36 results about "Congestion control algorithm" patented technology

The embodiment of the invention relates to the technical field of photovoltaic communication testing, and discloses a distributed photovoltaic multi-protocol communication testing method and related equipment, and the method comprises the steps: determining whether to switch a communication protocol or not according to a communication quality parameter and a parameter threshold value based on the interference of a network signal attenuation simulator on a communication signal, the method comprises the following steps: caching communication data based on a multi-level data caching mechanism, detecting communication interruption, continuously transmitting interrupted data based on a congestion control algorithm, identifying data loss through a missing data algorithm, and complementing the data through a complementing algorithm. And generating a test report according to the data recovery rate, the time efficiency index, the resource consumption index, the protocol adaptability index, the protocol switching parameter, the cache parameter, the continuous transmission parameter and the data completion parameter. According to the embodiment of the invention, tests of communication protocol switching, data caching, interruption identification, data continuous transmission, data loss identification and complementation in various weak network environments can be simulated, the test precision is high, and the test effect is good.

The invention provides a satellite communication method and device, computer equipment and a storage medium, the method is applied to a satellite communication system, the satellite communication system comprises user equipment, a first modem, a second modem and a target server, and the method comprises the following steps: responding to a communication connection request of the user equipment to the target server; creating a satellite communication link between the user equipment and the target server through the first modem and the second modem; and performing data transmission control on the satellite communication link based on a dynamic bandwidth delay product window model and a BBRv2 congestion control algorithm. Based on the scheme of the invention, the transmission performance in a high-delay and high-error-code environment is remarkably improved while the transparent proxy of a satellite link is realized.

The embodiment of the present application relates to the technical field of photovoltaic communication test, and discloses a kind of distributed photovoltaic multi-protocol communication test method and related equipment, the method comprises: communication signal interference is simulated based on network signal attenuation simulator, whether communication protocol is switched according to communication quality parameter and parameter threshold value, communication data is cached based on multi-level data caching mechanism, communication interruption is detected, and interrupted data is continued to be transmitted based on congestion control algorithm, data loss is identified by missing data algorithm, data is completed by completion algorithm, and test report is generated according to data recovery rate, time efficiency index, resource consumption index, protocol adaptability index, protocol switching parameter, caching parameter, continuation parameter and data completion parameter.The embodiment of the present application can simulate the test of communication protocol switching, data caching, interruption identification, data continuation, data loss identification and completion under a variety of weak network environments, and has high test precision and good test effect.

The invention provides a communication method and device, and the method comprises the steps: a terminal device can determine the maximum uplink rate and the maximum downlink rate of a current air interface, and notifies a server of the maximum downlink rate, so that after the terminal device and the server establish a communication connection, the maximum uplink rate and the maximum downlink rate of the current air interface can be obtained. The terminal device can send uplink service data to the server according to the maximum uplink rate, and the server can also send downlink service data to the terminal device according to the maximum downlink rate of the terminal device. According to the method, the process that the sending window and the transmission rate are gradually increased through multiple rounds of detection and iteration in the initial stage by a congestion control algorithm used by the terminal equipment and the server can be avoided, so that the transmission delay of uplink service data and downlink service data is reduced, and the communication efficiency between the terminal equipment and the server is improved; and the time for completing the uploading and downloading tasks by the terminal equipment is obviously shortened.

The invention provides a congestion control system and a control method for jointly adjusting a sending rate based on queues and time delays under a wireless local area network, relates to the technical field of congestion control of the wireless local area network, and aims to solve the problems that a traditional congestion control algorithm depends on single signal sensing, is lagged in response, cannot adapt to bottleneck dynamic switching of the wireless local area network, and is low in cost. And the transmission delay and the link throughput are difficult to balance. According to the method, after each round of data transmission, a network card driving queue residual length RQ is obtained, a data packet round trip time RTT is monitored, a congestion scene is cooperatively judged, a congestion window cwnd is dynamically adjusted to optimize the transmission rate, and corresponding formulas or strategies are adopted for adjustment according to scenes. According to the method, the problems of one-sided sensing and response lag of a traditional congestion control algorithm can be solved, a scene is judged through RQ and RTT dual-sensing cooperation, cwnd is dynamically adjusted, time delay is reduced when the network is good, throughput is guaranteed when the network is poor, and the performance is superior to Cubic and BBR.

Example methods and network interface devices for congestion control are described. In one example, a network interface device may include a first processing layer and a second processing layer. The first processing layer may receive an event notification from the second processing layer. In response to determination that congestion control is required based on the event notification, the first processing layer may determine an adjustment to a packet forwarding parameter by applying a congestion control algorithm. The congestion control algorithm may be one of multiple congestion control algorithms that the first processing layer is programmable to apply. The first processing layer may generate and send an instruction to the second processing layer to perform the adjustment. Based on the instruction, the second processing layer may configure a component to control packet forwarding towards a physical network based on the second value of the packet forwarding parameter.

A computer system for managing congestion control of packets includes a processor that implements a network traffic manager including a congestion controller and a socket. The congestion controller determines messages parameters for packets of a plurality of messages and assigns a congestion control algorithm setting to each packet based on the message parameters associated with each packet. The socket includes a buffer with a queue having a plurality of threshold queue positions. The congestion controller determines that a subset of packets exceeds at least a first threshold queue position and selects a congestion control action for each packet in the subset based on the assigned congestion control setting for each respective packet and a position of each respective packet relative to the plurality of threshold queue positions.

The application provides a kind of congestion control method and device of cross-data center RDMA network based on near-end control, comprising: in the transmission of cross-data center network data, when the data packet congestion sent by upstream data center to upstream switch is detected in upstream switch, preset congestion control algorithm is used to generate departure notification message, and upstream data center adjusts sending rate according to departure notification message;In downstream data center, when the data packet congestion sent by downstream switch to downstream data center is detected, preset congestion control algorithm is used to generate arrival notification message, and downstream switch adjusts sending rate according to arrival notification message;In downstream switch, long-distance notification message is generated according to the total amount of data packet completed forwarding periodically, and upstream switch adjusts forwarding rate according to long-distance notification message and preset data packet limit number.The method provided by the application is suitable for cross-data center network, the congestion control loop is short, and the fairness between each flow is guaranteed.

The application discloses a high-precision flow control protocol simulation system and method for large-scale networks, and relates to the field of network operation simulation services.In the system, a user flow control protocol integration module automatically converts a congestion control protocol algorithm or a flow control protocol provided by a user into a BPF program; a congestion control protocol simulation module compiles the BPF program into bytecode capable of being run by a Linux kernel and mounts the bytecode at a hook function.A flow generator generates flow by using the mounted congestion control algorithm or flow control protocol; a data collection and processing module collects and processes the flow of the flow control protocol simulation experiment by using a database; and an experimental network topology management tool generates a network topology and performs a simulation experiment based on the flow generated by the flow generator.The application can reduce simulation overhead, completely and truly reflect complex conditions in an actual network, and thus does not limit the applicability and authenticity of simulation results.

A method of improving the utilization of a data communications link is provided. The method includes sending a request, to a round trip time, RTT, meter (304), requesting a measurement of the base round trip time of a data communications flow. The method includes setting an increase parameter of a congestion control algorithm based on the base round trip time measurement received from the round trip time meter in response to the request.

The invention provides a congestion control selection method and system based on reinforcement learning, and relates to the technical field of network congestion control. The method comprises the following steps: firstly, in an offline preparation state, dividing a network state into a plurality of grades, and matching a candidate congestion control algorithm pool for each network grade; after entering an online running state, collecting currently running network performance data, determining the grade of the currently running network performance data, loading a corresponding candidate congestion control algorithm pool, and monitoring the network dynamic state so as to feed back and adjust a network grade division basis of an offline stage; and a reinforcement learning agent is introduced, the selection of the congestion control algorithm is used as the action of the reinforcement learning agent, the reinforcement learning agent is trained, and the trained reinforcement learning agent is utilized to decide and output the congestion control algorithm. The preparation of the offline stage accelerates the convergence speed of training, can quickly and dynamically switch to the current optimal congestion control algorithm, and ensures the stability and high efficiency of network transmission.

The application provides a multi-objective transmission control method realized by a self-evolution method, fairness is generally defined as whether resource allocation of competitive traffic in a network is equal, but previous transmission control methods only consider equal distribution of bandwidth when multiple flows coexist, and ignore other valuable transmission resources such as stability and responsiveness, the application can make trade-off between transmission performances and maintain fairness between flows; secondly, the application evaluates multi-objective performance influence of a congestion control algorithm at a system level based on system analysis and theoretical reasoning of the network, and proposes a comprehensive mathematical expression; finally, the application introduces an online evolution congestion control solution generation algorithm based on a first-order derivative, effectively navigates a Pareto front of performance of the congestion control algorithm, and realizes trade-off between multi-dimensional performance objectives.

In order to facilitate applying a congestion control algorithm such as DCQCN to long-distance data transmission, this data transmission device for transmitting data to a data reception device comprises: an acquisition unit that acquires information regarding communication latency between the data transmission device and the data reception device; an adjustment unit that, before data is transmitted, adjusts a parameter relating to increasing the transmission rate in the congestion control algorithm, on the basis of the information regarding the communication latency; and a rate control unit that, using the parameter, controls the transmission rate of the data by means of the congestion control algorithm.

The invention discloses a bandwidth prediction method and device, a medium, electronic equipment and a program product. The method applied to a receiving end comprises the following steps: in response to receiving a first data packet sent by a sending end, generating first feature information of a first network in a first time window according to the first data packet and a historical data packet; inputting the first feature information into a bandwidth prediction model to obtain a current bandwidth prediction value; sending the current bandwidth prediction value to a sending end; and the sending end is used for adjusting the sending rate and the size of the congestion window according to the current bandwidth predicted value. The bandwidth prediction work is completed at the receiving end, and the prediction result is fed back to the sending end, so that the dependence on the optimization congestion control algorithm of the sending end is eliminated, and the CDN is ensured to uniformly adopt a standardized congestion control strategy. A bandwidth prediction method based on a bandwidth prediction model is adopted, and the method can quickly adapt to a dynamically changing network environment. In addition, when the network has a problem, the receiving end can automatically and efficiently check the problem, and external dependence is reduced.

The invention relates to a communication method comprising: - determining a congestion ratio for a communication channel based on measured data; - obtaining, for each terminal in a set of terminals (312, 316, 324), a requirement (504) for radio resources related to the communication channel; and - determining, individually for each terminal in the set of terminals, a respective congestion control table (520) based on the determined congestion ratio of the communication channel and further based on the requirement of each respective terminal.

The application discloses a data transmission method in a network, which is applied to a sending device and comprises the following steps: determining a current network state of a network between the sending device and a receiving device; if the current network state indicates that the network is currently normal, calling a first congestion control algorithm in a transmission protocol which supports the normal network to perform network data transmission; and if the current network state indicates that the network is currently a weak network, calling a second congestion control algorithm in the transmission protocol which supports the weak network to perform network data transmission. It can be seen that the application supports the congestion control under the normal network and the weak network simultaneously, and selects a proper congestion control algorithm according to the current network state to perform network data transmission, thereby improving the data transmission performance. The application further discloses a data transmission system and device in a network and a computer readable storage medium, which have the same beneficial effects as the data transmission method.

An improved method of performing congestion control on a network device is disclosed. The network device establishes a plurality of connections with two nodes. After receiving a data packet from a first node, the network device transmits data to a second node through the plurality of connections according to an outbound traffic policy. When network congestion reaches a certain threshold, the network device may establish multiple new connections with the second node, assigning different congestion control algorithms to them, and replacing multiple connections previously established between the network device and the second node.

This invention relates to the field of flow control or congestion control, and more particularly to a virtualized data center network transmission strategy, including the DCTCP protocol in vSwitch and a priority-based dynamic and static bandwidth allocation strategy. The DCTCP protocol in vSwitch is used to determine the support for ECN by the virtual machines at the sending and receiving ends. Data packets are sent by the sending virtual machine, and upon arrival at vSwitch, the packets are forcibly set to ECN_Capable, achieving unified and flexible configuration of the congestion control algorithm without affecting user virtual machines. Users with administrator privileges or high-quality service policies are classified as core users, and those without are classified as ordinary users. Static priority schemes and dynamic priority schemes are used respectively. The static priority scheme improves the service quality of core users while reducing the impact of competition for ordinary users. The dynamic priority scheme allows the network itself to adjust the sending window according to priority, effectively improving data center throughput, service quality, and fairness.

Systems and methods are provided for implementing enhanced Low Latency, Low Loss, and Scalable throughput (L4S) mechanisms at a bottleneck network node to detect and more accurately / selectively address congestion. Low and high watermark limits can be established for access category (AC) queues at the bottleneck network node, such as an access point (AP). Incoming packets can be analyzed to determine their priority, and then assigned to an AC queue. Depending on the state of a queue (whose thresholds can differ) packets can be marked or not marked with a “congestion experienced” (CE) indication. Additionally, if a congestion indication is received by an AP from a receiver application, but the congestion no longer exists, the AP can forgo forwarding this feedback upstream.

The invention relates to the technical field of communication, and provides a user-defined RDMA (Remote Direct Memory Access) congestion control simulation method, which comprises the following steps that: a host side request end initializes related congestion control parameters; the host side request end sends a data packet according to the current congestion control algorithm; the switch side forwards the data packet, and executes ECN marking or INT information insertion according to a congestion control algorithm; after receiving the data packet, the host side response end generates feedback information according to the network state; and the host side finishing end analyzes the feedback information, calls a corresponding congestion control algorithm to process logic, and executes rate adjustment. According to the method, a user can flexibly realize and deploy a self-defined congestion control mechanism, and function verification and performance evaluation are carried out on an algorithm in a simulation environment.

The application provides a user state-based RDMA network QoS coordination method, which comprises the following steps: a sending end configures different QoS initial parameters for different service flows, and sends data packets with the same sending window size; a receiving end carries a network congestion control signal in an ACK packet returned after receiving the packet; the sending end acquires the network congestion control signal; the sending end adjusts the sending window by using a user state congestion control algorithm; the sending end periodically reports QoS parameters and service quality of the service flow to a correction node; and the correction node adjusts the QoS parameters by using a parameter adjustment algorithm according to the QoS parameters and service quality of the service flow reported by the sending end, and delivers the QoS parameters to the sending end. The application performs fine-grained control on a single service flow, so that more priority levels are realized, and the correction module can recover the pre-set QoS as soon as possible, so that good fairness, convergence and stability are achieved.

The application provides a network load tester for evaluating congestion control deployment effect, and relates to the field of network data monitoring or testing. The network load tester is realized by cooperation of FPGA and programmable switch. The FPGA network card is responsible for calculation of the congestion control algorithm, generates a scheduling message, and controls the programmable switch to generate a data message. The programmable switch accepts an acknowledgement message, generates a feedback message after processing, and sends the feedback message to the FPGA, so that processing and generation of a predetermined scale of flow are realized. The application simultaneously plays the high-density advantage of the programmable switch and the high processing capacity of the FPGA, amplifies the processing capacity of the FPGA through the programmable switch, and realizes low-cost Tbps-level high-density load testing. The application proposes a new three-stage rate and burst control design on the programmable switch, realizes high-precision rate burst control, and realizes high-precision real-time measurement without additional message headers.

The invention discloses an Internet of Vehicles distributed network congestion control method and system using a double-layer deep reinforcement learning architecture, and relates to the field of wireless distributed multi-node communication. The method solves the problem of insufficient adaptability of a distributed congestion control algorithm in an existing cellular Internet of Vehicles network in a dynamic environment, and comprises the following steps: analyzing a target communication system, and determining an optimal transmission parameter by controlling a data packet transmission interval and sending power so as to maximize the average data packet transmissibility of vehicle user equipment; the method comprises the following steps: constructing a problem model, setting constraint conditions, carrying out multi-parameter joint regulation and control, dividing an action domain into a plurality of sub-action domains based on a deep Q network, and selecting corresponding sub-action domains for output in different environments to realize dynamic adjustment of communication parameters; and constructing a double-layer deep reinforcement learning architecture model, and performing parameter optimization by using the double-layer deep reinforcement learning architecture model. The method is also suitable for the application fields of distributed congestion control and the like in a cellular Internet of Vehicles network.

The application discloses a data transmission method and related device, determines a congestion control algorithm and a congestion control parameter, obtains a next packet sending opportunity from a congestion control module, the next packet sending opportunity is determined by the congestion control module according to current network packet status by using the congestion control algorithm and the congestion control parameter, and the receiving end sends a packet when the write operation base class waits to meet the next packet sending opportunity, and the write operation base class receives an ACK packet returned by the receiving end, and the existing congestion state information of the congestion control module is updated based on the ACK packet. The application perceives the network state in real time through the congestion control module, and determines the next packet sending opportunity of the write operation base class according to the current network packet status, effectively avoids that the write operation base class sends a packet when the network is congested, improves the data transmission efficiency, and guarantees the reliability of data transmission through the receiving end sending the ACK packet.

The invention discloses an improved optimization method of an end-network cooperative congestion control algorithm based on in-band network telemetering, which relates to the technical field of computer networks, and comprises the following steps: S1, initializing a sending end; s2, switch processing, S3, receiving end feedback and S4, end-network cooperative closed-loop control: the sending end updates a transmission strategy according to a credit quota fed back by the receiving end, the switch adjusts an INT sampling and data packet processing mode according to a network load, and the receiving end continuously optimizes credit distribution based on INT information to form an end-network cooperative congestion control closed loop; through closed-loop linkage of the sending end, the switch and the receiving end, on the basis of network path state information collected in real time through in-band network telemetering, a bottleneck link can be accurately recognized, credit quota and a transmission strategy can be dynamically adjusted, efficient congestion control can still be kept in a high-bandwidth delay product scene, and the congestion control efficiency is improved. And the requirements of a data center network on high throughput and low delay communication can be met.

This invention provides a host-based congestion control method and apparatus based on RDMA. The method is executed at the sending end of a remote direct memory access network. The sending end obtains the host-based traffic congestion signal transmitted by the receiving end in a timely manner through periodic probe packets and return probe acknowledgment packets. The current receiving end delay is obtained through the timestamps of the periodic probe packets and return probe acknowledgment packets. The current receiving end receiving rate is calculated based on the current receiving end delay, the previous receiving end delay, the target delay, and the previous receiving end receiving rate. The current receiving rate is compared with the alternative sending rate calculated based on a preset congestion control algorithm to obtain the target sending rate that needs to be adjusted under the current congestion situation. At the same time, the host-based traffic congestion signal is also used to instruct the receiving end to reduce the available memory bandwidth of the CPU and allocate the remaining available bandwidth to the network card through a bandwidth allocation tool. This timely and effective method can achieve host-based congestion control while avoiding waste of available bandwidth.

The invention provides a congestion control system and a control method for jointly adjusting a sending rate based on an intelligent queue-time delay under a wireless local area network, relates to the technical field of congestion control of the wireless local area network, and aims to solve the problems that a traditional congestion control algorithm depends on single signal sensing, is lagged in response, cannot adapt to bottleneck dynamic switching of the wireless local area network, and is low in cost. And the transmission delay and the link throughput are difficult to balance. According to the method, after each round of data transmission, a network card driving queue residual length RQ is obtained, a data packet round trip time RTT is monitored, a congestion scene is cooperatively judged, a congestion window cwnd is dynamically adjusted to optimize the transmission rate, and corresponding formulas or strategies are adopted for adjustment according to scenes. According to the method, the problems of one-sided sensing and response lag of a traditional congestion control algorithm can be solved, a scene is judged through RQ and RTT dual-sensing cooperation, cwnd is dynamically adjusted, time delay is reduced when the network is good, throughput is guaranteed when the network is poor, and the performance is superior to Cubic and BBR.

Example methods and network interface devices for user-defined congestion control are described. In one example, a network interface device may include a first processing layer and a second processing layer. The first processing layer may receive an event notification from the second processing layer. In response to determining that congestion control is required based on the event notification, the first processing layer may determine adjustments to packet forwarding parameters by applying a congestion control algorithm. The congestion control algorithm may be one of a plurality of congestion control algorithms that the first processing layer is programmable to apply. The first processing layer may generate and send instructions to perform the adjustment to the second processing layer. Based on the instruction, the second processing layer may configure a component to control packet forwarding to a physical network based on the second value of the packet forwarding parameter.

The application provides a round-trip delay correction method and system based on reverse path timestamp, comprising: collecting data packet sending timestamp, acknowledgement packet sending timestamp and acknowledgement packet receiving timestamp; storing reverse path delay samples dynamically through a sliding window, and calculating a reference delay by selecting a minimum value method or a least square regression method according to the sample quantity; removing reverse path congestion interference in the round-trip delay according to the difference between the current reverse path delay and the reference delay, and obtaining a corrected round-trip delay; and sharing the reference delay of the same source-destination pair under a symmetric topology. The application can accurately separate forward and reverse path congestion, avoid misjudgment of the traditional RTT caused by reverse path congestion, and improve the bandwidth utilization and short flow performance of the congestion control algorithm; through hardware timestamp and dynamic baseline estimation, low-cost deployment without hardware modification is realized, and the application is suitable for high-precision delay optimization of a data center network.

The application discloses a system and method for realizing bandwidth allocation based on AIMD, and the method comprises the following steps: establishing a fluid model in a fluid model module according to the link queue type in a network; determining the congestion window proportion of all flows of the fluid model by a higher controller according to the current link queue type and the bandwidth occupation proportion to which all flows controlled by the controller are expected to converge, and then obtaining the weight parameter proportion of all flows; setting the weight parameters of all flows according to the weight parameter proportion of all flows, allocating the weight parameters to the congestion control algorithm of the corresponding flow, and starting the transmission of the corresponding flow; and adjusting the congestion window of the transmission by running the AI module or MD module of the congestion control algorithm according to the feedback given by the system outside. The application can effectively provide precise bandwidth allocation for multiple flows according to the weight, avoid modification of the link switch device, and adapt to the current network link situation with a deep buffer queue.