Coding transmission service scheduling method and system of satellite terminal

Abstract

The invention discloses a coding transmission service scheduling method and system for a satellite terminal, and the method comprises the steps: taking a repair group as an independent virtual flow, bringing the independent virtual flow into a unified scheduling frame, and deducing a virtual repair flow weight; a WFQ scheduling algorithm is introduced, the virtual completion time of a to-be-scheduled packet is calculated through the weight and the system virtual time, and it is guaranteed that bandwidth allocation of a repair flow is proportional to the weight; a DRR scheduling algorithm is introduced, a round-robin scheduling mode is adopted, a deficit counter is maintained for each stream, approximate proportional fairness is achieved with the complexity of decision time, and the method is suitable for a satellite terminal environment with limited resources. According to the method, the repair packet is taken as the independent virtual stream to be incorporated into the unified scheduling framework, so that the problem of transmission reliability in a long-time-delay and high-packet-loss environment in a non-ground network is effectively solved. The repair flow and each service flow jointly participate in scheduling decision, and the weight of the repair flow is dynamically calculated based on the network packet loss rate, so that the optimal balance between the transmission reliability and the bandwidth efficiency is realized.

Description

Technical Field

[0001] This invention belongs to the field of data transmission optimization of satellite terminals in satellite communication, and particularly relates to a method and system for scheduling encoded transmission services of satellite terminals. Background Technology

[0002] Low-latency packet transmission technology is a key requirement in the current satellite communication terminal field, playing a crucial role in typical satellite application scenarios such as emergency communication, ocean-going vessels, and real-time monitoring. These services place extremely high demands on the data transmission capabilities of satellite terminals, requiring not only stable throughput but, more importantly, stringent low-latency and high-reliability specifications. In a satellite channel environment, the loss of any data packet or transmission timeout can directly lead to the interruption of critical services, severely impacting the service quality and user experience of the satellite communication system.

[0003] However, the traditional TCP / IP network transmission model and its retransmission-dependent error control mechanism face severe challenges in the unique environment of satellite networks, characterized by long propagation delays and high bit error rates. Satellite terminals need to deal with issues such as signal attenuation, atmospheric effects, and intermittent satellite-to-ground links during communication. These factors make it difficult for traditional retransmission-based transmission mechanisms to meet the deterministic quality of service requirements of real-time services.

[0004] To improve the reliability of satellite terminal transmission and reduce end-to-end delivery latency, forward erasure coding (FEC) has become an important solution in satellite communication systems. This technology encodes the original data blocks on the transmitting side of the satellite terminal to generate redundant data packets. The receiving terminal only needs to successfully receive a sufficient number of data packets to recover the original information through decoding, thus effectively adapting to the long latency characteristics of satellite links. However, in multi-service stream transmission scenarios on satellite terminals, the system faces unique scheduling challenges: service streams of different priorities need to share limited satellite link resources, and each service stream has different requirements for latency and reliability; simultaneously, the satellite terminal needs to make precise scheduling decisions between sending original data packets and redundant repair packets, ensuring repair capabilities under adverse channel conditions while fully considering the valuable bandwidth resources of the satellite link.

[0005] Traditional service flow scheduling strategies in satellite terminals, whether based on polling or generalized processor sharing models, mostly employ predefined static scheduling strategies. These methods perform well in relatively stable terrestrial network environments, but their limitations become increasingly apparent in dynamically changing satellite network environments, particularly in satellite terminals using forward erasure coding (FEC). The FEC transmission mechanism in satellite terminals not only alters the characteristics of service flows due to the coding process, but the dynamic fluctuations in satellite link quality also cause the equivalent service rate to constantly change. Static scheduling decisions based on fixed weights are ill-suited to this complex and ever-changing satellite communication environment, failing to achieve adaptive optimal resource allocation among multiple service flows. This has become a key bottleneck restricting the improvement of satellite terminal transmission performance. Summary of the Invention

[0006] Purpose of the Invention: The purpose of this invention is to provide a method and system for scheduling encoded transmission services in satellite terminals. It focuses on designing a controller for multi-service flow scheduling under forward erasure coding transmission to achieve fair and efficient data delivery in satellite communication networks with long latency and high packet loss. By incorporating repair packets as independent virtual flows into a unified scheduling framework, it effectively solves the transmission reliability problem in non-terrestrial networks under long latency and high packet loss environments. Under this framework, the repair flow and various service flows jointly participate in scheduling decisions, and the weight of the repair flow is dynamically calculated based on the network packet loss rate to achieve an optimal balance between transmission reliability and bandwidth efficiency. By employing both WFQ and DRR scheduling algorithms, the system can ensure that the orderly delivery ratio and weight of multiple service flows are strictly matched while adapting to the computational resource constraints of different satellite terminals, providing differentiated quality of service guarantees for various services.

[0007] Technical solution: The present invention provides a method for scheduling encoded transmission services in a satellite terminal, comprising the following steps:

[0008] Step 1: By incorporating repair groups as independent virtual flows into a unified scheduling framework, the weights of the virtual repair flows are derived.

[0009] Step 2: Treat the repair group as the first For each virtual stream, a weighted fair queuing (WFQ) scheduling algorithm is introduced. The virtual completion time of the packets to be scheduled is calculated by weight and system virtual time to ensure that the bandwidth allocation of the repair stream is proportional to the weight.

[0010] Step 3: Introduce the Deficit Round Robin (DRR) scheduling algorithm. It adopts a round-robin scheduling method to maintain a deficit counter for each flow. It achieves approximately proportional fairness with the complexity of decision time, which is suitable for resource-constrained satellite terminal environments.

[0011] Furthermore, in step 1, the unified scheduling framework includes:

[0012] Business Flow: There are n business flows, each flow There is a buffer zone, and groups enter the buffer zone via a Poisson-Pareto burst process;

[0013] Weighting: Each business flow is assigned a weight. This indicates relative importance;

[0014] Scheduler: Selectable per time slot One of the actions.

[0015] Furthermore, step 1 specifically involves: in each time slot, the scheduler has One option: Action From the business flow Take the head packet from the buffer and send it as the source packet; Action Repair packets are generated and sent based on a random linear combination of unacknowledged source packets; the packet loss rate of the link is... That is, each group is based on probability. Loss, propagation delay is Furthermore, the sending end maintains a list of unacknowledged packets, while the receiving end uses an instantaneous Gaussian elimination decoder to detect interruptions in ordered delivery and activate decoding. When the number of packets is repaired... When packets are lost, the lost packets can be recovered; among which, the flow within the time period The proportion of groups that are delivered in an orderly manner is called the ordered delivery proportion. Matching orderly delivery ratio With weight The proportional relationship, that is:

[0016] Derive the first The weights of each virtual repair stream are first set to the proportion of source packets in the total transmitted packets. The repair group ratio is Then we have:

[0017]

[0018] Let the source packet transmission rate be... Repair the packet sending rate to P e If the link packet loss rate is given, then the number of repair packets received by the receiver is... To recover the lost Each source group needs to satisfy:

[0019]

[0020] Right now:

[0021]

[0022] because ,and Substituting, we get:

[0023]

[0024] Solving for:

[0025]

[0026] To ensure sufficient margin, the repair group ratio is required to be relatively high compared to... higher ,Right now Repair the weights corresponding to the grouped flows The proportional relationship with other flows can be expressed as:

[0027]

[0028] The repair flow weights can be obtained:

[0029]

[0030] in It is an additional repair group ratio, and it meets the constraints. .

[0031] Furthermore, step 2 specifically involves the WFQ scheduling algorithm maintaining a virtual completion time for each flow i. Assign weights to business flows Repair flow weight is When the scheduler is ready to schedule a packet for forwarding, the algorithm compares the first group of all queues and selects the packet with the shortest virtual completion time for forwarding; the WFQ algorithm principle is as follows:

[0032] System virtual time initialization and calculation: Initially, the system virtual time is initialized to 0. Each arrival or departure of a group is recorded as an event. When an event occurs, the global virtual time is adjusted. The updated formula is as follows:

[0033]

[0034] In the formula, Indicates the first The moment the event occurred It is expressed as the length of the time interval, and satisfies... ;

[0035] The virtual start time and virtual finish time are initialized and calculated, both of which are initialized to 0. The virtual start time and virtual finish time are calculated based on the system virtual time when the packet arrives, using the following formula:

[0036]

[0037]

[0038] In the formula, S represents the arrival time of the group. i k The virtual start time represents the moment when the group begins to be served on the virtual timeline. The virtual completion time represents the moment when the group completes its service on the virtual timeline.

[0039] In each scheduling slot, the scheduler performs the following: Update virtual time. ; Calculate the virtual completion time of each stream;

[0040] Choose the streaming service with the shortest virtual completion time: If you choose the business stream : Send the head source packet; If repair stream is selected: Generate and send repair packets;

[0041] By selecting the stream with the shortest virtual completion time to provide services, the number of operations required for the algorithm's execution and the input size are determined. The complexity is proportional to the logarithm of the expression, i.e., the time complexity is... The proportion of fairness and time delay protection are guaranteed.

[0042] Furthermore, step 3 specifically involves: In the DRR scheduling algorithm, at the beginning of each round of scheduling, each service flow... A credit supplement constant is assigned. The total amount of current credit maintained by each business flow is called the deficit. This represents the maximum length of data packets that this stream can send, whenever the scheduler polls the non-empty traffic stream queue. When the length of the data packet at the head of the queue is... Not greater than Then send the data packet and minus , until Less than DRR uses a round-robin scheduling method and maintains a deficit counter for each stream, achieving approximately proportional fairness with decision-making time complexity, which is suitable for resource-constrained satellite terminal environments.

[0043] This invention also discloses a satellite terminal encoding transmission service scheduling system, comprising:

[0044] Repair the grouping module: including the business flow module, weight allocation module, and scheduler module;

[0045] The WFQ scheduling algorithm module calculates the virtual completion time of the packets to be scheduled by using weights and system virtual time, ensuring that the bandwidth allocation of the repair stream is proportional to the weights.

[0046] The DRR scheduling algorithm module adopts a round-robin scheduling method and maintains a deficit counter for each flow. It achieves approximately proportional fairness with the complexity of decision time, making it suitable for resource-constrained satellite terminal environments.

[0047] The present invention also discloses a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method of the present invention.

[0048] The present invention also discloses a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implements the steps of the method of the present invention.

[0049] The present invention also discloses a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the method of the present invention.

[0050] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages:

[0051] 1. This invention effectively addresses the transmission reliability issues in non-terrestrial networks under long latency and high packet loss environments by incorporating repair packets as independent virtual flows into a unified scheduling framework. Within this framework, the repair flow and other service flows participate in scheduling decisions, dynamically calculating the repair flow weight based on the network packet loss rate to achieve an optimal balance between transmission reliability and bandwidth efficiency. By employing both WFQ and DRR scheduling algorithms, the system can ensure the orderly delivery ratio and strict weight matching of multiple service flows while adapting to the computational resource constraints of different satellite terminals, providing differentiated quality of service guarantees for various services.

[0052] 2. Significantly improved transmission reliability: The δ parameter in the repair flow weight calculation formula provides the system with an adjustable redundancy protection margin, which can effectively cope with sudden packet loss and channel estimation errors in satellite links, resulting in a significant improvement in decoding success rate. At the same time, the intelligent repair group scheduling mechanism significantly reduces data recovery latency, ensuring stable data transmission performance in non-terrestrial network environments with long latency and high packet loss.

[0053] 3. Strict Quality of Service Guarantee for Multiple Service Flows: By combining different scheduling algorithms suitable for various scenarios, the weighted fair queue-based algorithm provides bounded experimental guarantees, making it particularly suitable for real-time services with extremely high fairness requirements. Meanwhile, the deficit-based round-robin algorithm, while ensuring basic fairness, provides an efficient scheduling solution for terminals with limited computing resources. Both algorithms work together to ensure that service flows of different priorities receive a quality of service commensurate with their importance, achieving true differentiated service assurance.

[0054] 4. Efficient utilization of satellite link resources: The designed scheduler optimizes the configuration of satellite link resources through precise repair flow weight calculation and intelligent scheduling strategies. The repair flow weight achieves the best balance between reliability and bandwidth overhead, avoiding the excessive redundancy problem common in traditional forward erasure coding, and improving effective throughput and link utilization.

[0055] 5. System Practical Value and Scalability: The technical solution of this invention has significant practical value and good scalability. Its parameterized design provides an intuitive means of performance control for system operation and maintenance, the unified scheduling framework design reduces the complexity of system integration, and the modular algorithm selection mechanism facilitates deployment and implementation in different types of satellite terminals. Attached Figure Description

[0056] Figure 1 This is a schematic diagram of a service flow QoS scheduling framework based on virtual repair streams under elastic erasure coding.

[0057] Figure 2 The graph shows the scheduling delay and delivery delay results for the same priority.

[0058] Figure 3 The graph shows the scheduling delay and delivery delay results under different priorities. Detailed Implementation

[0059] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings and specific embodiments. It should be noted that the described examples and technical solutions are only some embodiments of the present invention, and not all embodiments. The following embodiments or drawings are used to illustrate the present invention and are not intended to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] This invention proposes an intelligent FEC service flow scheduling algorithm for non-terrestrial networks, which specifically includes the following steps:

[0061] This invention considers the following: Figure 1The diagram illustrates the architecture of a service flow scheduling system. This architecture assumes there are D service flows in the system, each corresponding to an arrival buffer queue, denoted as [Duplicate]. Data packets in each queue are numbered according to their arrival order, and the packet length is fixed at K bytes. Packets are processed at a rate... Enter the corresponding queue , Waiting for scheduling. To facilitate convenient and scalable deployment of FEC, performance-enhanced proxies are generally used in practical systems. The deployment method does not affect the specific design and analysis of the scheduling algorithm; therefore, this paper assumes that FEC is deployed using PEP. The scheduler, based on a specific scheduling strategy, ... Scheduling interval (i.e., rate) The data packet at the head of each queue is selected as the source packet and enters the FEC encoder queue deployed in PEP form. This invention uses FEC encoding for transmission between the sending and receiving ends, that is, repair packets are inserted at equal intervals in the source packet sequence. The receiving end then performs forward erasure decoding using instantaneous Gaussian elimination based on the received source packets and repair packets, thereby recovering packets that may have been lost during transmission.

[0062] Based on this, such as Figure 1 As shown, this invention examines two key latency indicators: one is scheduling latency (… ), that is, grouping by Arrive at the corresponding queue The waiting time experienced by a device being scheduled into the encoder reflects the timeliness and fairness of the scheduler's processing of each service flow; secondly, the end-to-end delivery delay. This encompasses the entire process of scheduling, sending, transmission, and receiving confirmation, directly determining the final latency performance of the service experience. During this period, This represents the time when the PEP sender completes encoding and sends the packet to the receiver. This indicates the moment when the PEP receiver receives the data packet.

[0063] The arrival model of this invention follows a Poisson-Pareto Burst Process (PPBP). The arrival process of each traffic flow is characterized by the burst interval (following an exponential distribution) and the burst duration (following a Pareto distribution), and its self-similarity is adjusted by the Hurst parameter. Furthermore, dynamic parameters are considered, that is, during transmission, the burst arrival rate Hurst parameter can vary randomly within a specific range to reflect the long-term correlation, burst clustering, and time-varying characteristics of network traffic.

[0064] Based on the above transmission model, the D service flows are assigned different priority weights according to their quality of service requirements. The system utilizes a newly designed scheduler model, treating the repair packet as the (n+1)th virtual service flow. When the scheduling time arrives, the system schedules the packet from the waiting queue of each service flow or selects to send the repair packet into the FEC encoder.

[0065] The scheduler of this invention is based on PEP (Plan-Do-Check-Act), guiding scheduling decisions by selecting the most suitable service flow for each time slot. Its core innovation lies in treating the repair packet as an independent virtual service flow (i.e., the (n+1)th flow) and assigning it a specific weight. This allows it to be integrated into the classic fair scheduling framework (WFQ and DRR).

[0066] The scheduler's decision for each time slot involves selecting one service stream from n business flows and one virtual repair flow to provide service. This is to achieve an effective delivery ratio. With weight Precise matching, weight of virtual repair stream It is a key parameter, and its value is given by the formula. Decision. Among them, For link packet loss rate, This is a redundancy protection factor introduced to address network fluctuations. This weighting ensures that repair packets have sufficient bandwidth resources to quickly recover lost data in channels with high packet loss, thereby fundamentally supporting the fairness of the orderly delivery ratio of each service flow.

[0067] In its implementation, this invention provides two scheduling decision-making mechanisms that incorporate this core idea. One is based on Weighted Fair Queues (WFQ), which maintains a virtual completion time for each flow (including virtual repair flows). The WFQ algorithm selects the stream with the shortest virtual completion time for service within each time slot. The principle of the WFQ algorithm is as follows:

[0068] (1) System virtual time initialization and calculation. Initially, the system virtual time is initialized to 0. Each arrival or departure of a group is treated as an event. When an event occurs, the global virtual time is adjusted. The updated formula is as follows:

[0069]

[0070] In the formula, Indicates the first The time when the event occurred, and .

[0071] (2) Initialization and calculation of virtual start time and virtual finish time. Both are initialized to 0. The virtual start time and virtual finish time are calculated based on the system virtual time when the group arrives. The calculation formula is as follows:

[0072]

[0073]

[0074] In the formula, This represents the arrival time of the group.

[0075] In each scheduling slot, the scheduler executes:

[0076] 1. Update virtual time ;

[0077] 2. Calculate the virtual completion time for each flow: Business Flow : Repair Stream: , ;

[0078] 3. Select the streaming service with the shortest virtual completion time: If you select a business stream... : Send the head source packet; If repair stream is selected: Generate and send repair packets;

[0079] This mechanism, based on virtual time comparison, provides strict proportional fairness and bounded scheduling latency, with a decision time complexity of O(n log n). It is suitable for satellite service scenarios with extremely high requirements for fairness and latency assurance.

[0080] In the DRR scheduling algorithm, at the beginning of each round of scheduling, each service flow... A credit supplement constant is assigned. The total amount of current credit maintained by each business flow is called the deficit. This represents the maximum length of data packets that this stream can send. Whenever the scheduler polls the non-empty traffic stream queue... When the length of the data packet at the head of the queue is... Not greater than Then send the data packet and minus , until Less than DRR uses a round-robin scheduling method to maintain a deficit counter for each flow. The complexity achieves near-proportional fairness, making it suitable for resource-constrained satellite terminal environments. For service flows, source packets can only be sent if the queue is not empty and the deficit is sufficient; for repair flows, repair packets are only generated and sent if there are unacknowledged source packets and the deficit is sufficient. This mechanism, involving only simple arithmetic operations and sequential polling, achieves... It offers extremely low decision-making time complexity, high processing efficiency, and scalability. While providing approximate proportional fairness, it can meet the needs of satellite terminal scenarios with limited computing resources or a large number of service flows. For example... Figure 2 , Figure 3 The presentation compares scheduling latency under the same priority level with different priorities and contrasts it with queue behavior. Under the same priority configuration, the scheduling latency distribution of each flow is relatively similar, demonstrating the weighted proportional fairness characteristic of WFQ in the absence of explicit priority differences. However, under different priority configurations, the latency of high-priority flows (such as Flow 3) is significantly lower than that of low-priority flows, and the latency increases in a stepwise manner as priority decreases. This verifies that WFQ can effectively support differentiated quality of service assurance. Furthermore, the repair flow, as a virtual flow, can obtain stable scheduling opportunities based on preset weights within this scheduling framework. This maintains fairness among multiple service flows while providing a reliable redundant transmission foundation for the forward erasure coding mechanism, enhancing the overall robustness of the system in long-latency, high-packet-loss environments.

Claims

1. A method for scheduling encoded transmission services in a satellite terminal, characterized in that, Includes the following steps: Step 1: By incorporating repair groups as independent virtual flows into a unified scheduling framework, the weights of the virtual repair flows are derived. Step 2: Treat the repair group as the first A virtual stream is introduced, and the weighted fair queue (WFQ) scheduling algorithm is used to calculate the virtual completion time of the group to be scheduled by weight and system virtual time, so as to ensure that the bandwidth allocation of the repair stream is proportional to the weight. Step 3: Introduce the deficit round-robin DRR scheduling algorithm, which adopts a round-robin scheduling method to maintain a deficit counter for each flow. This achieves approximately proportional fairness with the complexity of decision time, making it suitable for resource-constrained satellite terminal environments.

2. The satellite terminal encoding transmission service scheduling method according to claim 1, characterized in that, In step 1, the unified scheduling framework includes: Business flow: exists Each business flow, each flow There is a buffer zone, and groups enter the buffer zone via a Poisson-Pareto burst process; Weighting: Each business flow is assigned a weight. This indicates relative importance; Scheduler: Selectable per time slot One of the actions.

3. The satellite terminal encoding transmission service scheduling method according to claim 1, characterized in that, Step 1 specifically involves: In each time slot, the scheduler has... One option: Action From the business flow Take the head packet from the buffer and send it as the source packet; Action Repair packets are generated and sent based on a random linear combination of unacknowledged source packets; the packet loss rate of the link is... That is, each group is based on probability. Loss, propagation delay is Furthermore, the sending end maintains a list of unacknowledged packets, while the receiving end uses an instantaneous Gaussian elimination decoder to detect interruptions in ordered delivery and activate decoding. When the number of packets is repaired... When packets are lost, the lost packets can be recovered; among which, the flow within the time period The proportion of groups that are delivered in an orderly manner is called the ordered delivery proportion. Matching orderly delivery ratio With weight The proportional relationship, that is: ； Derive the first The weights of each virtual repair stream are first set to the proportion of source packets in the total transmitted packets. The repair group ratio is Then we have: ； Let the source packet transmission rate be... Repair the packet sending rate to P e If the link packet loss rate is given, then the number of repair packets received by the receiver is... ; To recover the lost Each source group needs to satisfy: ； Right now: ； because ,and Substituting, we get: ； Solving for: ； To ensure sufficient margin, the repair group ratio is required to be relatively high compared to... higher ,Right now Repair the weights corresponding to the grouped flows The proportional relationship with other flows can be expressed as: ； The repair flow weights can be obtained: ； in It is an additional repair group ratio, and it meets the constraints. .

4. The satellite terminal encoding transmission service scheduling method according to claim 3, characterized in that, Step 2 specifically involves the WFQ scheduling algorithm maintaining a virtual completion time for each flow i. Assign weights to business flows Repair flow weight is When the scheduler is ready to schedule a packet for forwarding, the algorithm compares the first group of all queues and selects the packet with the shortest virtual completion time for forwarding; the WFQ algorithm principle is as follows: System virtual time initialization and calculation: Initially, the system virtual time is initialized to 0. Each arrival or departure of a group is recorded as an event. When an event occurs, the global virtual time is adjusted. The updated formula is as follows: ； In the formula, Indicates the first The moment the event occurred It is expressed as the length of the time interval, and satisfies... ; The virtual start time and virtual finish time are initialized and calculated, both of which are initialized to 0. The virtual start time and virtual finish time are calculated based on the system virtual time when the packet arrives, using the following formula: ； ； In the formula, S represents the arrival time of the group. i k The virtual start time represents the moment when the group begins to be served on the virtual timeline. The virtual completion time represents the moment when the group completes its service on the virtual timeline; In each scheduling slot, the scheduler performs the following: Update virtual time. ; Calculate the virtual completion time of each stream; Choose the streaming service with the shortest virtual completion time: If you choose the business stream : Send the head source packet; If repair stream is selected: Generate and send repair packets; By selecting the stream with the shortest virtual completion time to provide services, the number of operations required for the algorithm's execution and the input size are determined. The complexity is proportional to the logarithm of the expression, i.e., the time complexity is... The proportion of fairness and time delay protection are guaranteed.

5. The satellite terminal encoding transmission service scheduling method according to claim 1, characterized in that, Step 3 specifically involves: In the DRR scheduling algorithm, at the beginning of each round of scheduling, each service flow... A credit supplement constant is assigned. The total amount of current credit maintained by each business flow is called the deficit. This represents the maximum length of data packets that this stream can send, whenever the scheduler polls the non-empty traffic stream queue. When the length of the data packet at the head of the queue is... Not greater than Then send the data packet and minus , until Less than ; DRR employs a round-robin scheduling method, maintaining a deficit counter for each stream to achieve near-proportional fairness with decision-making time complexity, making it suitable for resource-constrained satellite terminal environments.

6. A satellite terminal coded transmission service scheduling system, used to implement the method of claim 1, characterized in that, include: Repair the grouping module: including the business flow module, weight allocation module, and scheduler module; The WFQ scheduling algorithm module calculates the virtual completion time of the packets to be scheduled by using weights and system virtual time, ensuring that the bandwidth allocation of the repair stream is proportional to the weights. The DRR scheduling algorithm module adopts a round-robin scheduling method and maintains a deficit counter for each flow. It achieves approximately proportional fairness with the complexity of decision time, making it suitable for resource-constrained satellite terminal environments.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method of claim 1.

8. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method of claim 1.

9. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method of claim 1.

Images