Remote management device based on computer terminal control

Abstract

The invention relates to the technical field of remote management, and discloses a remote management device based on computer terminal control, which comprises a computer terminal, a communication network, a remote management device and a data optimization module, and is characterized in that the data optimization module is used for performing dynamic modeling, path optimization, bandwidth allocation and data scheduling based on a network state; low-delay and high-stability communication between the computer terminal and the remote management device is realized; the data optimization module comprises a network modeling unit which is used for collecting real-time state information of a communication network and establishing a dynamic model for nodes and links of the communication network. The technical scheme based on dynamic network modeling and real-time path optimization is adopted, the optimal communication path from the computer terminal to the remote management device can be quickly calculated in a complex network environment, and the technical effects of remarkably reducing communication delay and improving transmission stability are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of remote management, in particular to a remote management device based on computer terminal control. Background Art

[0002] Currently, remote management devices are widely used in industrial control, smart home, Internet of Things and other fields to achieve remote monitoring and management of equipment. Sending control instructions through computer terminals, remote devices executing corresponding operations and feedback on equipment status have become a key component of modern intelligent systems. In this system architecture, the real-time and reliability of communication directly affect the performance of the entire system and user experience. However, due to the complexity of the communication network and its dynamic characteristics, the performance optimization of remote management devices faces many challenges.

[0003] In the prior art, most remote management devices implement data transmission based on static path selection or preset communication parameters. In this solution, a fixed communication path is usually used, and the bandwidth resource allocation and task scheduling strategy are set when the system is initialized, without considering the real-time changes in the network. For application scenarios with high real-time and low latency requirements, such as industrial equipment control or emergency remote response, existing solutions are difficult to adapt to sudden delay fluctuations, insufficient bandwidth or link interruption problems in complex network environments. In addition, in order to reduce the packet loss rate, the prior art sometimes adopts redundant data transmission, which further increases the communication burden and wastes resources.

[0004] However, the main problem with the existing technology is that it cannot cope with communication delays and uneven resource allocation in a dynamic network environment in real time. Since the fixed path selection strategy cannot adapt to the rapid changes in network status, the remote management device of the existing technology is prone to performance degradation such as excessive delay and increased packet loss rate in scenarios of network fluctuations, link congestion or resource competition, resulting in untimely remote control response or delayed feedback information, which seriously affects the stability and reliability of the system. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides a remote management device based on computer terminal control, which solves the problems of excessive communication delay and uneven resource allocation caused by rapid changes in network status in the prior art.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a remote management device based on computer terminal control, comprising a computer terminal, a communication network, a remote management device and a data optimization module, wherein the data optimization module is used to realize low-latency and high-stability communication between the computer terminal and the remote management device based on network status dynamic modeling, path optimization, bandwidth allocation and data scheduling; the data optimization module comprises: A network modeling unit, used to collect real-time status information of the communication network and establish a dynamic model for nodes and links of the communication network; A path optimization unit, used for selecting a communication path with optimal delay and packet loss rate according to a dynamic model generated by a network modeling unit; A bandwidth allocation unit, used to optimize the allocation of bandwidth resources on the path; The data scheduling unit is used to dynamically queue and schedule transmission tasks according to the data type priority.

[0007] Preferably, the communication network status information collected by the network modeling unit includes link delay, link packet loss rate and link bandwidth, and the dynamic model describes the network status through a node set and a link set, wherein the node set includes a computer terminal, a relay device and a remote management device, and the attributes of the link set are the delay, packet loss rate and bandwidth collected in real time.

[0008] Preferably, the path optimization unit determines the optimal communication path from the computer terminal to the remote management device based on the variational method, and the path optimization goal is to minimize the weighted sum of transmission delay and packet loss rate and meet the dynamic change requirements of the optimized path.

[0009] Preferably, the path optimization unit selects the optimal path according to the following optimization objectives: The weighted value of total delay and packet loss rate is the smallest; During the optimization process, the status of the path is updated according to the dynamic network model; Combined with the dynamic delay and packet loss rate of path nodes, numerical iteration is performed to solve the optimal path.

[0010] Preferably, the bandwidth allocation unit allocates link bandwidth using a dynamic game model, wherein: Each node chooses a bandwidth allocation strategy to maximize its communication performance; The bandwidth allocation target comprehensively considers the throughput, delay and packet loss rate of the path, obtains the Nash equilibrium point through iterative calculation, and determines the optimal allocation strategy.

[0011] Preferably, the bandwidth allocation unit monitors bandwidth changes on the link in real time, dynamically adjusts the node allocation strategy based on the monitoring results, and realizes efficient utilization of bandwidth resources through a feedback mechanism.

[0012] Preferably, the data scheduling unit queues and schedules data packets according to the priority of the data type, wherein: High-priority tasks include real-time control instructions; Low-priority tasks include status feedback data; The packet queuing process achieves low-latency transmission of high-priority tasks by dynamically adjusting priority weights.

[0013] Preferably, the data scheduling unit optimizes queuing performance according to queuing theory to reduce data packet delays of high priority tasks, and the queuing optimization is achieved by adjusting the data packet arrival rate and service rate, wherein the average delay of the queue is determined by the difference between the service rate and the arrival rate.

[0014] Preferably, the data optimization module dynamically adjusts the optimization strategy of each unit through a feedback mechanism, wherein: The network modeling unit updates the network status in real time; The path optimization unit recalculates the optimal path according to the new network status; The bandwidth allocation unit adjusts the node bandwidth allocation strategy through feedback; The data scheduling unit adjusts the priority weights in real time according to the queue load and task delay.

[0015] Preferably, the data optimization module uses the Markov decision process as an optimization framework in a dynamic network environment, defines network status, action and reward function, and obtains the global optimal strategy of the communication system through real-time optimization, wherein: Network status includes link delay, packet loss rate, and bandwidth; The actions are path selection, bandwidth allocation, and data scheduling; The reward function is defined based on the weighted values ​​of delay and packet loss rate.

[0016] The present invention provides a remote management device based on computer terminal control, which has the following beneficial effects: 1. The present invention adopts a technical solution based on dynamic network modeling and real-time path optimization, which can quickly calculate the optimal communication path from the computer terminal to the remote management device in a complex network environment, achieving the technical effect of significantly reducing communication delay and improving transmission stability. Compared with the problem that the single fixed path selection method in the prior art cannot cope with network fluctuations, it solves the shortcomings of inflexible path selection and the inability to dynamically optimize delay and packet loss rate.

[0017] 2. The present invention allocates path bandwidth by introducing a dynamic game model, fully considering the communication resource usage of each path node, and realizing efficient utilization and dynamic adjustment of bandwidth resources. Compared with the technical solutions in the prior art where the bandwidth allocation strategy is fixed or cannot dynamically respond to network changes, the present invention solves the problems of uneven resource allocation and low communication throughput, while effectively reducing the congestion risk of high-load links.

[0018] 3. The present invention uses a data scheduling module to dynamically prioritize and schedule data packets, ensuring that high-priority tasks are transmitted with lower delays, thus achieving the technical effect of significantly improving the system response speed. The prior art lacks dynamic management of data priorities, which often causes high-priority tasks to be delayed or compete with ordinary tasks for resources. The present invention solves the problem of unstable delays in traditional scheduling methods in a multi-task environment.

[0019] 4. The present invention adopts a feedback mechanism throughout the entire process of data collection, performance evaluation and optimization adjustment, constructs a dynamic closed-loop optimization process, and achieves rapid adaptation to network fluctuations and environmental changes. Compared with the solutions in the prior art that rely on static parameter settings or manual intervention, the present invention solves the problem of optimization results being invalid due to lack of dynamic adjustment, and further improves the robustness and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the remote management device of the present invention; Figure 2 It is a workflow diagram of the network modeling unit of the present invention; Figure 3 It is a schematic diagram of a path optimization unit of the present invention; Figure 4 It is a schematic diagram of the bandwidth allocation unit game model of the present invention; Figure 5 A schematic diagram of a priority queue of a data scheduling unit of the present invention; Figure 6 Schematic diagram of the feedback mechanism of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Please see attached Figure 1-6 The embodiment of the present invention provides a remote management device based on computer terminal control, which mainly adopts a technical solution of collaborative operation of modules such as dynamic network modeling, path optimization, bandwidth allocation, data scheduling and feedback mechanism.

[0023] First, the device framework of the present invention includes a computer terminal, a communication network, a remote management device and a data optimization module. The computer terminal is used to send control instructions to the remote management device and receive status feedback from the device; the communication network provides a data transmission path, and its dynamic characteristics (such as delay, packet loss rate and bandwidth) may have a significant impact on communication efficiency; the remote management device responds to the terminal's instructions to perform specific tasks; the data optimization module realizes dynamic adjustment of the communication path, resource allocation and data transmission scheduling by real-time monitoring and optimizing the network status.

[0024] The functions of the data optimization module include: dynamic modeling of network status, selection of optimal communication path, reasonable allocation of bandwidth resources, and priority scheduling of data packets.

[0025] 1. Network Modeling Network modeling collects dynamic status information of the communication network in real time through the network modeling unit to establish a topological model of nodes and links.

[0026] In this embodiment, the network modeling unit dynamically models the communication network, which is defined as follows: In this embodiment, the network modeling unit dynamically models the communication network, which is defined as follows: The communication network is represented as a weighted directed graph Among them, the node set Including computer terminals, relay equipment and remote management devices, link collection It includes the communication paths connecting the nodes. The dynamic properties of the link include the following parameters: Link Delay , in milliseconds, indicating the data from the node To Node The transmission time of change.

[0027] Link packet loss rate , in percentage, indicating the number of packets on the link The loss probability also changes dynamically over time.

[0028] Link bandwidth , in Mbps, represents the maximum data transmission rate on the link.

[0029] Generally, the network modeling unit monitors the above dynamic parameters of the link through periodic sampling. As an option, the link attributes can be weighted averaged using a sliding window method to smooth out fluctuations in a short period of time. This modeling method can accurately reflect the real-time status of the network while reducing the demand on system resources.

[0030] Specifically, in some embodiments, network modeling also supports topology updates between multiple nodes. For example, when a relay node fails, the model will promptly remove the links related to the node and recalculate the topology structure.

[0031] Through the above modeling method, the dynamic state of the communication network can be It is fully described in the document, providing a reliable basis for subsequent path selection and bandwidth allocation.

[0032] 2. Path Optimization The role of the path optimization unit is to calculate the optimal communication path from the computer terminal to the remote management device in real time based on the modeled network status information. In a dynamic network environment, the path optimization aims to minimize the total delay and packet loss rate. In this embodiment, the objective function of the path optimization is defined as:

[0033] in: : The communication path from the starting node to the target node.

[0034] : Node on the path Dynamic delay.

[0035] : Node on the path Dynamic packet loss rate.

[0036] : Weight factors for delay and packet loss rate, set by user requirements.

[0037] The start and end time of the data transmission.

[0038] Specifically, the present invention solves the above path optimization problem by using the calculus of variations. Based on the optimization principle of the calculus of variations, the optimal path The following Euler-Lagrange equations must be satisfied:

[0039] in .

[0040] In some embodiments, path optimization also incorporates link bandwidth constraints, that is, only the bandwidth Links above a certain threshold to avoid transmission congestion caused by low-bandwidth paths.

[0041] The solution of path optimization can be solved by numerical iteration method. As an implementation method, the computer terminal regularly updates the path optimization result, and if it is found that the delay or packet loss rate of the current path exceeds the set threshold, the optimal path is recalculated.

[0042] 3. Bandwidth allocation Based on the path optimization, the bandwidth allocation unit is responsible for allocating resources on the path. Since there may be resource competition between paths, a reasonable allocation strategy needs to be adopted. In this embodiment, the participants are nodes on the path, and the bandwidth resources are the allocation objects of the game. The node's profit function is defined as:

[0043] in: :node Bandwidth allocation strategy.

[0044] : The strategy set of other nodes.

[0045] : are the weights of throughput, delay and packet loss rate respectively.

[0046] As an alternative, the goal of bandwidth allocation is to maximize data throughput while minimizing latency. Specifically, the Nash equilibrium point is gradually solved through an iterative game method. .

[0047] 4. Data Scheduling The data scheduling unit is responsible for queuing and scheduling data packets according to task priorities. The present invention adopts a dynamic priority queue model to achieve low-delay processing of high-priority tasks. In this embodiment, data packets are divided into two categories according to type: High priority tasks, including real-time control instructions, have a weight of ; Low priority tasks, including status feedback data, have a weight of .

[0048] In general, the data scheduling unit dynamically adjusts the arrival rate and service rate of data packets to reduce queuing delay. The average delay of the queue is determined by the following formula:

[0049] in: Service rate.

[0050] : Arrival rate.

[0051] As a possible implementation method, when the queue is congested, the data scheduling unit gives priority to high-priority tasks and implements flow control on low-priority tasks to ensure that system performance is not affected.

[0052] 5. Feedback Mechanism The feedback mechanism is one of the key technical features of the present invention, and its role runs through each module of network modeling, path optimization, bandwidth allocation and data scheduling. Through real-time monitoring and dynamic adjustment, the feedback mechanism ensures efficient communication and stable operation of the remote management device in a complex network environment. The implementation details of the feedback mechanism will be described in detail below.

[0053] The feedback mechanism of the present invention is based on periodic collection and real-time response, acting on each module of the communication process. Dynamically obtain the latest changes in network status, such as link delay, packet loss rate and bandwidth; Continuously evaluate the optimization results to ensure that the operation of each module meets the target performance; When anomalies or performance degradation are detected, the adjustment mechanism is triggered in a timely manner to update the optimization strategy.

[0054] The feedback mechanism is completed through the following steps: Data collection and modeling: real-time monitoring of communication network status changes; Performance evaluation: judge the current optimization results based on the collected data; Adjustment and update: Adjust path selection, bandwidth allocation, and data scheduling strategies based on the evaluation results.

[0055] 5.1 Data Collection and Modeling The first step of the feedback mechanism is to collect the dynamic status information of the communication network in real time. This is done through the network modeling unit, including the following: Periodically monitor the link's latency, packet loss, and bandwidth properties; The update frequency of the collected data is set according to the dynamic degree of the network. For example, a rapidly changing network may require a higher sampling frequency. The data are processed using a sliding window method to remove short-term noise and smooth long-term trend changes.

[0056] For example, in a communication link If the delay If there is an abnormal fluctuation within a sampling period, the information will be recorded and used as input data for performance evaluation. In some embodiments, data collection is also combined with an event trigger mechanism. For example, when the packet loss rate When the set threshold is exceeded, the modeling unit is immediately triggered to recalculate the global network state.

[0057] 5.2 Performance Evaluation The collected network status data will be transmitted to the performance evaluation unit to determine whether the current communication optimization results meet the target performance.

[0058] The performance evaluation process includes the following: Evaluation of path optimization results: Calculate the total delay and packet loss rate of the current path based on the real-time network status; If the path performance index exceeds the set tolerance range (for example, the delay is greater than 100 ms, or the packet loss rate is higher than 5%), the path optimization is considered to have failed.

[0059] Evaluation of bandwidth allocation strategies: Check whether the bandwidth utilization of each path is balanced; If the bandwidth utilization of a link is less than 30%, or the bandwidth overload exceeds 90%, bandwidth allocation adjustment is triggered.

[0060] Evaluation of data scheduling performance: Check if the average latency of high-priority tasks in the queue is within the target range; If the average delay of high-priority tasks exceeds the set threshold, scheduling adjustment is triggered.

[0061] In a possible implementation, the performance evaluation unit uses a dynamic weight factor to weight the indicator. For example, when the system task is mainly real-time, the weight factor of delay will be increased. , thereby prioritizing the impact of latency metrics 5.4 Adjustment and Update Based on the results of the performance evaluation, the feedback mechanism triggers the adjustment operations of the corresponding modules, including path selection, bandwidth allocation, and data scheduling. The core content of the adjustment mechanism is as follows: 1. Path optimization adjustment If the performance evaluation unit determines that the current path does not meet the target performance, the optimal path is recalculated.

[0062] In a link When severe congestion occurs (e.g., delay exceeds the tolerance range), the path optimization unit will remove the link and rerun the optimization algorithm; The selection of the new path takes into account the comprehensive weights of latency, packet loss rate, and bandwidth to ensure that the adjusted path can meet communication needs.

[0063] 2. Bandwidth Allocation Adjustment If the evaluation results show that the bandwidth allocation of a certain path is uneven or the utilization is unreasonable, the feedback mechanism will readjust the bandwidth allocation strategy.

[0064] Specifically, the participants (path nodes) of the dynamic game model will update their bandwidth allocation strategies until the payoff function reaches a new equilibrium state; For example, if the bandwidth utilization of a link is lower than 30%, more bandwidth resources will be allocated to the link to improve data throughput.

[0065] 3. Data scheduling adjustment If the scheduling performance does not meet the standard, the priority weight will be reallocated.

[0066] In one possible implementation, the weight of high-priority tasks will be appropriately increased to reduce their queuing delay; At the same time, by adjusting the flow control parameters of low-priority tasks, their occupancy of the queue can be reduced.

[0067] 5.5 Closed-loop Optimization of Feedback Mechanism The feedback mechanism forms a closed-loop optimization process between the above modules. Specifically: Real-time data collection from the network modeling unit provides basic data for performance evaluation; The performance evaluation unit continuously monitors the optimization results and transmits the adjustment requirements to the corresponding modules; The adjustment operations of each module will affect the network status again, triggering a new round of collection and evaluation.

[0068] The characteristics of this closed-loop optimization are: Can dynamically adapt to changes in the network environment, such as quickly responding to network jitter and link interruption; The optimization results will gradually approach the global optimum as the feedback mechanism operates.

[0069] In some embodiments, the feedback mechanism also supports the following extended functions: Multi-link switching: When the performance of a single link is insufficient, the feedback mechanism can enable multiple communication paths at the same time to achieve parallel data transmission; Long-term trend analysis: Through long-term recording of collected data, the feedback mechanism can predict the changing trend of network performance and adjust the optimization strategy in advance.

[0070] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A remote management device based on computer terminal control, comprising a computer terminal, a communication network, a remote management device and a data optimization module, characterized in that: The data optimization module is used to achieve low-latency and high-stability communication between the computer terminal and the remote management device based on dynamic network status modeling, path optimization, bandwidth allocation and data scheduling; The data optimization module includes: A network modeling unit, used to collect real-time status information of the communication network and establish a dynamic model for the nodes and links of the communication network; A path optimization unit, used for selecting a communication path with optimal delay and packet loss rate according to a dynamic model generated by a network modeling unit; A bandwidth allocation unit, used to optimize the allocation of bandwidth resources on the path; The data scheduling unit is used to dynamically queue and schedule transmission tasks according to the data type priority.

2. A remote management device based on computer terminal control according to claim 1, characterized in that: The communication network status information collected by the network modeling unit includes link delay, link packet loss rate and link bandwidth. The dynamic model describes the network status through a node set and a link set, wherein the node set includes a computer terminal, a relay device and a remote management device, and the attributes of the link set are the delay, packet loss rate and bandwidth collected in real time.

3. A remote management device based on computer terminal control according to claim 1, characterized in that: The path optimization unit determines the optimal communication path from the computer terminal to the remote management device based on the variational method. The path optimization goal is to minimize the weighted sum of transmission delay and packet loss rate and meet the dynamic change requirements of the optimized path.

4. A remote management device based on computer terminal control according to claim 1, characterized in that: The path optimization unit selects the optimal path according to the following optimization objectives: The weighted value of total delay and packet loss rate is the smallest; During the optimization process, the status of the path is updated according to the dynamic network model; Combined with the dynamic delay and packet loss rate of path nodes, numerical iteration is performed to solve the optimal path.

5. A remote management device based on computer terminal control according to claim 1, characterized in that: The bandwidth allocation unit allocates link bandwidth using a dynamic game model, wherein: Each node chooses a bandwidth allocation strategy to maximize its communication performance; The bandwidth allocation target comprehensively considers the throughput, delay and packet loss rate of the path, obtains the Nash equilibrium point through iterative calculation, and determines the optimal allocation strategy.

6. A remote management device based on computer terminal control according to claim 1, characterized in that: The bandwidth allocation unit monitors bandwidth changes on the link in real time, dynamically adjusts the node allocation strategy based on the monitoring results, and realizes efficient utilization of bandwidth resources through a feedback mechanism.

7. A remote management device based on computer terminal control according to claim 1, characterized in that: The data scheduling unit queues and schedules data packets according to the priority of the data type, wherein: High-priority tasks include real-time control instructions; Low-priority tasks include status feedback data; The packet queuing process achieves low-latency transmission of high-priority tasks by dynamically adjusting priority weights.

8. A remote management device based on computer terminal control according to claim 1, characterized in that: The data scheduling unit optimizes the queuing performance according to the queuing theory to reduce the data packet delay of the high priority task. The queuing optimization is achieved by adjusting the data packet arrival rate and the service rate, wherein the average delay of the queue is determined by the difference between the service rate and the arrival rate.

9. A remote management device based on computer terminal control according to claim 1, characterized in that: The data optimization module dynamically adjusts the optimization strategy of each unit through a feedback mechanism, where: The network modeling unit updates the network status in real time; The path optimization unit recalculates the optimal path according to the new network status; The bandwidth allocation unit adjusts the node bandwidth allocation strategy through feedback; The data scheduling unit adjusts the priority weights in real time according to the queue load and task delay.

10. A remote management device based on computer terminal control according to claim 1, characterized in that: The data optimization module uses the Markov decision process as the optimization framework in a dynamic network environment, defines the network state, action and reward function, and obtains the global optimal strategy of the communication system through real-time optimization, where: Network status includes link delay, packet loss rate, and bandwidth; The actions are path selection, bandwidth allocation, and data scheduling; The reward function is defined based on the weighted values ​​of delay and packet loss rate.

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