Network transmission protocol optimization method and system based on distributed soft bus

Abstract

The invention provides a network transmission protocol optimization method and system based on a distributed soft bus, and belongs to the field of communication. The method comprises the following steps: dividing data to be transmitted into a plurality of data segments, grouping the segmented data, sending the grouped data in sequence, confirming the grouped data by a receiver, and calculating an integrity index; according to the partial confirmation or complete confirmation sent by the receiver, dynamically adjusting the packet size, calculating the network quality score, and realizing a self-adaptive network environment; different transmission priorities are set for different types of data, and priority and timely transmission of key data is ensured by calculating priority scores; and optimizing the network transmission protocol through the three parameters of the integrity index, the priority score and the network quality score. According to the method, various dynamic optimization mechanisms are effectively integrated and applied to the field of data transmission.

Description

Technical Field

[0001] The invention belongs to the field of communications, and in particular relates to a network transmission protocol optimization method and system based on a distributed soft bus. Background Art

[0002] In the Hongmeng ecosystem, inter-device communication often relies on the soft bus transmission protocol. However, the TCP protocol directly relied on by the traditional soft bus for reliable transmission has some limitations in efficiency and reliability. Under weak network conditions with frequent on / off and limited bandwidth, problems such as low transmission rate, high latency, and data loss are prone to occur. Therefore, an optimized transmission protocol is needed to improve the performance and reliability of inter-device communication.

[0003] The present invention proposes a network transmission protocol optimization method based on Hongmeng soft bus. By improving and optimizing the transmission protocol, the efficiency and reliability of data transmission are improved. The method is applicable to inter-device communication based on Hongmeng operating system, and provides an efficient and reliable transmission solution for device interconnection in Hongmeng ecosystem. Summary of the invention

[0004] In view of this, the present invention provides a network transmission protocol optimization method based on a distributed soft bus, comprising:

[0005] Divide the data to be transmitted into multiple data segments, each of which is accompanied by a sequence number and a checksum;

[0006] The segmented data is grouped and the grouped data is sent in sequence, and the receiving party confirms the grouped data and calculates the integrity index;

[0007] Dynamically adjust the packet size and calculate the network quality score based on the partial or full confirmation sent by the receiver to achieve an adaptive network environment;

[0008] Set different transmission priorities for different types of data, and calculate priority scores to ensure timely transmission of critical data;

[0009] The network transmission protocol is optimized through the three parameters of the integrity index, priority score and network quality score.

[0010] In particular, the integrity index is calculated as follows,

[0011]

[0012] Where I(T) represents the integrity index, N is the total number of group confirmation packets, and D i (T) is the amount of data received by the i-th packet confirmation packet, L i(T) is the packet size corresponding to the i-th packet confirmation packet, and M is the maximum size of the packet; this expression reflects the completeness of data transmission within time T.

[0013] In particular, when the receiver sends a partial confirmation, it indicates that part of the packet data has been received, and the sender re-adds the unconfirmed packet data to the sending queue.

[0014] In particular, the network quality score C′(T) is calculated in real time according to the following expression:

[0015]

[0016] Where N is the total number of group confirmation packets, D i (T) represents the amount of data received by the i-th packet confirmation packet, and M represents the maximum size of the packet; by dynamically adjusting the packet size, it reflects the average effective transmission rate of the network within time T.

[0017] In particular, the transmission priority can be expressed using the calculated priority score R(T) as:

[0018]

[0019] Where N is the total number of packets, C i (T) is the congestion window size of the i-th data packet, Q i is the priority weight of the ith data packet, P i is the payload size of the ith data packet, L i (T) is the amount of data transmitted by the ith packet, and M is the maximum size of a packet; this expression takes into account congestion control, priority weight, payload size, and amount of data transmitted to calculate the priority score

[0020] In particular, the network is optimized by using the three parameters of the integrity index, priority score and network quality score, specifically including: firstly dynamically adjusting the packet size according to the network quality score C'(T) and the integrity index I(T); then performing priority scheduling on different data packets according to the priority score R(T); obtaining an optimization result through dual dynamic adjustment of the packet size and priority, and customizing an optimization strategy according to the optimization result; wherein the optimization result is calculated by the following expression:

[0021] Optimize(T) = αC′(T) β *I(T) γ *(1+λR(T)) δ

[0022] C′(T) β and I(T) γThey respectively represent the nonlinear influence of network quality and integrity on the optimization result Optimize(T);

[0023] (1+λR(T)) δ Represents the combined linear and nonlinear effects of priorities on optimization;

[0024] α controls the magnitude of the entire expression, 0<α≤1, the larger α is, the larger the Optimize(T) value is; β controls the influence of the network quality score C'(T) on the optimization; γ controls the influence of the transmission integrity score I(T) on the optimization;

[0025] δ controls the nonlinear influence of the priority score R(T) on the optimization; λ controls the magnitude and relative importance of the priority score R(T).

[0026] In particular, customizing the optimization strategy according to the optimization result specifically includes:

[0027] If the value of the optimization result Optimize(T) is greater than the first threshold, the packet size is increased to improve the transmission efficiency; or if the value of the optimization result Optimize(T) is less than the second threshold, the packet size is reduced to improve the transmission reliability;

[0028] At the same time, the priority order of sending the data packets is determined according to the priority score R(T) value.

[0029] The present invention also provides a network transmission protocol optimization system based on a distributed soft bus, comprising:

[0030] A data segmentation module, used to divide the data to be transmitted into multiple data segments, each of which is accompanied by a sequence number and a checksum;

[0031] An integrity index calculation module is used to group the segmented data, send the grouped data in sequence, and the receiving party confirms the grouped data and calculates the integrity index;

[0032] A network quality score calculation module is used to dynamically adjust the packet size and calculate the network quality score according to the partial confirmation or full confirmation sent by the receiver to achieve an adaptive network environment;

[0033] The priority score calculation module is used to set different transmission priorities for different types of data. By calculating the priority scores, it ensures the priority and timely transmission of key data.

[0034] The network transmission protocol optimization module is used to optimize the network transmission protocol through the three parameters of the integrity index, priority score and network quality score.

[0035] Beneficial effects:

[0036] The technical solution of the present invention can achieve the following technical effects:

[0037] Dynamically adjust the transmission strategy and adapt to changes in the network environment. This invention proposes a dynamic optimization mechanism that comprehensively evaluates network quality, transmission integrity and data priority. The system can monitor network conditions and transmission quality in real time, and dynamically adjust transmission parameters such as packet size, confirmation cycle, and sending window based on the comprehensive score, so that the transmission process can adapt to changes in different network environments and make full use of available network resources.

[0038] Comprehensively optimize transmission performance. By dynamically adjusting the packet size, this solution can improve data transmission efficiency when the network conditions are good and reduce transmission pressure when the network quality deteriorates. This improves the overall transmission efficiency while ensuring transmission reliability and data integrity.

[0039] In addition, with the help of the priority scheduling mechanism, key data can be given priority and transmitted in a timely manner, effectively meeting the needs of data of different priorities.

[0040] To improve the robustness and scalability of the system, this technical solution adopts a distributed architecture, with low coupling between functional modules and strong scalability. Even if a module fails, it will not affect the operation of the entire system. At the same time, the system parameter settings are flexible, and the correlation coefficient can be adjusted according to different application scenarios, showing good configurability and versatility.

[0041] Reduce implementation costs and system complexity. Compared with solutions based entirely on hardware, the software-defined approach of the present invention has lower implementation complexity and lower costs. It only requires the deployment of corresponding software modules on the existing system, without the need to replace a large number of existing equipment, thus reducing the capital investment in system upgrades and renovations.

[0042] In short, by effectively integrating multiple dynamic optimization mechanisms and applying them to the field of data transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram of a network transmission protocol optimization method based on a distributed soft bus proposed by the present invention;

[0044] Figure 2 This is a schematic diagram of the network transmission protocol optimization system based on the distributed soft bus proposed by the present invention. DETAILED DESCRIPTION

[0045] The present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0046] The present invention provides a network transmission protocol optimization method based on a distributed soft bus. Figure 1 As shown, including:

[0047] Step 1, divide the data to be transmitted into multiple data segments, each data segment is accompanied by a sequence number and a checksum;

[0048] Specifically, it includes: dividing the data segments, firstly dividing the entire data to be transmitted into multiple data segments according to a certain size. The size of the data segment can be preset as a fixed value, or it can be adjusted dynamically according to the network conditions; generating a sequence number, generating a sequence number (SequenceNumber) for each data segment. It usually starts from 0 and increases in sequence. The sequence number is used to identify the transmission order of the data segment, which is convenient for the receiving end to reorder; calculating the checksum, and calculating the checksum (Checksum) for each data segment. Commonly used checksum algorithms include CRC (cyclic redundancy check), addition check, etc. Checksum is used to detect whether the data has been tampered with or bit errors have occurred during the transmission process.

[0049] Step 2, grouping the segmented data, sending the grouped data in sequence, and the receiving party confirming the grouped data and calculating the integrity index; the integrity index is calculated in the following way:

[0050]

[0051] Where, N is the total number of group confirmation packets, D i (T) is the amount of data received by the i-th packet confirmation packet, L i (T) is the packet size corresponding to the i-th packet confirmation packet, and M is the maximum size of the packet; this expression reflects the completeness of data transmission within time T.

[0052] Step 3: According to the partial confirmation or full confirmation sent by the receiver, the packet size is dynamically adjusted, the network quality score is calculated, and an adaptive network environment is realized;

[0053] When the receiver sends a partial confirmation, it means that part of the packet data has been received, and the sender will re-add the unconfirmed packet data to the sending queue.

[0054] By calculating the network quality score, judging partial confirmation and full confirmation, monitoring the network status in real time, and dynamically adjusting the packet size;

[0055]

[0056] Dynamically adjusting the packet size specifically includes: calculating the network quality score C′(T) in real time according to the following expression:

[0057] Where N is the total number of group confirmation packets, D i(T) represents the amount of data received by the i-th packet confirmation packet, and M represents the maximum size of the packet; by dynamically adjusting the packet size, it reflects the average effective transmission rate of the network within time T.

[0058] Step 4: Set different transmission priorities for different types of data, and calculate the priority score to ensure the timely transmission of key data. The transmission priority can be expressed using the calculated priority score R(T) as:

[0059]

[0060] Where N is the total number of packets, C i (T) is the congestion window size of the i-th data packet, Q i is the priority weight of the ith data packet, P i is the payload size of the ith data packet, L i (T) is the amount of data transmitted by the ith packet, and M is the maximum size of a packet; this expression takes into account factors such as congestion control, priority weight, payload size, and amount of data transmitted to calculate the priority score.

[0061] In this solution, the priority management module performs dynamic priority scheduling on the data to be transmitted according to the calculated priority score R(T).

[0062] Data packets with higher R(T) values ​​will be given higher transmission priority, enter the sending queue first and be transmitted;

[0063] Data packets with lower R(T) values ​​wait temporarily and are sent after the high-priority data is transmitted.

[0064] This ensures that critical data is transmitted in a timely and prioritized manner, improving overall transmission efficiency. The network quality score C'(T) reflects the transmission quality and efficiency of the current network. A higher C'(T) value indicates a good network state, which can improve transmission efficiency; a lower C'(T) value indicates a poor network state, and the transmission intensity needs to be reduced to ensure reliability.

[0065] The integrity index I(T) reflects the integrity of data transmission. A higher I(T) value indicates high transmission integrity; a lower I(T) value indicates poor transmission integrity, which may result in packet loss and other problems.

[0066] The priority score R(T) takes into account factors such as congestion control, priority weight, payload size, and transmitted volume, and is used to determine the transmission priority of different data packets.

[0067] The dynamic grouping module can dynamically adjust the grouping size based on the values ​​of C'(T) and I(T):

[0068] When both C'(T) and I(T) are high, increase the packet size to improve efficiency;

[0069] When C'(T) or I(T) is low, the packet size is reduced to ensure reliability.

[0070] The priority management module dynamically schedules the transmission data according to the R(T) value:

[0071] Packets with higher R(T) values ​​enter the sending queue first;

[0072] Packets with lower R(T) values ​​are temporarily waiting to be transmitted.

[0073] Step 5, optimizing the network transmission protocol by using the three parameters of the integrity index, priority score and network quality score, specifically comprising: firstly dynamically adjusting the packet size according to the network quality score C'(T) and the integrity I(T);

[0074] Then, different data packets are prioritized and scheduled according to the priority score R(T);

[0075] By dynamically adjusting the group size and priority, an optimization result is obtained, and an optimization strategy is customized according to the optimization result; wherein the optimization result is calculated by the following expression:

[0076] Optimize(T) = αC′(T) β *I(T) γ *(1+λR(T)) δ ;

[0077] C′(T) β and I(T) γ They respectively represent the degree of nonlinear influence of network quality and integrity on optimization;

[0078] (1+λR(T)) δ Represents the combined linear and nonlinear effects of priorities on optimization;

[0079] α controls the magnitude of the entire expression, 0<α≤1, the larger α is, the larger the Optimize(T) value is; β controls the influence of the network quality score C'(T) on the optimization;

[0080] β represents the influence of the control network quality fraction C'(T) on the optimization.

[0081] When β = 1, the effect of C'(T) is linear;

[0082] When β>1, high values ​​of C'(T) have a greater impact on optimization, while low values ​​have a smaller impact;

[0083] When β<1, high values ​​of C'(T) have less impact on optimization, while low values ​​have a greater impact.

[0084] γ represents the influence of the control transmission integrity score I(T) on the optimization;

[0085] δ represents the degree of nonlinear influence of the control priority score R(T) on the optimization.

[0086] When δ>1, the impact of high-priority data is greater than that of low-priority data;

[0087] When δ<1, the impact of low-priority data is relatively large.

[0088] λ represents the magnitude and relative importance of the control priority score R(T).

[0089] The larger λ is, the greater the impact of R(T) on the optimization; the smaller λ is, the smaller the impact of R(T) is.

[0090] δ controls the nonlinear influence of the priority score R(T) on the optimization

[0091] λ controls the magnitude and relative importance of the priority score R(T),

[0092] Customizing the optimization strategy according to the optimization results specifically includes:

[0093] If the value of the optimization result Optimize(T) is greater than the first threshold, the packet size is increased to improve the transmission efficiency; for example, if Optimize(T) ≥ the first threshold Threshold_High:

[0094] Then increase the packet size and appropriately increase the confirmation cycle;

[0095] Or if the value of the optimization result Optimize(T) is less than the second threshold, the packet size is reduced to improve transmission reliability; wherein, ElseIfOptimize(T)≤the second threshold Threshold_Low:

[0096] Reduce the packet size and confirmation cycle; limit the sending rate of high-priority data

[0097] At the same time, the R(T) value is comprehensively considered to prioritize and schedule data packets.

[0098] This comprehensive expression fully integrates the influence of multiple factors, reflects more dynamics and complexity, and is conducive to more accurate description and implementation of the dynamic optimization process, so as to achieve the goal of comprehensively balancing transmission efficiency, reliability and priority requirements.

[0099] By setting these adjustment coefficients, the relative importance of network quality, transmission integrity and priority requirements to dynamic optimization can be weighed according to different application scenarios. For example:

[0100] For real-time video transmission, β and γ can be appropriately increased to ensure good network quality and integrity;

[0101] For security control data, δ and λ can be improved to ensure the immediate and reliable transmission of high-priority data;

[0102] For normal data transmission, the values ​​of α, β, γ, δ, and λ can be made more balanced.

[0103] The present invention also discloses a network transmission protocol optimization system based on a distributed soft bus, such as Figure 2 As shown, including:

[0104] A data segmentation module, used to divide the data to be transmitted into multiple data segments, each of which is accompanied by a sequence number and a checksum;

[0105] An integrity index calculation module is used to group the segmented data, send the grouped data in sequence, and the receiving party confirms the grouped data and calculates the integrity index;

[0106] A network quality score calculation module is used to dynamically adjust the packet size and calculate the network quality score according to the partial confirmation or full confirmation sent by the receiver to achieve an adaptive network environment;

[0107] The priority score calculation module is used to set different transmission priorities for different types of data. By calculating the priority scores, it ensures the priority and timely transmission of key data.

[0108] The network transmission protocol optimization module is used to optimize the network transmission protocol through the three parameters of the integrity index, priority score and network quality score.

[0109] This solution corresponds one-to-one with the solution in the method embodiment, so it will not be described in detail.

[0110] In summary, the above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0111] It is obvious to those skilled in the art that the embodiments of the present invention are not limited to the details of the above exemplary embodiments, and that the embodiments of the present invention can be implemented in other specific forms without departing from the spirit or basic features of the embodiments of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the embodiments of the present invention is limited by the attached claims rather than the above description, so it is intended to include all changes that fall within the meaning and scope of the equivalent elements of the claims in the embodiments of the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units, modules or devices stated in the system, device or terminal claims can also be implemented by the same unit, module or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0112] Finally, it should be noted that the above implementation modes are only used to illustrate the technical solutions of the embodiments of the present invention and are not intended to limit them. Although the embodiments of the present invention have been described in detail with reference to the above preferred implementation modes, those skilled in the art should understand that the technical solutions of the embodiments of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A network transmission protocol optimization method based on a distributed soft bus, characterized in that: include: Divide the data to be transmitted into multiple data segments, each of which is accompanied by a sequence number and a checksum; The segmented data is grouped and the grouped data is sent in sequence, and the receiving party confirms the grouped data and calculates the integrity index; Dynamically adjust the packet size and calculate the network quality score based on the partial or full confirmation sent by the receiver to achieve an adaptive network environment; Set different transmission priorities for different types of data, and calculate priority scores to ensure timely transmission of critical data; The network transmission protocol is optimized through the three parameters of the integrity index, priority score and network quality score.

2. The network transmission protocol optimization method based on distributed soft bus according to claim 1 is characterized in that: The integrity index is calculated as follows, Where I(T) represents the integrity index, N is the total number of group confirmation packets, and D i (T) is the amount of data received by the i-th packet confirmation packet, L i (T) is the packet size corresponding to the i-th packet confirmation packet, and M is the maximum size of the packet; this expression reflects the completeness of data transmission within time T.

3. The network transmission protocol optimization method based on distributed soft bus according to claim 2 is characterized in that: When the receiver sends a partial confirmation, it means that part of the packet data has been received, and the sender will re-add the unconfirmed packet data to the sending queue.

4. The network transmission protocol optimization method based on distributed soft bus according to claim 3 is characterized in that: The network quality score C′(T) is calculated in real time according to the following expression: Where N is the total number of group confirmation packets, D i (T) represents the amount of data received by the i-th packet confirmation packet, and M represents the maximum size of the packet; the average effective transmission rate of the network within time T is reflected by dynamically adjusting the packet size.

5. The network transmission protocol optimization method based on distributed soft bus according to claim 4 is characterized in that: The transmission priority can be expressed by calculating the priority score R(T) as: Where N is the total number of packets, C i (T) is the congestion window size of the i-th data packet, Q i is the priority weight of the ith data packet, P i is the payload size of the ith data packet, L i (T) is the amount of data transmitted by the ith packet, and M is the maximum size of a packet; this expression takes into account congestion control, priority weight, payload size, and amount of data transmitted to calculate the priority score.

6. The network transmission protocol optimization method based on distributed soft bus according to claim 5 is characterized in that: The network is optimized by using the three parameters of the integrity index, the priority score and the network quality score, specifically including: firstly dynamically adjusting the packet size according to the network quality score C'(T) and the integrity index I(T); then performing priority scheduling on different data packets according to the priority score R(T); obtaining an optimization result by dual dynamic adjustment of the packet size and the priority, and customizing an optimization strategy according to the optimization result; wherein the optimization result is calculated by the following expression: Optimize(T)=αC′(T) β *I(T) γ *(1+λR(T)) δ C′(T) β and I(T) γ They respectively represent the nonlinear influence of network quality and integrity on the optimization result Optimize(T); (1+λR(T)) δ Represents the combined linear and nonlinear effects of priorities on optimization; α controls the magnitude of the entire expression, 0<α≤1, the larger α is, the larger the Optimize(T) value is; β controls the influence of the network quality score C'(T) on the optimization; γ controls the influence of the transmission integrity score I(T) on the optimization; δ controls the nonlinear influence of the priority score R(T) on the optimization; λ controls the magnitude and relative importance of the priority score R(T).

7. The method for optimizing network transmission protocol based on distributed soft bus according to claim 6, characterized in that: Customizing the optimization strategy according to the optimization results specifically includes: If the value of the optimization result Optimize(T) is greater than the first threshold, the packet size is increased to improve the transmission efficiency; or if the value of the optimization result Optimize(T) is less than the second threshold, the packet size is reduced to improve the transmission reliability; At the same time, the priority order of sending the data packets is determined according to the priority score R(T) value.

8. A network transmission protocol optimization system based on a distributed soft bus, comprising: A data segmentation module, used to divide the data to be transmitted into multiple data segments, each of which is accompanied by a sequence number and a checksum; An integrity index calculation module is used to group the segmented data, send the grouped data in sequence, and the receiving party confirms the grouped data and calculates the integrity index; A network quality score calculation module is used to dynamically adjust the packet size and calculate the network quality score according to the partial confirmation or full confirmation sent by the receiver to achieve an adaptive network environment; The priority score calculation module is used to set different transmission priorities for different types of data. By calculating the priority scores, it ensures the priority and timely transmission of key data. The network transmission protocol optimization module is used to optimize the network transmission protocol through the three parameters of the integrity index, priority score and network quality score.

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