Service optimization communication system based on 5G LAN static multicast communication

Abstract

The invention discloses a service optimization communication system based on 5G LAN static multicast communication, relates to the technical field of communication optimization, and solves the technical problems that network resources are difficult to accurately allocate for various services, a means for effectively optimizing a transmission path is lacked, and normal development of related services and user experience are influenced. According to the method, the real-time priority index of each communication service is calculated by performing quantitative analysis on the service delay demand, the packet loss rate and the service continuity, and the corresponding resources are allocated to the services according to the real-time priority index, so that the key services and the services with high real-time requirements can be ensured to preferentially obtain enough resources, the stability and the reliability of service operation are improved, and the service quality is improved. Meanwhile, different resource requirements of the service in the peak period and the conventional period are considered, differentiated resource allocation is carried out in different periods, the resource utilization efficiency is further improved, and resource waste is avoided.

Description

Technical Field

[0001] The present invention relates to the field of communication optimization technology, and specifically to a service optimization communication system based on 5G LAN static multicast communication. Background Art

[0002] With the widespread application of 5G technology, 5G LAN static multicast communication has been increasingly used in many fields such as industrial automation, live video broadcasting, and financial transactions.

[0003] However, different communication services have different requirements for network performance, such as latency, packet loss rate, and business continuity. In traditional 5G LAN static multicast communication systems, it is difficult to accurately allocate network resources to various services, and there is also a lack of means to effectively optimize transmission paths. As a result, some services cannot obtain good service quality, affecting the normal operation of related services and user experience. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a service optimization communication system based on 5G LAN static multicast communication, which solves the problem of difficulty in accurately allocating network resources to various services and lack of means to effectively optimize the transmission path, which affects the normal development of related services and user experience.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a service optimization communication system based on 5G LAN static multicast communication, comprising: The communication service analysis module is used to analyze the real-time priority of all communication services based on the service demand information transmitted by the communication basic information collection module. By quantifying the delay requirements, packet loss rate and service continuity of the communication services, corresponding quantitative assignments are obtained. The real-time priority index of the communication services is obtained through a weighted algorithm. At the same time, priority ranking information is generated from the largest to the smallest and transmitted; The resource allocation optimization module is used to allocate resources for real-time communication services based on the obtained priority ranking information, calculate the required resource volume based on the real-time priority indicators corresponding to the real-time communication services, determine the peak hours and regular hours based on historical data, allocate different required resource volumes at the same time, generate resource allocation optimization information, and transmit it to the transmission optimization analysis module; The transmission optimization analysis module is used to perform transmission optimization processing on the obtained resource allocation optimization information. It separates the service traffic of each node according to the real-time service traffic of the real-time communication service, filters out the excess nodes that exceed the threshold, and generates a transmission path based on the network topology diagram. It calculates the comprehensive index of the transmission path based on the delay, packet loss rate and broadband utilization rate, and selects the transmission path with the largest comprehensive index to generate transmission optimization information, which is then transmitted to the optimization information output module.

[0006] As a further solution of the present invention, it also includes a communication basic information acquisition module for acquiring all communication services and corresponding business demand information and transmitting it to the communication service analysis module, wherein the business demand information includes delay requirements, packet loss rate and business continuity.

[0007] As a further solution of the present invention, the communication service analysis module quantifies the delay requirement, packet loss rate and service continuity of the communication service, and obtains the corresponding quantitative values in the following specific manner: Get all the communication services and label them as i, where i=1, 2, ..., j, where j represents the number of communication services; The delay requirements of communication services are quantified and the delay requirements are classified into strict tolerance, medium tolerance, general tolerance and loose tolerance, and the values are assigned as 4, 3, 2 and 1 respectively; The packet loss rate of communication services is quantified and the packet loss rate classification levels are determined to obtain extremely low packet loss rate, low packet loss rate, medium packet loss rate and high packet loss rate, and the values are assigned to them as 4, 3, 2 and 1 respectively; The communication business continuity is quantified to determine the business continuity classification levels, which include extremely high continuity requirements, high continuity requirements, medium continuity requirements and low continuity requirements, and are assigned values of 4, 3, 2 and 1 respectively.

[0008] As a further solution of the present invention, the communication service analysis module generates the priority information in the following specific manner: According to the formula Calculate the real-time priority index Yi corresponding to the communication service i, where Ci is the delay requirement value, Bi is the packet loss rate value, and Hi is the service continuity value. and is the weight coefficient, and + =1, and sort them from large to small to generate priority information, and transmit it to the resource allocation optimization module.

[0009] As a further solution of the present invention, the specific manner in which the resource allocation optimization module generates resource allocation optimization information is as follows: Obtain all real-time communication services and label them as a, where a=1, 2, ..., b, where b represents the number of real-time communication services. Obtain the real-time priority index Ya corresponding to real-time communication service a. Calculate the corresponding required resource amount based on the real-time priority index Ya. Calculate the required resource amount La for real-time communication service a using the formula La=Ya×Lz, where Lz is the standard required resource amount. Obtain historical data of real-time communication service a, and obtain corresponding peak hours and regular hours, and allocate different demand resources for peak hours and regular hours, generate resource allocation optimization information, and transmit it to the optimization information output module.

[0010] As a further solution of the present invention, the transmission optimization analysis module selects excess nodes exceeding the threshold in the following manner: The real-time service traffic distribution node corresponding to the real-time communication service a is obtained, and the service traffic corresponding to the distribution node is obtained. At the same time, the distribution nodes whose service traffic exceeds the threshold are screened. The specific value of the threshold is set by the operator and recorded as excess nodes.

[0011] As a further solution of the present invention, the transmission optimization analysis module selects the transmission path with the largest comprehensive index to generate transmission optimization information in the following specific manner: Taking the excess nodes as the starting point, the corresponding network topology diagram is drawn and the transmission path is generated. The delay, packet loss rate and broadband utilization are quantified and weighted to obtain the comprehensive index of the transmission path. The transmission path corresponding to the maximum comprehensive index is selected as the standard to generate the standard transmission path. The transmission optimization information is further generated and transmitted to the optimization information output module.

[0012] As a further solution of the present invention, it also includes an optimization information output module for optimizing the communication service according to the resource allocation optimization information and the transmission optimization information.

[0013] The present invention provides a service optimization communication system based on 5G LAN static multicast communication. Compared with the existing technology, it has the following advantages: The present invention performs quantitative analysis on service delay requirements, packet loss rate, and service continuity, calculates the real-time priority index of each communication service, and allocates corresponding resources to the service accordingly. This ensures that key services and services with high real-time requirements are given priority to obtain sufficient resources, thereby improving the stability and reliability of service operations. At the same time, taking into account the different resource requirements of services during peak hours and regular hours, differentiated resource allocation is performed for different time periods, further improving resource utilization efficiency and avoiding resource waste.

[0014] Based on the analysis of resource allocation optimization information, the present invention screens out nodes with excessive business traffic, and uses these nodes as starting points to draw a network topology diagram and generate transmission paths. By quantifying and weighting the delay, packet loss rate and bandwidth utilization of the transmission path, the transmission path with the best overall performance is selected. Compared with traditional transmission methods, this method reduces the delay and packet loss rate of data transmission, improves bandwidth utilization, and significantly enhances data transmission efficiency and service quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a block diagram of the system principle of the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only 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 ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0017] Example 1 See also Figure 1 This application provides a service optimization communication system based on 5G LAN static multicast communication, including a communication basic information acquisition module, a communication service analysis module, a resource allocation optimization module, a transmission optimization analysis module and an optimization information output module, and combines Figure 1 It can be known that the functional modules are electrically connected in a unidirectional manner.

[0018] The communication basic information acquisition module is used to obtain all communication services and corresponding business demand information and transmit it to the communication service analysis module, where the business demand information includes delay requirements, packet loss rate and business continuity.

[0019] The communication service analysis module is used to analyze the real-time priority of all services based on the acquired service demand information. The specific analysis method is as follows: Obtain all communication services and label them as i, where i = 1, 2, ..., j, where j represents the number of communication services. Then, quantify the delay requirement, packet loss rate, and service continuity to obtain the corresponding quantitative indicators. The specific method of quantifying the delay requirements of communication services is to obtain the delay tolerance corresponding to service i and classify them according to the delay tolerance, and the classification is as follows: Strict tolerance: For some critical businesses, such as real-time feedback control signal transmission in industrial control, the tolerance for delay is extremely low, usually required to be within 10 milliseconds to ensure system stability and security. If the delay exceeds this threshold, it may cause equipment failure or production accidents.

[0020] Medium tolerance: Real-time interactive services such as voice and video calls generally require a delay of less than 150 milliseconds to ensure smooth and natural communication. If the delay exceeds this range, users will notice a significant decline in call quality, with issues such as lag and echo occurring.

[0021] General Tolerance: Services such as live video streaming and online gaming can generally tolerate delays ranging from a few hundred milliseconds to around one second. For example, in live video streaming, a delay of around 500 milliseconds may cause viewers to experience slight lag, but it will not significantly impact the viewing experience. In online games, delays in character movements and scene updates are within one second, allowing players to generally continue gaming normally.

[0022] Relaxed Tolerance: For non-real-time services, such as file downloads and database queries, users have a higher tolerance for latency, ranging from a few seconds to tens of seconds or even longer. For example, when downloading a large file, users may be willing to wait several minutes or even more than ten minutes, as long as the download is eventually successful.

[0023] The delay requirement value is assigned based on the classified delay tolerance. Specifically, the value for strict tolerance is 4, the value for medium tolerance is 3, the value for general tolerance is 2, and the value for broadband tolerance is 1. The specific method of quantifying the packet loss rate of the communication service is to obtain the packet loss rate corresponding to the service i, and classify and assign values according to the packet loss rate. The specific classification and assignment method is as follows: Extremely low packet loss rate: Mission-critical services such as industrial automation control and aerospace communications require a packet loss rate of less than 0.1% or even lower. Even the smallest amount of data loss can have serious consequences. For example, the loss of control commands in an aircraft's autopilot system can lead to a flight accident.

[0024] Low packet loss rate: Services such as voice and video calls and real-time financial transactions generally require a packet loss rate below 1%. Excessive packet loss can cause voice interruption, blurred video, or transaction data errors, affecting the normal operation of the service and user experience.

[0025] Moderate packet loss rate: For services such as live video streaming and online gaming, a tolerable packet loss rate of around 3%-5% is acceptable. Within this range, error correction and compensation mechanisms, such as error concealment technology in video and data retransmission mechanisms in games, can minimize the impact of packet loss on services and ensure a basic viewing and gaming experience.

[0026] Higher packet loss rate: For non-real-time services such as file transfer and web browsing, a relatively high packet loss rate will not have a significant impact on the service. Generally, a packet loss rate of 5%-10% or even higher can be tolerated because these services can compensate for lost data through a retransmission mechanism. Users may only feel that the download speed is slower or the web page loading time is longer, but it will not affect the final result.

[0027] The corresponding value assignment is performed according to the obtained classified packet loss rate. The polar packet loss rate is assigned a value of 4, the low packet loss rate is assigned a value of 3, the medium packet loss rate is assigned a value of 2, and the high packet loss rate is assigned a value of 1.

[0028] At the same time, the specific method of quantifying the business continuity of the communication service i is to obtain the business continuity corresponding to the communication service i, and classify and assign values according to the business continuity. The specific classification and assignment methods are as follows: Extremely high continuity requirements: Services such as hospital life support systems and traffic signal control systems must operate 24 / 7. Any short interruption could endanger lives or cause traffic disruption. Therefore, they have extremely high real-time requirements and require highly reliable backup and fault-tolerance mechanisms to ensure continuous and stable service delivery under all circumstances.

[0029] High continuity requirements: Financial transaction systems and core business systems of large enterprises require a high degree of continuity during normal business hours. Even if a failure occurs, it needs to be restored in a very short time. Generally, the interruption time is required to be no more than a few minutes. This is because transaction interruptions may cause huge economic losses, and interruptions of the core business of the enterprise will affect the operation of the entire enterprise.

[0030] Medium continuity requirements: Services such as video conferencing and online education have certain continuity requirements, but these are slightly lower than those of the first two types of services. If a brief interruption occurs, it will be restored within a few minutes and generally will not have a significant impact on the business. For example, a brief disconnection may occur during a video conference, but the meeting can continue after reconnection; a brief interruption in an online education course will not affect students' overall learning of the course content.

[0031] Low continuity requirements: For some non-critical entertainment services, such as online music playback and short video browsing, users have a high tolerance for occasional interruptions. Even if there is an interruption of a few minutes, users may choose to replay or wait for recovery, which will not have a serious negative impact on the user experience.

[0032] The corresponding value assignment is performed according to the obtained classification continuity. The value assigned to the extremely high continuity requirement is 4, the value assigned to the high continuity requirement is 3, the value assigned to the medium continuity requirement is 2, and the value assigned to the low continuity requirement is 1. Then substitute the obtained delay requirement value, packet loss rate value and business continuity value into the formula Calculate the real-time priority index Yi corresponding to the communication service i, where Ci is the delay requirement value, Bi is the packet loss rate value, and Hi is the service continuity value. and is the weight coefficient, and + =1, and sort them from large to small to generate priority information, and transmit it to the resource allocation optimization module.

[0033] The resource allocation optimization module is used to allocate resources to communication services based on the obtained priority information. The specific allocation method is as follows: Obtain all real-time communication services and label them as a, where a = 1, 2, ..., b, where b represents the number of real-time communication services, and real-time communication services here represent services that are currently communicating. Obtain the real-time priority index Ya corresponding to real-time communication service a, and calculate the corresponding required resource amount based on the real-time priority index Ya. The required resource amount La of real-time communication service a is calculated according to the formula La = Ya × Lz, where Lz is the standard required resource amount, specifically the resource required amount corresponding to the intermediate value of the real-time priority index. Similarly, calculate the required resource amount for all real-time communication services a. Then, the historical data corresponding to the real-time communication service a is obtained, and the peak hours and regular hours corresponding to the real-time communication service a are obtained based on the historical data. At the same time, different demand resource amounts are allocated to the peak hours and regular hours, and resource allocation optimization information is generated and transmitted to the optimization information output module.

[0034] The optimization information output module is used to perform corresponding resource allocation according to the obtained resource allocation optimization information.

[0035] Example 2 As the second embodiment of the present invention, it is implemented on the basis of the first embodiment, and differs from the first embodiment in the following aspects: The resource allocation optimization module transmits the generated resource allocation optimization information to the transmission optimization analysis module and analyzes it.

[0036] The transmission optimization analysis module is used to process the obtained resource allocation optimization information, obtain the real-time service traffic distribution nodes corresponding to the real-time communication service a, and obtain the service traffic corresponding to the distribution nodes. At the same time, it screens the distribution nodes whose service traffic exceeds the threshold. The specific value of the threshold is set by the operator and is recorded as an excess node. Taking the excess nodes as the starting point, draw the corresponding network topology diagram and generate the transmission path. At the same time, conduct a comprehensive analysis based on the delay, packet loss rate and broadband utilization of the transmission path to obtain the comprehensive index of the transmission path. Here, the delay, packet loss rate and broadband utilization are quantified to obtain the corresponding quantitative index, and then weighted processing is performed to obtain the comprehensive index. The specific processing method is the same as the processing method of the above-mentioned communication business, and the transmission path corresponding to the maximum comprehensive index is selected as the standard. The larger the comprehensive index here, the better the overall performance of the transmission path. Generate a standard transmission path, further generate transmission optimization information, and transmit it to the optimization information output module.

[0037] The optimization information output module is used to transmit according to the acquired transmission optimization information.

[0038] Example 3 As the third embodiment of the present invention, the focus is on combining the implementation processes of the first and second embodiments.

[0039] Some of the data in the above formulas are calculated based on their numerical values and are not substituted into parameter units for calculation. At the same time, the contents not described in detail in this specification belong to the existing technology known to those skilled in the art.

[0040] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A service optimization communication system based on 5G LAN static multicast communication, characterized by: include: The communication service analysis module is used to analyze the real-time priority of all communication services based on the service demand information transmitted by the communication basic information collection module. By quantifying the delay requirements, packet loss rate and service continuity of the communication services, corresponding quantitative assignments are obtained. The real-time priority index of the communication services is obtained through a weighted algorithm. At the same time, priority ranking information is generated from the largest to the smallest and transmitted; The resource allocation optimization module is used to allocate resources for real-time communication services based on the obtained priority ranking information, calculate the required resource volume based on the real-time priority indicators corresponding to the real-time communication services, determine the peak hours and regular hours based on historical data, allocate different required resource volumes at the same time, generate resource allocation optimization information, and transmit it to the transmission optimization analysis module; The transmission optimization analysis module is used to perform transmission optimization processing on the obtained resource allocation optimization information. It separates the service traffic of each node according to the real-time service traffic of the real-time communication service, filters out the excess nodes that exceed the threshold, and generates a transmission path based on the network topology diagram. It calculates the comprehensive index of the transmission path based on the delay, packet loss rate and broadband utilization rate, and selects the transmission path with the largest comprehensive index to generate transmission optimization information, which is then transmitted to the optimization information output module.

2. The service optimization communication system based on 5G LAN static multicast communication according to claim 1, characterized in that: It also includes a communication basic information collection module for acquiring all communication services and corresponding business demand information and transmitting it to the communication service analysis module, where the business demand information includes delay requirements, packet loss rate and business continuity.

3. The service optimization communication system based on 5G LAN static multicast communication according to claim 1, characterized in that: The communication service analysis module quantifies the delay requirement, packet loss rate, and service continuity of the communication service, and obtains the corresponding quantitative values in the following manner: Get all the communication services and label them as i, where i=1, 2, ..., j, where j represents the number of communication services; The delay requirements of communication services are quantified and the delay requirements are classified into strict tolerance, medium tolerance, general tolerance and loose tolerance, and the values are assigned as 4, 3, 2 and 1 respectively; The packet loss rate of communication services is quantified and the packet loss rate classification levels are determined to obtain extremely low packet loss rate, low packet loss rate, medium packet loss rate and high packet loss rate, and the values are assigned to them as 4, 3, 2 and 1 respectively; The communication business continuity is quantified to determine the business continuity classification levels, which include extremely high continuity requirements, high continuity requirements, medium continuity requirements and low continuity requirements, and are assigned values of 4, 3, 2 and 1 respectively.

4. The service optimization communication system based on 5G LAN static multicast communication according to claim 1, characterized in that: The specific method for the communication service analysis module to generate the priority information is as follows: According to the formula Calculate the real-time priority index Yi corresponding to the communication service i, where Ci is the delay requirement value, Bi is the packet loss rate value, and Hi is the service continuity value. and is the weight coefficient, and + =1, and sort them from large to small to generate priority information, and transmit it to the resource allocation optimization module.

5. The service optimization communication system based on 5G LAN static multicast communication according to claim 1, characterized in that: The specific method for the resource allocation optimization module to generate resource allocation optimization information is as follows: Obtain all real-time communication services and label them as a, where a=1, 2, ..., b, where b represents the number of real-time communication services. Obtain the real-time priority index Ya corresponding to real-time communication service a. Calculate the corresponding required resource amount based on the real-time priority index Ya. Calculate the required resource amount La for real-time communication service a using the formula La=Ya×Lz, where Lz is the standard required resource amount. Obtain historical data of real-time communication service a, and obtain corresponding peak hours and regular hours, and allocate different demand resources for peak hours and regular hours, generate resource allocation optimization information, and transmit it to the optimization information output module.

6. The service optimization communication system based on 5G LAN static multicast communication according to claim 1, characterized in that: The transmission optimization analysis module selects excess nodes exceeding the threshold in the following manner: The real-time service traffic distribution node corresponding to the real-time communication service a is obtained, and the service traffic corresponding to the distribution node is obtained. At the same time, the distribution nodes whose service traffic exceeds the threshold are screened. The specific value of the threshold is set by the operator and recorded as excess nodes.

7. The service optimization communication system based on 5G LAN static multicast communication according to claim 1, characterized in that: The specific method in which the transmission optimization analysis module selects the transmission path with the largest comprehensive index to generate transmission optimization information is as follows: Taking the excess nodes as the starting point, the corresponding network topology diagram is drawn and the transmission path is generated. The delay, packet loss rate and broadband utilization are quantified and weighted to obtain the comprehensive index of the transmission path. The transmission path corresponding to the maximum comprehensive index is selected as the standard to generate the standard transmission path. The transmission optimization information is further generated and transmitted to the optimization information output module.

8. The service optimization communication system based on 5G LAN static multicast communication according to claim 1, characterized in that: It also includes an optimization information output module for optimizing communication services based on resource allocation optimization information and transmission optimization information.

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