task, the user sets the priority of the green energy path and the tolerable delay period.

[0137] 2. The system intelligently schedules tasks based on the availability of green energy nodes, giving priority to transmission during periods of sufficient green energy. The intelligent scheduling process refers to the first point above.

[0138] 3. After the task is completed, the system will feedback the results to the user and give additional rewards based on the user's green energy priority.

[0139] This example provides a method for optimizing green energy routing in 5G networks based on user incentives and feedback. Through user incentives and feedback mechanisms, combined with intelligent scheduling and node priority management, the maximum utilization of green energy in 5G networks is achieved. Users can not only obtain actual rewards by choosing green energy paths, but also understand their environmental contributions through system feedback, thereby further stimulating their willingness to continue to use green energy. This innovative mechanism promotes the widespread application of green energy while optimizing the energy consumption of 5G networks. Therefore, through this example, through the user incentive and feedback mechanism, combined with intelligent scheduling and node priority management, users can not only obtain actual incentives, but also enhance awareness and pride through environmental feedback and achievement display. These innovative measures have greatly improved the utilization rate of green energy and promoted green energy optimization in 5G networks.

[0140] The embodiment of the present invention also provides a computer device having the above Figures 2 to 4 The green energy routing optimization method for 5G networks is shown.

[0141] See also Figure 6 , Figure 6 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 6As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 6 A processor 10 is taken as an example.

[0142] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0143] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0144] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0145] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0146] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0147] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0148] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0149] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A 5G network green energy routing optimization method, characterized in that: Used in a 5G core network system, the 5G core network system is connected to a user terminal, the 5G core network system includes a session management function module, a network storage function module and a policy control function module, the session management function module is respectively connected to the network storage function module and the policy control function module; the method includes: When the session management function module receives the green energy usage instruction sent by the user terminal, the first energy status data of each green energy node in the 5G network is obtained through the network storage function module; Based on the first energy state data of each green energy node, using the policy control function module to generate an initial routing policy, and sending the initial routing policy to the user end; When the network storage function module receives the green energy path preference data and the task transmission data sent by the user end, based on the green energy path preference data, the network storage function module and the policy control function module are used to intelligently schedule the task transmission data to obtain the task scheduling result and environmental benefit data, and the green energy path preference data is determined according to the initial routing policy; The task scheduling result and the environmental benefit data are sent to the user terminal.

2. The method according to claim 1, characterized in that Based on the first energy state data of each green energy node, the strategy control function module is used to generate an initial routing strategy, and the initial routing strategy is sent to the user end, including: Based on the first energy state data of each green energy node, the policy control function module is used to evaluate each green energy path in the 5G network to obtain multiple evaluation results; generating the initial routing strategy based on the multiple evaluation results; The initial routing strategy is sent to the user terminal.

3. The method according to claim 1, characterized in that When the network storage function module receives the green energy path preference data and the task transmission data sent by the user end, based on the green energy path preference data, the network storage function module and the policy control function module are used to intelligently schedule the task transmission data to obtain task scheduling results and environmental benefit data, including: When the network storage function module receives the green energy path preference data and the task transmission data sent by the user terminal, the second energy state data of each green energy node in the 5G network is obtained; Based on the green energy path preference data and the second energy status data of each green energy node, the network storage function module and the policy control function module are used to intelligently schedule the task transmission data to obtain the task scheduling result and the environmental benefit data.

4. The method according to claim 3, characterized in that Based on the green energy path preference data and the second energy state data of each green energy node, the task transmission data is intelligently scheduled using the network storage function module and the policy control function module to obtain the task scheduling result and the environmental benefit data, including: The network storage function module sends the green energy path preference data and the second energy state data of each green energy node to the policy control function module; Based on the green energy path preference data and the second energy state data of each green energy node, the initial routing strategy is optimized by using the strategy control function module to obtain a target routing strategy, and the target routing strategy is sent to the network storage function module; Based on the target routing strategy, the network storage function module is used to intelligently schedule the task transmission data to obtain a task scheduling result; Based on the target routing strategy and the task scheduling result, the environmental benefit data is determined using the network storage function module.

5. The method according to claim 1, characterized in that The method further comprises: Reward data is determined based on the green energy path preference data and the reward data is sent to the user terminal.

6. A 5G network green energy routing optimization method, characterized in that: Used for a user terminal, the user terminal is connected to a 5G core network system; the method comprises: Sending a green energy usage instruction to the 5G core network system, so that the 5G core network system generates an initial routing strategy based on the green energy usage instruction; Receiving the initial routing strategy sent by the 5G core network system; determining green energy path preference data based on the initial routing strategy; Acquire task transmission data and send the task transmission data and the green energy path preference data to the 5G core network system, so that the 5G core network system intelligently schedules the task transmission data based on the green energy path preference data and obtains task scheduling results and environmental benefit data; Receive the task scheduling results and environmental benefit data sent by the 5G core network system.

7. The method according to claim 6, characterized in that The method further comprises: Receive reward data sent by the 5G core network system.

8. A 5G network green energy routing optimization system, characterized in that: The system comprises: a 5G core network system and a user terminal, wherein the 5G core network system comprises a session management function module, a network storage function module and a policy control function module, wherein the session management function module is connected to the network storage function module and the policy control function module respectively; The 5G core network system is used to execute the 5G network green energy routing optimization method according to any one of claims 1 to 5; The user terminal is used to execute the 5G network green energy routing optimization method described in claim 6 or 7.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the 5G network green energy routing optimization method described in any one of claims 1 to 7.

10. A computer program product, characterized in that It includes computer instructions, which are used to enable a computer to execute the 5G network green energy routing optimization method described in any one of claims 1 to 7.

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