Multi-channel meter reading optimization method based on terminal routing

Abstract

The invention discloses a multi-channel meter reading optimization method based on terminal routing. According to the technical scheme, the system aims at solving the problems of resource waste and communication efficiency reduction caused by fixed channel meter reading in the field of power system communication. According to the technical scheme, the system comprises a self-adaptive algorithm unit and an environment monitoring unit, and the number of meter reading channels can be dynamically adjusted according to real-time communication loads and network conditions. And the adaptive algorithm unit receives the network environment and communication load data provided by the environment monitoring unit, and determines the optimal meter reading channel configuration through algorithm calculation. The environment monitoring unit monitors network bandwidth requirements, transmission delay, signal quality, network congestion and other parameters and communication load conditions in real time. And the system continuously optimizes the performance through a feedback mechanism. Compared with a traditional fixed channel meter reading method, the method has the advantages that efficient utilization of resources is achieved, the flexibility and adaptability of a communication system are improved, meanwhile, the cost is reduced, and the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the field of power system communication, and particularly to an optimization method for multi-channel meter reading based on terminal routing. In the field of power system communication, multi-channel meter reading based on terminal routing is one of the key technologies, and the present invention mainly solves a series of problems brought by the fixed number of channels for meter reading in this field.

[0002] In traditional power system communication, the number of meter reading channels is usually statically configured as a fixed value and cannot be dynamically adjusted according to actual needs and network conditions. This has led to some problems. First, when the communication load is low, there may be too many idle channels, resulting in waste of resources. Second, when the communication load is high, the fixed number of channels may not meet the requirements, leading to communication congestion and increased transmission delay.

[0003] The present invention aims to achieve dynamic adjustment of multi-channel meter reading based on terminal routing by introducing an adaptive algorithm. Specifically, the adaptive algorithm can adjust the number of meter reading channels in real time according to the real-time communication load and network conditions. When the communication load is low, the adaptive algorithm reduces the number of idle channels to improve resource utilization; when the communication load is high, it increases the number of meter reading channels to ensure sufficient bandwidth and throughput.

[0004] The application field of this technical solution is power system communication, especially multi-channel meter reading involving terminal routing. By introducing an adaptive algorithm, the present invention realizes dynamic adjustment of the number of meter reading channels and solves the limitation of the fixed number of meter reading channels in traditional methods. Therefore, the present invention has broad application prospects in the field of power system communication and can provide a more efficient, flexible and intelligent broadband communication solution. Background Art

[0005] In the current field of power system communication, the optimization and adjustment of multi-channel meter reading based on terminal routing is a key issue. In traditional methods, the number of meter reading channels is statically configured as a fixed value and cannot be dynamically adjusted according to actual needs and network conditions, thus leading to a series of problems.

[0006] First, since the number of meter reading channels is fixed, when the communication load is low, there may be too many idle channels. This waste of resources not only causes cost waste but also wastes valuable communication resources, preventing the network from being fully utilized. In this case, multi-channel meter reading with a fixed number of terminal routes cannot flexibly adapt to changes in communication load, limiting the efficiency and performance of the communication system. Second, when the communication load is high, multi-channel meter reading with a fixed number of terminal routes may not be able to meet the demand, resulting in communication congestion and increased transmission delays. This leads to a decline in communication quality and affects the user experience. The fixed number of channel meter readings cannot adapt to dynamic communication requirements, limiting the flexibility and adaptability of the communication system.

[0007] Therefore, the objective of the present invention is to solve the problems brought about by the fixed number of meter reading channels in traditional methods. Through an adaptive algorithm, the present invention can dynamically adjust the number of meter reading channels according to actual needs and network conditions to achieve optimal utilization of resources and improvement of communication efficiency.

[0008] Through the adaptive algorithm, the number of meter reading channels can be adjusted in real time according to real-time communication load and network conditions. When the communication load is low, the adaptive algorithm can reduce the number of idle channels, achieving resource conservation and increased utilization. When the communication load is high, the adaptive algorithm can increase the number of meter reading channels to ensure sufficient bandwidth and throughput, improving communication efficiency and transmission speed. Summary of the Invention

[0009] In view of the deficiencies and defects existing in the prior art, the present invention provides an optimization method for multi-channel meter reading based on terminal routing. Aiming at the limitation of the fixed number of meter reading channels in traditional methods, by introducing an adaptive algorithm, dynamic adjustment of multi-channel meter reading based on terminal routing is achieved. This technical solution can flexibly adjust the number of meter reading channels according to actual needs and network conditions, solve the problems of resource waste and decreased communication efficiency, and provide a more efficient, flexible, and intelligent broadband communication solution.

[0010] The objective of the present invention can be achieved through the following technical solutions:

[0011] An optimization method for multi-channel meter reading based on terminal routing, comprising the following steps:

[0012] Step 1: Monitor the network conditions and communication load in real time, obtain relevant parameters, including bandwidth requirements, transmission delays, signal quality, network congestion, etc., and evaluate the current communication load situation, such as real-time data transmission volume, packet loss rate, transmission rate, etc.

[0013] Step 2: Dynamically adjust the number of meter reading channels according to the monitored network environment and communication load situation to achieve optimal performance and resource utilization.

[0014] Step 3: Feed back the real-time network environment and communication load information to the adaptive algorithm module to achieve real-time performance optimization of the system.

[0015] Further, in the above Step 1, the environment monitoring unit is used to monitor the network condition in real time, providing an accurate data basis for the decision-making of the adaptive algorithm unit.

[0016] Further, in the above Step 2, the adaptive algorithm unit is a key component of the present invention, responsible for implementing the adaptive algorithm for selecting the number of meter reading channels.

[0017] Further, in the above Step 3, the feedback mechanism ensures that the system can make corresponding adjustments according to the changes in the real-time network environment to maintain the optimal communication efficiency and resource utilization.

[0018] Beneficial technical effects of the present invention: By introducing the adaptive algorithm, the dynamic adjustment of the number of multi-channel meter reading channels is realized, solving the problems of resource waste and decreased communication efficiency caused by the fixed number of meter reading channels in the traditional method. The specific effects include achieving dynamic adjustment, improving resource utilization rate, and the ability to adapt to different environments. Description of the Drawings

[0019] Figure 1 is the overall framework diagram of the present invention.

[0020] Figure 2 is the partial functional block flowchart of the adaptive algorithm unit of the present invention Detailed Embodiments

[0021] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not limit the present invention.

[0022] As Figure 1 The present invention relates to an adaptive multi-channel meter reading system, which is used in the field of power system communication and is particularly suitable for the optimization and adjustment of multi-channel meter reading with terminal fixed routing.

[0023] The system includes:

[0024] 1. Adaptive algorithm unit: As shown by module A in Figure 1 , this unit is responsible for receiving the data provided by the environment monitoring unit and dynamically adjusting the number of meter reading channels according to these data.

[0025] Figure 2This is the adaptive algorithm unit part of the present invention. In this part, simple rules or calculation methods can be adopted. Due to the real-time nature and uncontrollability of the network, the parameters received by this model are defaulted to fuzzy parameters in this case, and fuzzy logic control is used to control the dynamic adjustment of the number of meter reading channels. The specific flowchart is as shown in Figure 2 shown below.

[0026] The specific steps are as follows:

[0027] Step 1: Define fuzzy sets:

[0028] First of all, it is necessary to define the fuzzy sets of input variables (such as data transmission volume, packet loss rate, transmission rate) and output variables (such as the number of channels). For example, the input variables can be defined as "low", "medium", "high", and the output variables can be defined as "reduce channels", "remain unchanged", "increase channels".

[0029] Step 2: Establish a fuzzy rule base:

[0030] According to the actual network management and communication requirements, a series of fuzzy rules are formulated. These rules describe the control strategies that should be taken under specific input conditions. For example:

[0031] If the data transmission volume is "low" and the packet loss rate is "low", then keep the number of channels unchanged.

[0032] If the data transmission volume is "high" and the transmission rate is "low", then increase the number of channels.

[0033] Step 3: Fuzzy inference:

[0034] During actual operation, the system will monitor the values of input variables in real time and convert them into membership degrees in the fuzzy set. Then, based on the fuzzy rule base, inferences are made to determine the values of output variables in the current situation. This process involves operations of fuzzy logic, such as fuzzy "AND", "OR", "NOT", etc.

[0035] Step 4: Defuzzification:

[0036] The result of fuzzy inference is a fuzzy output set, which needs to be converted into specific numerical values through the defuzzification process. Commonly used defuzzification methods include the centroid method, the maximum membership degree method, etc. For example, if the result after defuzzification indicates that channels should be increased, the system will perform the operation of increasing channels.

[0037] Step 5: Feedback adjustment:

[0038] The system will adjust the fuzzy rule base according to the feedback of the network state after execution to optimize the control strategy. This may involve adjusting the definition of fuzzy sets, modifying fuzzy rules, or adjusting the defuzzification method.

[0039] Step 6: System implementation:

[0040] Integrate the implementation of the above-mentioned fuzzy logic control into the network management system, enabling it to monitor the network status in real time and dynamically adjust the number of meter reading channels according to the output of the fuzzy controller.

[0041] 2. Environmental monitoring unit: As shown in Module B of Figure 1 , this unit is responsible for monitoring the network status in real time, including parameters such as bandwidth demand, transmission delay, signal quality, network congestion, etc., as well as communication load conditions, such as indicators like real-time data transmission volume, packet loss rate, transmission rate, etc. Specific implementation method:

[0043] As shown in Figure 1 , an adaptive multi-channel meter reading system includes the following steps:

[0044] Step 1: The environmental monitoring unit B monitors the meter reading network status and communication load conditions in real time, and obtains relevant parameter data.

[0045] Step 2: The adaptive algorithm unit A receives the data provided by the environmental monitoring unit B, and performs algorithm calculations based on these data to determine whether it is necessary to adjust the number of meter reading channels.

[0046] Step 3: If the adaptive algorithm unit A decides that adjustment is needed, it will issue an instruction to increase or decrease the number of meter reading channels to adapt to the current communication load and network status.

[0047] Step 4: The system feeds back the real-time network environment and communication load information to the adaptive algorithm unit A for further performance optimization and adjustment.

[0048] Through the above implementation method, the adaptive multi-channel meter reading system of the present invention can dynamically adjust the number of meter reading channels according to the real-time communication load and network status, thereby achieving optimal utilization of resources and improvement of communication efficiency.

[0049] The above embodiments are illustrative of the specific implementation methods of the present invention, rather than limitations on the present invention. Those skilled in the relevant technical fields can make various transformations and changes without departing from the spirit and scope of the present invention to obtain corresponding equivalent technical solutions. Therefore, all equivalent technical solutions should be included in the patent protection scope of the present invention.

Claims

1. An optimization method for multi-channel meter reading based on terminal routing, characterized in that It includes an adaptive algorithm unit and an environment monitoring unit. The adaptive algorithm unit is used to dynamically adjust the number of meter reading channels according to the network environment and communication load data provided by the environment monitoring unit.

2. The optimized method for multi-channel meter reading based on terminal routing according to claim 1, characterized in that, The adaptive algorithm unit adopts a threshold judgment method based on communication load to adjust the number of meter reading channels.

3. An optimization method for multi-channel meter reading based on terminal routing according to claim 1, characterized in that, The network environment parameters monitored by the environment monitoring unit include bandwidth requirements, transmission delay, signal quality, and network congestion level.

4. An optimization method for multi-channel meter reading based on terminal routing according to claim 1, characterized in that, The communication load conditions monitored by the environment monitoring unit include real-time data transmission volume, packet loss rate, and transmission rate.

5. An optimization method for multi-channel meter reading based on terminal routing according to claim 1, characterized in that The adaptive algorithm unit can make intelligent decisions based on real-time monitoring data to achieve flexible adjustment of the number of multi-channel meter reading channels.

6. The optimized method for multi-channel meter reading based on terminal routing according to claim 1, wherein The system also includes a feedback mechanism for feeding back real-time network environment and communication load information to the adaptive algorithm unit to achieve real-time performance optimization of the system.

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