Explicit congestion control method and transmitter based on 5G mobile information openness

Abstract

The present application provides an explicit congestion control method and a transmitter based on 5G mobile information openness, the method comprising: actively acquiring a mobile network switching signal of a terminal in a mobile scenario and served by a mobile 5G network based on MEC; encapsulating the mobile network switching signal into a target TCP message currently being transmitted in the mobile 5G network, the target TCP message being a TCP message equipped with a BBR congestion control algorithm, so that the sender of the target TCP message performs congestion control correction on the target TCP message when or after learning that the mobile network switching signal is encapsulated in the message to shorten and optimize its transmission time. The present application can effectively and timely improve the throughput of TCP messages equipped with a BBR congestion control algorithm transmitted between a terminal in a mobile scenario and served by a 5G network and a server, can effectively improve the data transmission performance in a mobile 5G network, and is particularly suitable for high-speed mobile scenarios such as mobile high-speed rail environments.

Description

Technical Field

[0001] The present application relates to the field of data transmission technology, and in particular to an explicit congestion control method and a transmitter based on 5G mobile information openness. Background Art

[0002] To achieve reliable data transmission, the TCP protocol relies on flow control and congestion control to avoid network congestion and widespread packet loss, which can disrupt the network's transmission capacity. Currently, TCP research focuses on congestion control. By adjusting congestion control algorithms to optimize data transmission performance at the transport layer, researchers have optimized the dynamics of TCP connections in diverse network environments, from the earliest Reno algorithm to the more recent BBR algorithm. These efforts maximize the utilization of network bandwidth resources and achieve high-speed transmission. In mobile 5G network scenarios, despite the widespread adoption of the BBR algorithm, bandwidth measurement is significantly impacted by frequent data interruptions caused by handovers. This leads to underestimated network capacity, reduced transmission rates, and a waste of network resources. Therefore, optimization of the data transmission process in mobile 5G networks is necessary.

[0003] Currently, existing explicit congestion control methods based on 5G mobile information disclosure typically first measure transport layer performance, particularly the transmission performance of the TCP module. Current mainstream transport layer measurement methods and tools, such as tcpdump and wireshark, rely on performance metrics proactively reported by the transport layer, such as throughput, round-trip delay, and packet loss rate. These methods then passively implement explicit congestion control based on 5G mobile information disclosure based on the measurement results. However, since these one-sided measurements of internal transport layer metrics fail to reflect how they are specifically affected by the mobile environment, and passive optimization methods are prone to missing optimal optimization opportunities, existing methods cannot guarantee the effectiveness of explicit congestion control based on 5G mobile information disclosure, particularly the throughput of TCP packets using the BBR congestion control algorithm transmitted over mobile 5G networks. Summary of the Invention

[0004] In view of this, the embodiments of the present application provide an explicit congestion control method and a transmitter based on 5G mobile information openness to eliminate or improve one or more defects existing in the prior art.

[0005] The first aspect of the present application provides an explicit congestion control method based on 5G mobile information openness, including:

[0006] Actively acquire the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network based on MEC;

[0007] The mobile network switching signal is encapsulated into a target TCP message currently transmitted in the mobile 5G network, where the target TCP message is a TCP message equipped with a BBR congestion control algorithm, so that the sender of the target TCP message performs congestion control correction on the target TCP message when or after learning that the mobile network switching signal is encapsulated in the target TCP message, so as to shorten and optimize the transmission time of the target TCP message.

[0008] In some embodiments of the present application, in the explicit congestion control method based on 5G mobile information openness provided in the first aspect, the MEC-based active acquisition of the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network includes:

[0009] Real-time acquisition of signaling messages between terminals and base stations in mobile scenarios and served by mobile 5G networks based on the RNIS wireless network information service;

[0010] A mobile network switching signal is extracted from the signaling message.

[0011] In some embodiments of the present application, in the explicit congestion control method based on 5G mobile information openness provided in the first aspect, encapsulating the mobile network switching signal into a target TCP message currently transmitted in the mobile 5G network includes:

[0012] According to the mobile network switching signal, perform identity switching processing on the reserved bit in the target TCP message currently transmitted in the mobile 5G network, and generate a corresponding identity switching message;

[0013] The identification switching message is sent to a sending end of the target TCP message, so that the sending end knows that the mobile network switching signal is encapsulated in the target TCP message.

[0014] In some embodiments of the present application, in the explicit congestion control method based on 5G mobile information openness provided in the first aspect, the sender of the target TCP message, upon or after learning that the mobile network switching signal is encapsulated in the target TCP message, performs congestion control correction on the target TCP message to shorten and optimize the transmission time of the target TCP message, including:

[0015] When or after learning that the mobile network switching signal is encapsulated in the target TCP message, the sender of the target TCP message retrieves a round-trip delay measurement value measured in advance based on the BBR congestion control algorithm, and uses the round-trip delay measurement value instead of the currently extended transmission time to perform bandwidth calculation to shorten and optimize the transmission time.

[0016] In some embodiments of the present application, in the explicit congestion control method based on 5G mobile information opening provided in the first aspect, before the MEC actively obtains the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network, it also includes:

[0017] Receive a notification message, wherein the notification message includes: an explicit congestion control object based on 5G mobile information openness is a TCP message carrying a BBR congestion control algorithm;

[0018] Setting the target TCP packet according to the notification message to: a TCP packet equipped with a BBR congestion control algorithm;

[0019] The explicit congestion control object based on 5G mobile information opening is determined in advance based on a 5G network transmission performance test and analysis method under a mobile scenario, and the 5G network transmission performance test and analysis method under a mobile scenario includes:

[0020] Based on a pre-set testbed platform, a transmission comparison test was conducted on TCP packets equipped with the CUBIC congestion control algorithm and TCP packets equipped with the BBR congestion control algorithm in a mobile 5G network, respectively, against the UDP protocol, and corresponding comparison test results were obtained.

[0021] Obtaining target data of transmission interruption and / or throughput reduction of TCP packets equipped with the CUBIC congestion control algorithm and TCP packets equipped with the BBR congestion control algorithm from the comparative test results;

[0022] The reasons for the decrease in the throughput of the TCP message equipped with the BBR congestion control algorithm are determined according to the target data, including: a mobile network switching event causing a prolonged transmission time from data transmission to data confirmation;

[0023] The TCP message equipped with the BBR congestion control algorithm is determined as an explicit congestion control object based on 5G mobile information openness, and a corresponding notification message is generated and output.

[0024] The second aspect of the present application provides an explicit congestion control method based on 5G mobile information openness, including:

[0025] A mobile network switching signal encapsulated in a target TCP message currently transmitted in the mobile 5G network is queried, wherein the mobile network switching signal is sent by a terminal in a mobile scenario and served by the mobile 5G network, and the mobile network switching signal is actively obtained by the MEC server and encapsulated into the target TCP message, wherein the target TCP message carries a BBR congestion control algorithm;

[0026] Congestion control correction is performed on the target TCP message to shorten and optimize the transmission time of the target TCP message.

[0027] In some embodiments of the present application, in the explicit congestion control method based on 5G mobile information openness provided in the second aspect, performing congestion control correction on the target TCP message to shorten and optimize the transmission time of the target TCP message includes:

[0028] A round-trip delay measurement value pre-measured based on the BBR congestion control algorithm is retrieved, and the round-trip delay measurement value is used instead of the currently extended transmission time to perform bandwidth calculation to shorten and optimize the transmission time.

[0029] In some embodiments of the present application, in the explicit congestion control method based on 5G mobile information openness provided in the second aspect, the mobile network switching signal is actively obtained by the MEC server and encapsulated into the target TCP message, including:

[0030] The MEC server actively obtains the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network based on MEC, and the MEC server encapsulates the mobile network switching signal into the target TCP message currently transmitted in the mobile 5G network.

[0031] In some embodiments of the present application, in the explicit congestion control method based on 5G mobile information openness provided in the second aspect, the MEC server actively obtains the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network based on the MEC, including:

[0032] The MEC server obtains signaling messages exchanged between terminals and base stations in mobile scenarios and served by mobile 5G networks in real time based on the RNIS wireless network information service; and extracts mobile network switching signals from the signaling messages.

[0033] In some embodiments of the present application, in the explicit congestion control method based on 5G mobile information openness provided in the second aspect, the MEC server encapsulates the mobile network switching signal into a target TCP message currently transmitted in the mobile 5G network, including:

[0034] The MEC server performs an identification switching process on the reserved bits in the target TCP message currently transmitted in the mobile 5G network according to the mobile network switching signal, and generates a corresponding identification switching message; the MEC server sends the identification switching message to the sender of the target TCP message, so that the sender knows that the mobile network switching signal is encapsulated in the target TCP message.

[0035] In some embodiments of the present application, in the explicit congestion control method based on 5G mobile information opening provided in the second aspect, the MEC server, before actively acquiring the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network based on the MEC, further includes:

[0036] The MEC server receives a notification message, wherein the notification message includes: an explicit congestion control object based on 5G mobile information openness is a TCP packet carrying a BBR congestion control algorithm;

[0037] The MEC server sets the target TCP packet to a TCP packet using the BBR congestion control algorithm according to the notification message.

[0038] The explicit congestion control object based on 5G mobile information opening is determined in advance based on a 5G network transmission performance test and analysis method under a mobile scenario, and the 5G network transmission performance test and analysis method under a mobile scenario includes:

[0039] Based on a pre-set testbed platform, a transmission comparison test was conducted on TCP packets equipped with the CUBIC congestion control algorithm and TCP packets equipped with the BBR congestion control algorithm in a mobile 5G network, respectively, against the UDP protocol, and corresponding comparison test results were obtained.

[0040] Obtaining target data of transmission interruption and / or throughput reduction of TCP packets equipped with the CUBIC congestion control algorithm and TCP packets equipped with the BBR congestion control algorithm from the comparative test results;

[0041] The reasons for the decrease in the throughput of the TCP message equipped with the BBR congestion control algorithm are determined according to the target data, including: a mobile network switching event causing a prolonged transmission time from data transmission to data confirmation;

[0042] The TCP message equipped with the BBR congestion control algorithm is determined as an explicit congestion control object based on 5G mobile information openness, and a corresponding notification message is generated and output.

[0043] Another aspect of the present application further provides an MEC server, including:

[0044] The handover perception module is used to actively obtain the current mobile network handover signal of the terminal in the mobile scene and served by the mobile 5G network based on MEC;

[0045] A switching notification module is used to encapsulate the mobile network switching signal into a target TCP message currently transmitted in the mobile 5G network, where the target TCP message is a TCP message equipped with a BBR congestion control algorithm, so that the sender of the target TCP message performs congestion control correction on the target TCP message when or after learning that the mobile network switching signal is encapsulated in the target TCP message, so as to shorten and optimize the transmission time of the target TCP message.

[0046] Another aspect of the present application further provides a TCP message sending end, including:

[0047] A handover query module is configured to query a target TCP message currently being transmitted in a mobile 5G network to obtain a mobile network handover signal encapsulated therein, wherein the mobile network handover signal is sent by a terminal in a mobile scenario and served by a mobile 5G network, and the mobile network handover signal is actively obtained by the MEC server and encapsulated into the target TCP message, wherein the target TCP message carries a BBR congestion control algorithm;

[0048] The congestion control module is used to perform congestion control correction on the target TCP message to shorten and optimize the transmission time of the target TCP message.

[0049] Another aspect of the present application further provides an explicit congestion control system based on 5G mobile information openness, including:

[0050] An MEC server, configured to implement the explicit congestion control method based on 5G mobile information openness provided in the first aspect;

[0051] The sending end of the TCP message includes: a terminal in a mobile scenario and served by a mobile 5G network, or a server connected to the terminal through communication between a base station; and the sending end of the TCP message is used to implement the explicit congestion control method based on 5G mobile information openness provided by the aforementioned second aspect.

[0052] Another aspect of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, it implements the explicit congestion control method based on 5G mobile information openness provided in the first aspect, or implements the explicit congestion control method based on 5G mobile information openness provided in the second aspect.

[0053] Another aspect of the present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it implements the explicit congestion control method based on 5G mobile information openness provided in the first aspect, or implements the explicit congestion control method based on 5G mobile information openness provided in the second aspect.

[0054] The explicit congestion control method based on 5G mobile information openness provided in the present application actively obtains the current mobile network switching signal of a terminal in a mobile scenario and served by a mobile 5G network based on MEC; encapsulates the mobile network switching signal into a target TCP message currently transmitted in the mobile 5G network, where the target TCP message is a TCP message carrying a BBR congestion control algorithm, so that the sender of the target TCP message performs congestion control correction on the target TCP message when or after learning that the mobile network switching signal is encapsulated in the target TCP message to shorten and optimize the transmission time of the target TCP message. This method can effectively improve the throughput of TCP messages carrying a BBR congestion control algorithm transmitted between a terminal in a mobile scenario and served by a 5G network and a server, optimizes the existing transport layer congestion control algorithm, improves its ability to utilize network bandwidth, and performs cross-layer low-overhead optimization at the congestion control algorithm level, which can effectively improve the data transmission performance in the mobile 5G network and is particularly suitable for high-speed mobile scenarios such as high-speed rail environments.

[0055] Additional advantages, purposes, and features of the present application will be described in part in the following description and will become apparent to those skilled in the art upon study of the following or may be learned from practice of the present application. The purposes and other advantages of the present application may be achieved and obtained by the structures specifically pointed out in the specification and drawings.

[0056] Those skilled in the art will understand that the purposes and advantages that can be achieved by the present application are not limited to the above specific description, and the above and other purposes that can be achieved by the present application will be more clearly understood based on the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The drawings described herein are intended to provide a further understanding of the present application, constitute a part of the present application, and do not constitute a limitation of the present application. The components in the drawings are not drawn to scale, but are only for the purpose of illustrating the principles of the present application. In order to facilitate the illustration and description of some parts of the present application, the corresponding parts in the drawings may be enlarged, that is, they may become larger than other components in the exemplary device actually manufactured according to the present application. In the drawings:

[0058] Figure 1This is a schematic diagram of the overall process of the first explicit congestion control method based on 5G mobile information opening in one embodiment of the present application.

[0059] Figure 2 This is a specific flow chart of the first explicit congestion control method based on 5G mobile information openness in one embodiment of the present application.

[0060] Figure 3 This is a specific flow chart of a method for testing and analyzing 5G network transmission performance in a mobile scenario in one embodiment of the present application.

[0061] Figure 4 This is a schematic diagram of the overall process of the second explicit congestion control method based on 5G mobile information opening in one embodiment of the present application.

[0062] Figure 5 This is a structural diagram of the MEC server in another embodiment of the present application.

[0063] Figure 6 This is a structural diagram of the sending end of the TCP message in another embodiment of the present application.

[0064] Figure 7 This is an example diagram of the test bed platform provided in the application example of this application.

[0065] Figure 8 The figure is a schematic diagram of the time-varying curve of the throughput of the UDP stream and the TCP stream equipped with the CUBIC algorithm in the application example of this application.

[0066] Figure 9 This is a schematic diagram of the "step-down" BBR throughput example provided in the application example of this application.

[0067] Figure 10 This is a schematic diagram of the principle of the message mechanism for reporting switching events to the sending end provided in the application example of this application. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail in conjunction with the embodiments and drawings. Here, the illustrative embodiments of this application and their descriptions are used to explain this application, but are not intended to limit this application.

[0069] It should also be noted here that in order to avoid obscuring the present application due to unnecessary details, the accompanying drawings only show structures and / or processing steps that are closely related to the scheme according to the present application, while other details that are not closely related to the present application are omitted.

[0070] It should be emphasized that the term "include / comprises" when used herein refers to the existence of features, elements, steps or components, but does not exclude the existence or addition of one or more other features, elements, steps or components.

[0071] It should also be noted that, unless otherwise specified, the term "connection" herein may refer not only to a direct connection but also to an indirect connection involving an intermediate.

[0072] Hereinafter, embodiments of the present application will be described with reference to the accompanying drawings. In the accompanying drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0073] Since the birth of the internet, its infrastructure has undergone numerous iterations. Today, the most widely used model remains the five-layer network model based on TCP / IP. From the bottom up, these layers are: physical layer, data link layer, network layer, transport layer, and application layer. Transport layer protocols primarily manage end-to-end network connections, enabling multiplexing, flow control, and congestion control. These protocols primarily include the TCP Transmission Control Protocol and the UDP User Datagram Protocol. TCP is the most widely used, providing reliable data transmission services. To achieve reliable data transmission, TCP relies on flow control and congestion control to avoid network congestion and widespread packet loss, which can compromise network transmission capacity. Currently, TCP research focuses on congestion control. By adjusting congestion control algorithms to optimize transport layer data transmission performance, from the earliest Reno algorithm to the more recent BBR algorithm, various approaches have been taken to optimize TCP connections to adapt to varying network environments, maximizing network bandwidth utilization and achieving high-speed transmission. Over the past decade, mobile communication networks have experienced tremendous growth. 5G mobile communication technology offers high bandwidth, low latency, and massive connections, providing a solid technical foundation for the development of mobile internet applications. However, a major problem brought about by mobile communications is the base station handover problem of communication terminals. Since the signal coverage provided by a single base station is limited, mobile communication operators need to deploy multiple base stations within the communication range to achieve signal coverage. When a terminal moves between base station coverage areas, it needs to switch from the originally connected base station to the base station with the new coverage area. Under the current mobile communication standards, this handover process will cause the communication data stream to be disconnected for a period of time. In high-speed mobile scenarios, the rapid change of location causes frequent handovers, and the resulting data interruption problem will seriously affect the efficiency of communication. In particular, for the transport layer responsible for ensuring reliable transmission, the handover problem will have a significant negative impact on the transport layer.

[0074] At the same time, current transmission performance measurements of the transport layer in mobile scenarios, especially those of the TCP module, are relatively limited. Only unilateral measurements of indicators within the transport layer cannot reflect how it is specifically affected by the mobile environment. Therefore, combining the measurement of wireless communication performance indicators with transmission performance indicators will be of great significance.

[0075] Since its first appearance in the 1970s, congestion control algorithms have undergone continuous iterations and updates at all levels, making them more suitable for high-speed, reliable network data transmission and various complex network dynamic environments. Optimization of congestion control algorithms has primarily focused on two aspects: congestion detection and congestion avoidance. Classic congestion control algorithms, such as Reno, established the basic framework of congestion control algorithms: a control cycle from slow start to congestion detection and congestion avoidance. The congestion control window is used to adjust the number of TCP packets sent when earlier packets are unacknowledged, thereby regulating the sending rate and adapting to network congestion conditions. The Reno algorithm largely solved the network congestion problem of the time. Subsequent algorithms such as BIC and CUBIC also inherited Reno's ideas, namely, congestion detection and congestion avoidance based on packet loss, but improved the congestion window growth method to enable faster convergence to the network's appropriate sending rate. However, with the continuous development of wireless networks and the increasing bandwidth, loss-based congestion control algorithms have limited the accompanying growth in transmission rates, resulting in a waste of bandwidth resources. To address the shortcomings of packet loss detection, delay-based congestion control algorithms such as Vegas and Westwood have been proposed. Their congestion windows decrease as network delay increases and increase as delay decreases. Theoretically, they can maintain high transmission rates. However, they are at a disadvantage in bandwidth competition compared to the majority of loss-based congestion control connections on the network, and have therefore not been widely adopted. Subsequently, congestion control algorithms based on bandwidth-delay product, such as the BBR algorithm, have combined these improvements and achieved better results. The BBR algorithm consistently measures network bandwidth and round-trip delay, using this information to estimate the actual network capacity and directly derive a preferred transmission rate. The BBR algorithm is currently widely used. However, in mobile networks, frequent data interruptions caused by handovers significantly impact bandwidth measurement, leading to an underestimation of network capacity, a reduction in transmission rates, and a waste of network resources.

[0076] Since the switching problem in the mobile scenario has a great impact on the transport layer performance, and the existing explicit congestion control method based on the openness of 5G mobile information cannot accurately optimize the transmission performance of TCP packets equipped with the BBR congestion control algorithm transmitted in the mobile 5G network, that is, it cannot effectively and timely improve its throughput, etc., this application proposes an optimization method for the transport layer congestion control algorithm to resist the negative impact of switching in the mobile scenario. Specifically, it is an explicit congestion control method based on the openness of 5G mobile information, which uses the open physical layer information of the 5G network to actively obtain switching information across layers, optimizes the existing transport layer congestion control algorithm, and improves its ability to utilize network bandwidth.

[0077] In one or more embodiments of the present application, the 5G mobile information exposure refers to exposing the switching information of the mobile UE to the video server through devices such as MEC. This is also referred to as "actively acquiring the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network based on MEC" in the present application.

[0078] In one or more embodiments of the present application, the explicit means that part of the congestion signal of the congestion control comes from the switching information disclosed by 5G, and is directly and clearly told to the sender that this is not congestion, but an illusion caused by switching.

[0079] The details are described in detail through the following examples.

[0080] Based on this, in order to effectively and timely improve the data transmission performance of the mobile 5G network, the embodiment of the present application provides a first explicit congestion control method based on 5G mobile information opening that can be executed by the MEC server, see Figure 1 The first explicit congestion control method based on 5G mobile information openness executed by the MEC server specifically includes the following contents:

[0081] Step 100: Actively obtain the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network based on MEC.

[0082] It is understandable that the handover event is obtained by using the open function of the 5G network. Since its introduction, 5G has emphasized the openness of the cellular network. This application uses the RNIS wireless network information service to deploy the mobile edge computing unit MEC near the base station to obtain the signaling messages interacting between the terminal and the base station in real time, extract the handover signal and report it to the next process.

[0083] Step 200: Encapsulate the mobile network switching signal into a target TCP message currently transmitted in the mobile 5G network, where the target TCP message is a TCP message equipped with a BBR congestion control algorithm, so that the sender of the target TCP message performs congestion control correction on the target TCP message when or after learning that the mobile network switching signal is encapsulated in the target TCP message to shorten and optimize the transmission time of the target TCP message.

[0084] In one or more embodiments of the present application, the sender of the target TCP message or the sender of the TCP message may refer to: a terminal in a mobile scenario and served by a mobile 5G network, or a server connected to the terminal through communication between a base station; that is, the sender of the TCP message transmitted to the server is the terminal (i.e., mobile UE), and the sender of the TCP message transmitted to the terminal is the server. The present application is particularly applicable to scenarios where the sender of the TCP message transmitted to the terminal is the server.

[0085] In static scenarios, BBR outperformed CUBIC, achieving 88% bandwidth utilization relative to UDP, compared to CUBIC's 31%. However, in high-speed mobile scenarios, the situation reversed, with BBR achieving only 26.6% (or 26 Mbps) of the baseline UDP throughput utilization. Furthermore, TCP flows using the BBR algorithm experienced a "step-down" throughput decline, meaning that each time throughput was affected, it would only partially recover and never reach its peak.

[0086] Through in-depth analysis of the operating mechanism of the BBR algorithm, we found that BBR requires real-time measurement of the network's bandwidth (BW) and round-trip delay (RTT) to calculate the bandwidth-delay product (BDP) and estimate the network's carrying capacity, thereby determining the congestion window and controlling the sending rate. BBR measures bandwidth and delay in the "Probe_BW" and "Probe_RTT" phases, respectively. The current bandwidth measurement value BtlBW at time T is calculated using formula (1), W R represents the past 10 RTTs, t represents any RTT during this period, Δdelivered represents the number of bytes sent during that RTT, and interval_us represents the actual time from sending to confirming receipt, i.e., the transmission time mentioned in one or more embodiments of this application. In practice, it is precisely because of handovers that a large number of datagrams arrive late, leading to bandwidth underestimation, low throughput, and the so-called "step-down" phenomenon.

[0087]

[0088] In other words, the embodiments of the present application address the issue that the TCP congestion control algorithm is susceptible to base station switching during mobility. This application proposes a method for optimizing TCP congestion control based on perceptible switching events, primarily based on the currently widely used BBR algorithm. The BBR algorithm is affected by switching in that the time from data transmission to confirmation of reception is magnified, resulting in an underestimation of the network bandwidth. Therefore, this application corrects the data transmission time by sensing base station switching in advance and notifying the sender, thereby obtaining the correct bottleneck bandwidth. The optimization algorithm is named BBR-H.

[0089] From the above description, it can be seen that the explicit congestion control method based on 5G mobile information openness provided in the embodiment of the present application can effectively improve the throughput of TCP packets equipped with the BBR congestion control algorithm transmitted between terminals and servers in mobile scenarios and served by 5G networks, optimize the existing transport layer congestion control algorithm, improve its ability to utilize network bandwidth, and perform cross-layer low-overhead optimization at the congestion control algorithm level. It can effectively improve the data transmission performance in mobile 5G networks, and is especially suitable for high-speed mobile scenarios such as high-speed rail environments in motion, and can improve the user experience of using terminals based on 5G networks in mobile scenarios.

[0090] In order to further improve the reliability and timeliness of obtaining mobile network switching signals, in the first explicit congestion control method based on 5G mobile information openness performed by a MEC server provided in an embodiment of the present application, see Figure 2 Step 100 of the first explicit congestion control method based on 5G mobile information openness performed by the MEC server further specifically includes the following content:

[0091] Step 110: Based on the RNIS wireless network information service, real-time acquisition of signaling messages exchanged between a terminal in a mobile scenario and served by a mobile 5G network and a base station.

[0092] Step 120: Extract the mobile network handover signal from the signaling message.

[0093] In order to further improve the accuracy and reliability of congestion control correction of TCP messages, in the first explicit congestion control method based on 5G mobile information openness performed by a MEC server provided in an embodiment of the present application, see Figure 2 Step 200 of the first explicit congestion control method based on 5G mobile information openness performed by the MEC server further specifically includes the following content:

[0094] Step 210: Based on the mobile network switching signal, perform identification switching processing on the reserved bits in the target TCP message currently transmitted in the mobile 5G network, and generate a corresponding identification switching message.

[0095] Step 220: Send the identification switching message to the sender of the target TCP packet, so that the sender is informed that the mobile network switching signal is encapsulated in the target TCP packet. Then, when or after learning that the mobile network switching signal is encapsulated in the target TCP packet, the sender of the target TCP packet retrieves a round-trip delay measurement value previously measured based on the BBR congestion control algorithm and uses this round-trip delay measurement value instead of the currently extended transmission time in bandwidth calculation to shorten and optimize the transmission time.

[0096] It is understandable that the MEC server encapsulates the switching signal into the target TCP message in transmission and then notifies the target TCP sender.

[0097] Specifically, after receiving the handover message, the handover notification module HONotifier located in the MEC server rewrites the message of the target TCP connection, that is, modifies the reserved bit of the message to 1 to mark the handover.

[0098] It is understandable that at the sending end, once a set reserved bit is found in a message, it means that the TCP stream in which the message is located is undergoing switching, and then the network socket corresponding to the stream is found, and the congestion control algorithm is corrected or submitted to the application layer for cross-layer optimization.

[0099] Specifically, upon receiving the handover message, the system kernel's congestion control module can perform bandwidth correction by correcting the amplified interval_us. Here, RTprob, the round-trip delay value continuously measured by the BBR algorithm, is used instead of interval_us for bandwidth calculation. RTprob is the time it takes for a packet to be sent and acknowledged, measured during the "Probe_RTT" phase. Similar to interval_us, RTprob is not as dynamic, but it is reasonable to use it instead of interval_us in this case.

[0100] In order to further improve the accuracy and reliability of congestion control correction of TCP messages, in the first explicit congestion control method based on 5G mobile information openness performed by a MEC server provided in an embodiment of the present application, see Figure 2 , the first explicit congestion control method based on 5G mobile information openness executed by the MEC server further specifically includes the following contents before step 100:

[0101] Step 010: Receive a notification message, wherein the notification message includes: the explicit congestion control object based on 5G mobile information openness is a TCP message equipped with a BBR congestion control algorithm.

[0102] Step 020: According to the notification message, the target TCP message is set to: a TCP message equipped with a BBR congestion control algorithm, wherein the explicit congestion control object based on 5G mobile information openness is determined in advance based on the 5G network transmission performance test and analysis method in the mobile scenario.

[0103] Since the current mainstream transport layer measurement methods and tools such as tcpdump and wireshark are based on performance indicators actively reported by the transport layer, such as throughput, round-trip delay, and packet loss rate, they lack detection and comprehensive consideration of mobile wireless links in mobile scenarios, making it difficult to qualitatively and quantitatively analyze the specific impact of the underlying mobile network on the transport layer. Therefore, to address the problem that the existing explicit congestion control method based on 5G mobile information openness is difficult to directly measure the negative effects in advance through existing tools, the explicit congestion control method based on 5G mobile information openness provided in this application can also provide a methodology for combining the measurement of mobile communication wireless link status and transport layer performance indicators. That is, the 5G network transmission performance testing and analysis method based on mobile scenarios mentioned in one or more embodiments of this application mainly relies on the measurement and comprehensive analysis of physical layer link indicators and transport layer performance indicators, mainly including wireless physical layer signal quality monitoring and the establishment of a communication signaling collection platform, a transport layer protocol indicator monitoring platform and indicator analysis, and synchronizing communication indicators and signaling with transport layer indicators by timestamp for comprehensive analysis.

[0104] See also Figure 3 The 5G network transmission performance test and analysis method in the mobile scenario specifically includes the following contents:

[0105] Step 1: Based on the preset testbed platform, a transmission comparison test was conducted on TCP packets equipped with the CUBIC congestion control algorithm and TCP packets equipped with the BBR congestion control algorithm in the mobile 5G network, respectively, and the corresponding comparison test results were obtained;

[0106] Step 2: Obtain target data of transmission interruption and / or throughput reduction of TCP packets equipped with the CUBIC congestion control algorithm and TCP packets equipped with the BBR congestion control algorithm from the comparative test results;

[0107] Step 3: determining, based on the target data, that the reason for the decrease in the throughput of the TCP message equipped with the BBR congestion control algorithm includes: a mobile network switching event causing the transmission time from data transmission to data confirmation to be extended;

[0108] Step 4: Determine the TCP message equipped with the BBR congestion control algorithm as an explicit congestion control object based on 5G mobile information openness, and generate and output a corresponding notification message.

[0109] For example, in order to simultaneously detect wireless physical layer information signaling and transport layer performance indicators, this application has built an end-to-end physical fluctuation and transport layer performance comprehensive measurement platform for 5G networks, that is, the test bed platform mentioned in one or more embodiments of this application, which mainly includes the following modules: physical layer information acquisition module, physical layer data processing module, transport layer performance monitoring module, and comprehensive data analysis module.

[0110] (1) Physical layer information collection module: This application uses the professional software PCNET and the open source framework MobileInsight to collect interactive signaling and physical channel parameters between mobile terminals and mobile network operator base stations in real time, such as handover measurement data, handover decision signaling, and reference signal reception quality. The collected data is reported to the physical layer data processing module in real time.

[0111] (2) Physical layer data processing module: Receives reported physical channel parameters and switching events, extracts the switching occurrence time, and estimates the channel quality based on the physical channel parameters to assist in decision-making.

[0112] (3) Transport layer performance monitoring module: This module consists of two parts, located at the sending end and the receiving end. The sending end extracts the indicator information reported by the transport layer from the system kernel, such as congestion window, round-trip delay, estimated bandwidth, etc. The receiving end counts the size of the received data flow at the network card and calculates the actual throughput.

[0113] (4) Comprehensive data analysis module: responsible for summarizing the physical layer channel quality, switching events and transport layer indicators, and presenting them in a time series comparison, intuitively showing the impact of physical layer channel fluctuations and switching on transport layer data transmission.

[0114] In order to effectively and timely improve the data transmission performance of the mobile 5G network, the embodiment of the present application provides a second explicit congestion control method based on 5G mobile information opening that can be executed by the sender of the target TCP message, see Figure 4 The second explicit congestion control method based on 5G mobile information openness executed by the sender of the target TCP message specifically includes the following contents:

[0115] Step 300: Query and obtain a mobile network switching signal encapsulated in a target TCP message currently transmitted in the mobile 5G network, wherein the mobile network switching signal is sent by a terminal in a mobile scenario and served by the mobile 5G network, and the mobile network switching signal is actively obtained by the MEC server and encapsulated into the target TCP message, and the target TCP message is equipped with a BBR congestion control algorithm.

[0116] Step 400: Perform congestion control modification on the target TCP message to shorten and optimize the transmission time of the target TCP message.

[0117] There is a data interaction process between the embodiment of the second explicit congestion control method based on 5G mobile information openness performed by the sender of the target TCP message provided in this application and the first explicit congestion control method based on 5G mobile information openness performed by the MEC server. Specifically, step 300 is performed after step 200, and the embodiment of the second explicit congestion control method based on 5G mobile information openness performed by the sender of the target TCP message has the same function as the first explicit congestion control method based on 5G mobile information openness performed by the MEC server. Its function is not repeated here, and reference can be made to the detailed description of the embodiment of the explicit congestion control method based on 5G mobile information openness. Similarly, the 5G network transmission performance test and analysis method in the mobile scenario can also be performed before step 300.

[0118] In order to further improve the accuracy and reliability of congestion control correction for TCP messages, in an embodiment of the present application, provided by a sender of a target TCP message, a second explicit congestion control method based on 5G mobile information openness is performed by the sender of the target TCP message. Step 400 of the second explicit congestion control method based on 5G mobile information openness performed by the sender of the target TCP message further specifically includes the following content:

[0119] Step 410: Retrieve a round-trip delay measurement value pre-measured based on the BBR congestion control algorithm, and use the round-trip delay measurement value instead of the currently extended transmission time to perform bandwidth calculation to shorten and optimize the transmission time.

[0120] In addition, in the second explicit congestion control method based on 5G mobile information openness, the mobile network switching signal is actively obtained by the MEC server and encapsulated into the target TCP message, including:

[0121] The MEC server actively obtains the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network based on MEC, and the MEC server encapsulates the mobile network switching signal into the target TCP message currently transmitted in the mobile 5G network.

[0122] In the second explicit congestion control method based on 5G mobile information opening, the MEC server actively obtains the current mobile network switching signal of the terminal in the mobile scene and served by the mobile 5G network based on the MEC, including:

[0123] The MEC server obtains signaling messages exchanged between terminals and base stations in mobile scenarios and served by mobile 5G networks in real time based on the RNIS wireless network information service; and extracts mobile network switching signals from the signaling messages.

[0124] The MEC server encapsulates the mobile network switching signal into a target TCP message currently transmitted in the mobile 5G network, including:

[0125] The MEC server performs an identification switching process on the reserved bits in the target TCP message currently transmitted in the mobile 5G network according to the mobile network switching signal, and generates a corresponding identification switching message; the MEC server sends the identification switching message to the sender of the target TCP message, so that the sender knows that the mobile network switching signal is encapsulated in the target TCP message.

[0126] Before the MEC server actively obtains the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network based on the MEC, the MEC server also includes:

[0127] The MEC server receives a notification message, wherein the notification message includes: an explicit congestion control object based on 5G mobile information openness is a TCP packet carrying a BBR congestion control algorithm;

[0128] The MEC server sets the target TCP packet to a TCP packet using the BBR congestion control algorithm according to the notification message.

[0129] The explicit congestion control object based on 5G mobile information opening is determined in advance based on a 5G network transmission performance test and analysis method under a mobile scenario, and the 5G network transmission performance test and analysis method under a mobile scenario includes:

[0130] Based on a pre-set testbed platform, a transmission comparison test was conducted on TCP packets equipped with the CUBIC congestion control algorithm and TCP packets equipped with the BBR congestion control algorithm in a mobile 5G network, respectively, against the UDP protocol, and corresponding comparison test results were obtained.

[0131] Obtaining target data of transmission interruption and / or throughput reduction of TCP packets equipped with the CUBIC congestion control algorithm and TCP packets equipped with the BBR congestion control algorithm from the comparative test results;

[0132] The reasons for the decrease in the throughput of the TCP message equipped with the BBR congestion control algorithm are determined according to the target data, including: a mobile network switching event causing a prolonged transmission time from data transmission to data confirmation;

[0133] The TCP message equipped with the BBR congestion control algorithm is determined as an explicit congestion control object based on 5G mobile information openness, and a corresponding notification message is generated and output.

[0134] From the software level, in order to effectively and timely improve the data transmission performance of the mobile 5G network, this application also provides a MEC server for executing all or part of the first explicit congestion control method based on 5G mobile information opening, see Figure 5 , the MEC server specifically includes the following contents:

[0135] The handover sensing module 10 is configured to proactively acquire the current mobile network handover signal of a terminal in a mobile scenario and served by a mobile 5G network based on the MEC;

[0136] The switching notification module 20 is used to encapsulate the mobile network switching signal into the target TCP message currently transmitted in the mobile 5G network, where the target TCP message is a TCP message equipped with a BBR congestion control algorithm, so that the sender of the target TCP message performs congestion control correction on the target TCP message when or after learning that the mobile network switching signal is encapsulated in the target TCP message to shorten and optimize the transmission time of the target TCP message.

[0137] The embodiment of the MEC server provided in this application can be specifically used to execute the processing flow of the embodiment of the first explicit congestion control method based on 5G mobile information openness in the above-mentioned embodiment. Its functions are not repeated here, and reference can be made to the detailed description of the above-mentioned first explicit congestion control method based on 5G mobile information openness embodiment.

[0138] From the above description, it can be seen that the MEC server provided in the embodiment of the present application can effectively improve the throughput of TCP packets equipped with the BBR congestion control algorithm transmitted between terminals and servers in mobile scenarios and served by 5G networks, optimize the existing transport layer congestion control algorithm, improve its ability to utilize network bandwidth, and perform cross-layer low-overhead optimization at the congestion control algorithm level. It can effectively improve the data transmission performance in mobile 5G networks, and is especially suitable for high-speed mobile scenarios such as high-speed rail environments in motion, and can improve the user experience of using terminals based on 5G networks in mobile scenarios.

[0139] From the software level, in order to effectively and timely improve the data transmission performance of the mobile 5G network, the present application also provides a sending end of the TCP message for executing all or part of the second explicit congestion control method based on 5G mobile information opening, see Figure 6 The sending end of the TCP message specifically includes the following content:

[0140] A handover query module 30 is configured to query a target TCP message currently being transmitted in the mobile 5G network to obtain a mobile network handover signal encapsulated therein, wherein the mobile network handover signal is sent by a terminal in a mobile scenario and served by the mobile 5G network, and the mobile network handover signal is actively obtained by the MEC server and encapsulated into the target TCP message, wherein the target TCP message carries a BBR congestion control algorithm;

[0141] The congestion control module 40 is configured to perform congestion control modification on the target TCP message to shorten and optimize the transmission time of the target TCP message.

[0142] The embodiment of the sending end of the TCP message provided in this application can be specifically used to execute the processing flow of the embodiment of the second explicit congestion control method based on 5G mobile information openness in the above embodiment. Its functions will not be repeated here, and you can refer to the detailed description of the above second explicit congestion control method based on 5G mobile information openness.

[0143] The part of the TCP message sending end that performs explicit congestion control based on 5G mobile information opening can be executed in the server, and in another practical application scenario, all operations can also be completed in the client device. The specific selection can be based on the processing capability of the client device and the limitations of the user's usage scenario. This application is not limited to this. If all operations are completed in the client device, the client device may also include a processor for specific processing of explicit congestion control based on 5G mobile information opening.

[0144] The client device may include a communication module (i.e., a communication unit) that can establish a communication connection with a remote server to implement data transmission with the server. The server may include a server on the task scheduling center side, and in other implementation scenarios, may also include a server on an intermediate platform, such as a server on a third-party server platform that has a communication link with the task scheduling center server. The server may include a single computer device, a server cluster consisting of multiple servers, or a server structure of a distributed device.

[0145] The server and the client device may communicate using any suitable network protocol, including network protocols that have not yet been developed as of the filing date of this application. Examples of such network protocols include TCP / IP, UDP / IP, HTTP, and HTTPS. Furthermore, examples of such network protocols include RPC (Remote Procedure Call Protocol) and REST (Representational State Transfer) protocols, which are used on top of the aforementioned protocols.

[0146] From the above description, it can be seen that the sender of the TCP message provided in the embodiment of the present application can effectively improve the throughput of the TCP message equipped with the BBR congestion control algorithm transmitted between the terminal and the server in the mobile scenario and served by the 5G network, optimizes the existing transport layer congestion control algorithm, improves its ability to utilize network bandwidth, and performs cross-layer low-overhead optimization at the congestion control algorithm level. It can effectively improve the data transmission performance in the mobile 5G network, and is especially suitable for high-speed mobile scenarios such as high-speed rail environments in motion, and can improve the user experience of using terminals based on 5G networks in mobile scenarios.

[0147] Based on the aforementioned embodiments of the first and second explicit congestion control methods based on 5G mobile information openness, the present application further provides an explicit congestion control system based on 5G mobile information openness, which specifically includes the following contents:

[0148] An MEC server, configured to implement the aforementioned first explicit congestion control method based on 5G mobile information openness;

[0149] The sending end of the TCP message includes: a terminal in a mobile scenario and served by a mobile 5G network, or a server connected to the terminal through communication between a base station and the terminal; and the sending end of the TCP message is used to implement the aforementioned second explicit congestion control method based on 5G mobile information openness.

[0150] In order to further illustrate this solution, the switching problem in the mobile scenario has a great impact on the performance of the transport layer, and it is difficult to directly measure the negative effects through existing tools. This application also provides a specific application example of an explicit congestion control method based on 5G mobile information openness. Specifically, a method for combining the measurement of mobile communication wireless link status and transport layer performance indicators is proposed, and cross-layer exploration and targeted optimization of the existing congestion control algorithm of the transport layer are carried out.

[0151] This application example mainly addresses two issues: first, existing transport layer measurement methods and tools are severely limited in mobile scenarios. Furthermore, existing methods and supporting tools primarily focus on performance indicators within the transport layer, making it difficult to conduct cross-layer synchronization analysis in conjunction with the dynamic changes in underlying mobile communications. Second, existing transport layer protocols are susceptible to the impact of last-hop base station handovers during mobility. The resulting data interruptions directly cause congestion control algorithms to severely underestimate network bandwidth, resulting in a waste of bandwidth resources.

[0152] In summary, the application examples proposed in this application address the above issues and have two major improvements: (1) a comprehensive measurement methodology combining wireless physical layer link fluctuations and transport layer performance indicators in mobile scenarios; and (2) an optimization of the transport layer congestion control algorithm to resist the negative impact of handoffs in mobile scenarios. Specific details are as follows:

[0153] (1) Comprehensive measurement platform for 5G network end-to-end physical layer fluctuations and transport layer performance

[0154] In order to simultaneously detect wireless physical layer information signaling and transport layer performance indicators, the application example of this application has built an end-to-end physical fluctuation and transport layer performance comprehensive measurement platform for 5G networks, which mainly includes the following modules: physical layer information acquisition module, physical layer data processing module, transport layer performance monitoring module, and comprehensive data analysis module.

[0155] (1) Physical layer information acquisition module: This application example uses the professional software PCNET and the open source framework MobileInsight to collect interactive signaling and physical channel parameters between mobile terminals and mobile network operator base stations in real time, such as handover measurement data, handover decision signaling, and reference signal reception quality. The collected data is reported to the physical layer data processing module in real time.

[0156] (2) Physical layer data processing module: Receives reported physical channel parameters and switching events, extracts the switching occurrence time, and estimates the channel quality based on the physical channel parameters to assist in decision-making.

[0157] (3) Transport layer performance monitoring module: This module consists of two parts, located at the sending end and the receiving end. The sending end extracts the indicator information reported by the transport layer from the system kernel, such as congestion window, round-trip delay, estimated bandwidth, etc. The receiving end counts the size of the received data flow at the network card and calculates the actual throughput.

[0158] (4) Comprehensive data analysis module: responsible for summarizing the physical layer channel quality, switching events and transport layer indicators, and presenting them in a time series comparison, intuitively showing the impact of physical layer channel fluctuations and switching on transport layer data transmission.

[0159] The measurement platform was tested on a test bed for a small base station system built in the laboratory and showed good results. Figure 7 The test bed platform in the laboratory is shown in the figure. In a real field scenario, the user equipment will be connected to the commercial base station and its core network, but the above system modules can still operate normally. Figure 7 In this article, OAI (Openairinterface) refers to the open source software-defined radio platform 4G; USRP b210 refers to the software-defined radio device model b210; LG Nexus refers to the model of the mobile terminal UE; Server refers to the server

[0160] (2) Cross-layer analysis of network transport layer performance in mobile scenarios

[0161] Using the comprehensive measurement platform described above, this application example conducted a series of performance tests on the UDP and TCP protocols at the transport layer. Specifically, TCP with the CUBIC and BBR congestion control algorithms was compared against UDP, yielding a detailed analysis of the impact of wireless link physical layer events on the transport layer. The following explanation, using a high-speed rail mobility scenario as an example, is divided into three parts.

[0162] UDP: Compared to TCP, which requires reliable data transmission, UDP doesn't prioritize data arrival. Therefore, it's theoretically less susceptible to handover interruptions. However, experiments show that UDP throughput drops by nearly half compared to static scenarios, to just 97 Mbps. This is due to signal shielding in high-speed train cars and the overall degradation of channel quality caused by high-speed movement. Next, we'll analyze TCP using UDP as a benchmark for actual network bandwidth.

[0163] CUBIC: Experiments show that the throughput of TCP flows equipped with the CUBIC algorithm is only 44.7% of that of UDP under the same conditions, with an average throughput of 43 Mbps. Figure 8 The figure shows the throughput of a UDP flow and a TCP flow equipped with the CUBIC algorithm over time. "HO" indicates the time when the mobile handover occurs. Figure 8The data shows that the throughput of TCP flows equipped with the CUBIC algorithm will drop significantly when the user device undergoes mobile switching, especially at time points M1 and M2, and even drop to 0Mbps. In contrast, the impact on UDP after the switch is not obvious. In particular, the TCP flow cannot recover to the level before the switch for a long time after the switch, and most of them remain low for several seconds. The data obtained from our measurement platform shows that the actual data interruption during the switch is only 98 milliseconds. This is because CUBIC is a congestion control algorithm based on packet loss. During the data interruption caused by the switch, there is a high probability of network packet loss or delay, which triggers the congestion control mechanism and causes the congestion window to grow slowly. In addition, mobile switching events are too frequent, resulting in slow throughput recovery.

[0164] BBR: In static scenarios, BBR outperforms CUBIC, achieving 88% bandwidth utilization relative to UDP, compared to CUBIC's 31%. However, in high-speed mobile scenarios, the situation reverses, with BBR achieving only 26.6% throughput utilization relative to the baseline UDP, or 26 Mbps. Furthermore, TCP flows using the BBR algorithm experience a "step-down" throughput drop, meaning that each time throughput is affected, it only partially recovers and never reaches its peak throughput. See [1] for more information. Figure 9 .

[0165] Through in-depth analysis of the operating mechanism of the BBR algorithm, we found that BBR requires real-time measurement of the network's bandwidth (BW) and round-trip delay (RTT) to calculate the bandwidth-delay product (BDP) and estimate the network's carrying capacity, thereby determining the congestion window and controlling the sending rate. BBR measures bandwidth and delay in the "Probe_BW" and "Probe_RTT" phases, respectively. The current bandwidth measurement value BtlBW at time T is calculated using formula (1), W R represents the past 10 RTTs, t represents any RTT during this period, Δdelivered represents the number of bytes sent during that RTT, and interval_us represents the actual time elapsed between sending and confirming receipt. In practice, it is precisely this handoff that causes a large number of delayed datagrams, leading to an underestimated bandwidth and resulting in low throughput and the so-called "staircase drop."

[0166]

[0167] In other words, the application examples of this application provide a comprehensive measurement methodology that combines wireless physical layer link fluctuations and transport layer performance indicators in mobile scenarios. This method expands the ability to measure and conduct in-depth analysis of the network transport layer, and assists in exploring the impact of physical layer factors on network capabilities.

[0168] (3) TCP performance optimization based on perceptible switching events

[0169] To address the issue that the TCP congestion control algorithm is susceptible to base station switching during mobility, this application example proposes a method for optimizing TCP congestion control based on perceptible switching events. This method is primarily implemented based on the currently widely used BBR algorithm. The BBR algorithm is affected by switching events because the time from data transmission to data confirmation is magnified, resulting in an underestimation of network bandwidth. Therefore, this application example detects base station switching in advance and notifies the sender, correcting the data transmission time to obtain the correct bottleneck bandwidth. The optimization algorithm is named BBR-H.

[0170] The workflow of the optimization algorithm is divided into the following steps:

[0171] (1) Obtaining handover events using the open functions of the 5G network. Since its introduction, 5G has emphasized the openness of cellular networks. In this application example, the mobile edge computing unit MEC deployed near the base station obtains the signaling messages interacting between the terminal and the base station in real time through the RNIS wireless network information service, extracts the handover signal, and reports it to the next process.

[0172] (2) Encapsulate the switching signal into the TCP message being transmitted to notify the sending end. The specific principle is as follows Figure 10 As shown. Figure 10 In the process (a) to (b), TCP header represents the TCP header field, where the specific content corresponds to Figure 10In the upper part of the table, Source port indicates the source port, Destination port indicates the destination port, Sequence number indicates the sequence number; Acknowledgment number (if ACK set) indicates the TCP response number, Data offset indicates the data offset, Reserved indicates the reserved value, Checksum indicates the checksum, Window Size indicates the window, Urgent pointer (if URG SYN indicates a request to establish a connection. A TCP segment carrying the SYN flag is called a synchronization segment. FIN indicates that the local end is about to close. A TCP segment with the FIN flag is called an end segment. Raw socket indicates a raw socket. Socket indicates a network socket. Socket API indicates a socket programming interface. S1 to S n and t1 to t n All are contents in the socket mapping table.

[0173] After receiving the handover message, the handover notification module HONotifier in the MEC rewrites the target TCP connection message, modifying the reserved bit in the message to 1 to mark the handover. On the sending end, if the reserved bit is set in the message, it indicates that the TCP flow in which the message is located is undergoing a handover. The sending end then searches for the network socket corresponding to the flow and modifies the congestion control algorithm or submits it to the application layer for cross-layer optimization.

[0174] (3) Congestion control algorithm modification. After receiving the handover message, the congestion control module in the system kernel can perform bandwidth modification. Specifically, it modifies the amplified interval_us. Here, the round-trip delay measurement value RTprob continuously measured by the BBR algorithm is used instead of interval_us for bandwidth calculation. RTprob is the time from the message sent to the confirmation, measured in the "Probe_RTT" phase. Similar to interval_us, although not as dynamic as interval_us, it is reasonable and feasible to replace interval_us with it at this time.

[0175] In other words, the application examples of this application provide an optimization method for the transport layer congestion control algorithm to resist the negative impact of handoffs in mobile scenarios. The application examples of this application deeply analyze the underlying reasons why transport layer performance is affected by base station handoffs caused by mobility, and perform cross-layer low-overhead optimization of the congestion control algorithm, significantly improving transmission performance.

[0176] In summary, the core improvements of this application example are as follows:

[0177] (1) A comprehensive measurement methodology combining wireless physical layer link fluctuations and transport layer performance indicators in mobile scenarios. This methodology mainly relies on the measurement and comprehensive analysis of physical layer link indicators and transport layer performance indicators. It mainly includes the construction of a wireless physical layer signal quality monitoring and communication signaling collection platform, a monitoring platform for transport layer protocol indicators and indicator analysis, and the synchronization of communication indicators and signaling with transport layer indicators by timestamp for comprehensive analysis.

[0178] (2) Optimization of the transport layer congestion control algorithm to resist the negative impact of handover in mobile scenarios. This application example uses wireless physical layer indicator measurements and transport layer performance indicators to summarize and map them for comparison, and conducts a specific analysis of the transport layer performance loss caused by handover events. It also uses the open physical layer information of the 5G network to actively report handover information across layers, optimizing the existing transport layer congestion control algorithm and improving its ability to utilize network bandwidth.

[0179] This application example utilizes the 5G mobile network's ability to open cellular network information, combined with physical layer wireless channel measurements and transport layer indicator analysis, to conduct in-depth research on 5G network transport layer performance issues in mobile scenarios. Through measurement and analysis, key findings are drawn, and cross-layer optimization that is easy to implement is performed. The method proposed in this application example has been deployed and tested in actual scenarios. In high-speed mobile scenarios in high-speed rail environments, the optimized BBR-H congestion control method can achieve an average throughput of 52Mbps, which is twice the throughput of BBR before optimization. It also exceeds the throughput of CUBIC, greatly improving transmission performance. This has great practical significance in the future when mobile networks are more developed and used more frequently.

[0180] The embodiment of the present application also provides an electronic device (i.e., an electronic device), which may include a processor, a memory, a receiver, and a transmitter, wherein the processor is used to execute the first explicit congestion control method based on 5G mobile information openness or the second explicit congestion control method based on 5G mobile information openness mentioned in the above embodiment, wherein the processor and the memory may be connected via a bus or other means, taking a bus connection as an example. The receiver may be connected to the processor and the memory via a wired or wireless manner. The electronic device may receive real-time motion data from sensors in the wireless multimedia sensor network, and receive original video sequences from the video acquisition device.

[0181] The processor may be a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0182] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as the program instructions / modules corresponding to the first explicit congestion control method based on 5G mobile information openness or the second explicit congestion control method based on 5G mobile information openness in the embodiments of the present application. The processor executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions, and modules stored in the memory, that is, implementing the first explicit congestion control method based on 5G mobile information openness or the second explicit congestion control method based on 5G mobile information openness in the above method embodiments.

[0183] The memory 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 by the processor, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory may optionally include a memory remotely located relative to the processor, and these remote memories may be connected to the processor 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.

[0184] The one or more modules are stored in the memory, and when executed by the processor, perform the first explicit congestion control method based on 5G mobile information openness or the second explicit congestion control method based on 5G mobile information openness in the embodiment.

[0185] In some embodiments of the present application, the user equipment may include a processor, a memory and a transceiver unit, and the transceiver unit may include a receiver and a transmitter. The processor, memory, receiver and transmitter may be connected through a bus system. The memory is used to store computer instructions, and the processor is used to execute the computer instructions stored in the memory to control the transceiver unit to send and receive signals.

[0186] As an implementation method, the functions of the receiver and transmitter in this application can be considered to be implemented through a transceiver circuit or a dedicated transceiver chip, and the processor can be considered to be implemented through a dedicated processing chip, a processing circuit or a general-purpose chip.

[0187] As another implementation method, it is possible to use a general-purpose computer to implement the server provided in the embodiments of the present application. That is, the program code for implementing the functions of the processor, receiver, and transmitter is stored in a memory, and the general-purpose processor implements the functions of the processor, receiver, and transmitter by executing the code in the memory.

[0188] The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the first explicit congestion control method based on 5G mobile information openness or the second explicit congestion control method based on 5G mobile information openness. The computer-readable storage medium can be a tangible storage medium, such as a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a floppy disk, a hard disk, a removable storage disk, a CD-ROM, or any other form of storage medium known in the art.

[0189] It should be understood by those skilled in the art that the various exemplary components, systems and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software or a combination of the two. Whether it is specifically performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of this application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link via a data signal carried in a carrier.

[0190] It should be understood that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated. Those skilled in the art can make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present application.

[0191] In this application, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with or replace features of other embodiments.

[0192] The above description is merely a preferred embodiment of the present application and is not intended to limit the present application. Those skilled in the art will appreciate that various modifications and variations of the present embodiment are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. An explicit congestion control method based on 5G mobile information openness, characterized in that: include: Actively acquire the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network based on MEC; Encapsulating the mobile network switching signal into a target TCP message currently being transmitted in the mobile 5G network, where the target TCP message is a TCP message equipped with a BBR congestion control algorithm, so that a sender of the target TCP message, upon or after learning that the mobile network switching signal is encapsulated in the target TCP message, performs congestion control correction on the target TCP message to shorten and optimize the transmission time of the target TCP message; When or after learning that the mobile network switching signal is encapsulated in the target TCP message, the sender of the target TCP message performs congestion control modification on the target TCP message to shorten and optimize the transmission time of the target TCP message, including: When or after learning that the mobile network switching signal is encapsulated in the target TCP message, the sender of the target TCP message retrieves a round-trip delay measurement value measured in advance based on the BBR congestion control algorithm, and uses the round-trip delay measurement value instead of the currently extended transmission time to perform bandwidth calculation to shorten and optimize the transmission time.

2. The explicit congestion control method based on 5G mobile information openness according to claim 1, characterized in that The actively acquiring the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network based on the MEC includes: Real-time acquisition of signaling messages between terminals and base stations in mobile scenarios and served by mobile 5G networks based on the RNIS wireless network information service; A mobile network switching signal is extracted from the signaling message.

3. The explicit congestion control method based on 5G mobile information openness according to claim 1, characterized in that Encapsulating the mobile network switching signal into a target TCP message currently transmitted in the mobile 5G network includes: According to the mobile network switching signal, perform identity switching processing on the reserved bit in the target TCP message currently transmitted in the mobile 5G network, and generate a corresponding identity switching message; The identification switching message is sent to a sending end of the target TCP message, so that the sending end knows that the mobile network switching signal is encapsulated in the target TCP message.

4. The explicit congestion control method based on 5G mobile information openness according to any one of claims 1 to 3, characterized in that: Before the MEC-based active acquisition of the current mobile network switching signal of the terminal in the mobile scenario and served by the mobile 5G network, the method further includes: Receive a notification message, wherein the notification message includes: an explicit congestion control object based on 5G mobile information openness is a TCP message carrying a BBR congestion control algorithm; Setting the target TCP packet according to the notification message to: a TCP packet equipped with a BBR congestion control algorithm; The explicit congestion control object based on 5G mobile information opening is determined in advance based on a 5G network transmission performance test and analysis method under a mobile scenario, and the 5G network transmission performance test and analysis method under a mobile scenario includes: Based on a pre-set testbed platform, a transmission comparison test was conducted on TCP packets equipped with the CUBIC congestion control algorithm and TCP packets equipped with the BBR congestion control algorithm in a mobile 5G network, respectively, against the UDP protocol, and corresponding comparison test results were obtained. Obtaining target data of transmission interruption and / or throughput reduction of TCP packets equipped with the CUBIC congestion control algorithm and TCP packets equipped with the BBR congestion control algorithm from the comparative test results; The reasons for the decrease in the throughput of the TCP message equipped with the BBR congestion control algorithm are determined according to the target data, including: a mobile network switching event causing a prolonged transmission time from data transmission to data confirmation; The TCP message equipped with the BBR congestion control algorithm is determined as an explicit congestion control object based on 5G mobile information openness, and a corresponding notification message is generated and output.

5. An explicit congestion control method based on 5G mobile information openness, characterized in that: include: A mobile network switching signal encapsulated in a target TCP message currently transmitted in the mobile 5G network is queried, wherein the mobile network switching signal is sent by a terminal in a mobile scenario and served by the mobile 5G network, and the mobile network switching signal is actively obtained by the MEC server and encapsulated into the target TCP message, wherein the target TCP message carries a BBR congestion control algorithm; Performing congestion control modification on the target TCP message to shorten and optimize the transmission time of the target TCP message; The performing congestion control correction on the target TCP message to shorten and optimize the transmission time of the target TCP message includes: A round-trip delay measurement value pre-measured based on the BBR congestion control algorithm is retrieved, and the round-trip delay measurement value is used instead of the currently extended transmission time to perform bandwidth calculation to shorten and optimize the transmission time.

6. A MEC server, characterized in that: include: The handover perception module is used to actively obtain the current mobile network handover signal of the terminal in the mobile scene and served by the mobile 5G network based on MEC; a switching notification module, configured to encapsulate the mobile network switching signal into a target TCP message currently being transmitted in the mobile 5G network, where the target TCP message is a TCP message equipped with a BBR congestion control algorithm, so that a sender of the target TCP message, upon or after learning that the mobile network switching signal is encapsulated in the target TCP message, performs congestion control correction on the target TCP message to shorten and optimize the transmission time of the target TCP message; When or after learning that the mobile network switching signal is encapsulated in the target TCP message, the sender of the target TCP message performs congestion control modification on the target TCP message to shorten and optimize the transmission time of the target TCP message, including: When or after learning that the mobile network switching signal is encapsulated in the target TCP message, the sender of the target TCP message retrieves a round-trip delay measurement value measured in advance based on the BBR congestion control algorithm, and uses the round-trip delay measurement value instead of the currently extended transmission time to perform bandwidth calculation to shorten and optimize the transmission time.

7. A TCP message sending end, characterized in that: include: A handover query module is configured to query a target TCP message currently being transmitted in a mobile 5G network to obtain a mobile network handover signal encapsulated therein, wherein the mobile network handover signal is sent by a terminal in a mobile scenario and served by a mobile 5G network, and the mobile network handover signal is actively obtained by the MEC server and encapsulated into the target TCP message, wherein the target TCP message carries a BBR congestion control algorithm; A congestion control module, configured to perform congestion control correction on the target TCP message to shorten and optimize the transmission time of the target TCP message; The performing congestion control correction on the target TCP message to shorten and optimize the transmission time of the target TCP message includes: A round-trip delay measurement value pre-measured based on the BBR congestion control algorithm is retrieved, and the round-trip delay measurement value is used instead of the currently extended transmission time to perform bandwidth calculation to shorten and optimize the transmission time.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the explicit congestion control method based on 5G mobile information openness as described in any one of claims 1 to 4, or implements the explicit congestion control method based on 5G mobile information openness as described in claim 5.

Images