A method for dynamic resource management of low voltage power line carrier communication system

Abstract

The present invention discloses a method for dynamic resource management of a low-voltage power line carrier communication system, including: collecting resource data information of the low-voltage power line carrier communication system; constructing a hierarchical topological structure of the power line carrier communication system based on the collected information, and hierarchically managing the resources based on the hierarchical management strategy and hierarchical topological structure of the power line carrier communication system resources; dynamically scheduling the resources according to the dynamic spectrum resource management strategy of the genetic algorithm, so as to realize the dynamic resource management of the power line carrier communication system. The present invention combines the advantages of distributed and centralized management, and can better adapt to the hierarchical topological structure of the power line carrier communication system; it can allocate resources to certain tasks on demand, and newly added tasks can only be allocated within the scope of the remaining available resources, rather than uniformly scheduling from a global perspective. In addition, the present invention adopts a dynamic scheduling method, which can effectively improve the utilization rate of the spectrum resources of the power line carrier communication.

Description

Technical Field

[0001] The present invention relates to the technical field of low-voltage power line carrier communication systems, and in particular to a method for dynamically managing resources of low-voltage power line carrier communication systems. Background Art

[0002] In the existing dynamic resource management methods of low-voltage power line carrier communication systems, centralized communication system resource management has poor flexibility and scalability, and is difficult to adapt to the topology of power line carrier communication systems; distributed communication system resource management lacks global information support. Even if the overall performance of the system can be improved through information interaction, this architecture is difficult to achieve optimal use of resources; static communication system resource management can only allocate new tasks within the scope of remaining available resources, rather than uniformly scheduling from a global perspective. In addition, the static allocation method lacks a resource recovery mechanism, and resource allocation is not flexible enough, resulting in low resource utilization. Summary of the invention

[0003] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is: in the prior art, flexibility and scalability are poor, it is difficult to achieve optimal use of resources, the resource management of the static communication system is not uniformly scheduled from a global perspective, there is a lack of a recovery mechanism, and resource allocation is not flexible enough, resulting in low resource utilization.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: collecting resource data information of a low-voltage power line carrier communication system; constructing a hierarchical topology structure of the power line carrier communication system according to the collected information, and performing hierarchical management of resources based on the power line carrier communication system resource hierarchical management strategy and the hierarchical topology structure; dynamically scheduling the resources according to the dynamic spectrum resource management strategy of the genetic algorithm to realize dynamic resource management of the power line carrier communication system.

[0007] As a preferred solution of the low-voltage power line carrier communication system resource dynamic management method described in the present invention, the power line carrier communication network includes multiple nodes, and the nodes include a central node - transformer, a common node - branch box and a terminal node - meter box.

[0008] As a preferred solution of the low-voltage power line carrier communication system resource dynamic management method described in the present invention, wherein: the hierarchical management strategy includes centralized and distributed architectures, and the resource management function is dispersed to the nodes of each network for execution, and the central node is established on the multiple nodes to coordinate the resource status between the entities and make a global optimization strategy.

[0009] As a preferred solution of the method for dynamic resource management of low-voltage power line carrier communication system described in the present invention, wherein: the hierarchical decision-making mechanism combining the advantages of the distributed and centralized architecture calculates the optimal solution for dispatching the optimal working state in the power line carrier communication network in the region. * , specifically including,

[0010]

[0011]

[0012] Among them, ε represents the upper threshold, λ and μ represent the average service arrival rate and service time within a given time.

[0013] As a preferred solution of the method for dynamic resource management of a low-voltage power line carrier communication system described in the present invention, the dynamic spectrum resource management strategy of the genetic algorithm includes chromosome encoding, initializing the population, designing a fitness function, selection, crossover, and mutation.

[0014] As a preferred solution of the method for dynamic management of resources of a low-voltage power line carrier communication system described in the present invention, wherein: according to the usage characteristics of the communication task, the basic constraints for the dynamic scheduling of the power line carrier communication resources are analyzed, including time constraints: the duration required for the task is fixed, the time range required for the task is continuous, the task has a minimum start time and a latest end time, and the difference between the latest end time and the minimum start time must be greater than or equal to the duration required for the task; frequency constraints: the bandwidth required for the task is fixed, and the frequency range required for the task is continuous.

[0015] As a preferred solution of the low-voltage power line carrier communication system resource dynamic management method described in the present invention, wherein: the dynamic scheduling of power line carrier communication system resources includes finally obtaining a set of optimal communication task arrangement sequences by formulating a series of optimal scheduling principles: assuming that the given time range is 0T, at this time T should be greater than or equal to the maximum value of the latest end time of all tasks, and the given frequency range is 0F, then the optimal scheduling principle is as follows: the frequency value represented by the frequency contour line, that is, the maximum height value of the task sample diagram is lower than the preset threshold; the time value represented by the time contour line, that is, the maximum width value of the task sample diagram is lower than the preset threshold.

[0016] As a preferred solution of the method for dynamic resource management of a low-voltage power line carrier communication system described in the present invention, wherein: according to the optimal scheduling principle, the design of the dynamic scheduling process of the power line carrier resource includes randomly initializing a sorting sequence of n communication tasks; taking out each communication task in turn according to the order of the sorting sequence, for each task, defining the earliest start time as t0, the latest start time as t1, and the duration as t, then in the time period of t0 to t0+t, finding whether there is idle frequency resource to support the task, if so, arranging the task blocks in the same order within the time period; If it does not exist within the corresponding frequency range, add an offset t' to the start time of the search time period, repeat the above search process, if no available frequency resources are found when t0+t'+t>t1, mark the task as an unassignable task; calculate the total area Area0 of all the task blocks arranged, calculate the area Area within the frequency contour line and time contour line formed after the arrangement is completed, and finally calculate f=Area0 / Area; exchange the task positions, adjust the task arrangement, find the maximum value of f, and until f converges or meets the number of iterations, output the task arrangement result when f is the maximum.

[0017] As a preferred solution of the method for dynamic resource management of a low-voltage power line carrier communication system described in the present invention, the genetic algorithm solution process includes:

[0018] Chromosome encoding and population initialization:

[0019] Interchange coding is used. During initialization, M task sequences are randomly initialized according to the size of the initial population M. The expression of each sequence is as follows:

[0020] Q={q1,q2,q3,…,q n}

[0021] Find the fitness function:

[0022] The fitness function is a measure of the adaptability of chromosomes in the population. The larger the fitness function value, the better the quality of the solution. The fitness function is determined to be Z = Z according to the optimal scheduling. 2 (f), where f = Area0 / Area, where Area0 is the total area of ​​the task blocks to be arranged, and Area is the area within the frequency contour line and time contour line formed after the arrangement is completed, and the maximum value of f is 1.

[0023] Selection: The process of selecting chromosomes to enter the next generation population according to the size of the fitness value;

[0024] For each chromosome in the initial population, the size of its fitness function value is calculated, and then the roulette algorithm is used to perform proportional selection operation according to the size of the chromosome fitness function value. The selection probability formula is:

[0025]

[0026] Where f(i) is the fitness function value of chromosome i. When selecting chromosomes, a number k is randomly generated, 0<k<1. If the random number k satisfies (P1+P2+…+P i-1 )<k<(P1+P2+…+P i ), then the i-th chromosome is selected;

[0027] Crossover: First, pair the chromosomes in the selected population with random probability, and then select a single-point crossover operator to perform a crossover operation to generate M chromosomes to form the offspring population;

[0028] The process of the single-point crossover operation based on interchange coding is as follows: let the two chromosomes to be crossed be X and Y, randomly generate a crossover position b within the range of 1n, copy the elements before b from X to a new offspring chromosome newX as the front element, and copy the remaining elements to newX in the order of their appearance in Y, and obtain another new chromosome newY in the same way;

[0029] Mutation: For the offspring chromosomes that have undergone the crossover operation, the position mutation operator is used to perform the mutation operation, and two mutation positions b1 and b2 are randomly generated within the range of 1n. The two tasks located at b1 and b2 in the offspring chromosomes are swapped with a small probability.

[0030] Elite retention: An elite retention strategy is introduced to optimize the genetic algorithm.

[0031] Beneficial effects of the present invention: hierarchical resource management combines the advantages of distributed and centralized management, and can better adapt to the hierarchical topology of the power line carrier communication system; compared with the static resource allocation method used to allocate resources to certain tasks on demand, new tasks can only be allocated within the scope of the remaining available resources, rather than being uniformly scheduled from a global perspective. In addition, the present invention adopts a dynamic scheduling method, which can effectively improve the utilization rate of power line carrier communication spectrum resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0033] Figure 1 A schematic diagram of a hierarchical power line carrier resource management architecture of a low voltage power line carrier communication system resource dynamic management method provided by an embodiment of the present invention;

[0034] Figure 2 A schematic diagram of communication task arrangement of a method for dynamic resource management of a low-voltage power line carrier communication system provided by an embodiment of the present invention;

[0035] Figure 3 An example diagram of a single-point crossover operation of a method for dynamic resource management of a low-voltage power line carrier communication system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0037] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0038] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0039] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0040] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0041] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0042] Example 1

[0043] Reference Figures 1 to 3 , as an embodiment of the present invention, provides a method for dynamic management of resources of a low-voltage power line carrier communication system, comprising:

[0044] S1: Collect low-voltage power line carrier communication system resource data information.

[0045] It should be noted that the collected data information is the distribution status of physical resources such as transformers, branch boxes, and meter boxes. Among them, the power line carrier communication network is a network composed of multiple nodes, and the nodes can be divided into central nodes (transformers), ordinary nodes (branch boxes), and terminal nodes (meter boxes).

[0046] S2: construct a hierarchical topology structure of the power line carrier communication system according to the collected information, and manage the resources in a hierarchical manner based on the power line carrier communication system resource hierarchical management strategy and the hierarchical topology structure.

[0047] It should be noted that if Figure 1 As shown in the figure, the hierarchical management architecture combines the characteristics of centralized and distributed architectures, distributes some resource management functions to the nodes of each network for execution, and establishes central nodes on multiple nodes. It can coordinate the resource status between entities and make global optimization strategies, and achieve a good compromise in terms of system overhead, network flexibility and network performance. The centralized management architecture and the distributed management architecture each have their own advantages and disadvantages, and the hierarchical management architecture that combines the characteristics of the above two is considered to be the most competitive communication resource management method.

[0048] In order to avoid service congestion in the power line carrier communication system, the present invention proposes that the global goal of the collaborative network based on the above model is to maximize the overall network benefit in the region under the premise of meeting the node QoS requirements; the following hierarchical decision-making mechanism combining the advantages of distributed and centralized is more suitable for studying the optimal solution for scheduling the best working state in the power line carrier communication network in the region. * The problem can be specifically expressed as follows:

[0049]

[0050]

[0051] Among them, ε represents the upper threshold, λ and μ represent the average service arrival rate and service time within a given time. According to the Irish formula, the blocking rate in the system shall not exceed an upper threshold ε. In this embodiment, the blocking rate is used as a service requirement. The blocking rate of the power line carrier communication network in the area for the service needs to meet a preset threshold to ensure that users can access the network in a timely manner. The selection of the upper threshold ε of the blocking rate can be set according to the standard of the communication network.

[0052] S3: Dynamically schedule resources according to the dynamic spectrum resource management strategy of the genetic algorithm to realize dynamic resource management of the power line carrier communication system.

[0053] It should be noted that the genetic algorithm first represents the parameters of the problem with genes and the solution to the problem with chromosomes, thereby obtaining a group composed of different chromosomes. This group is placed in a specific problem environment to compete for survival. The fittest have the best chance to survive and produce offspring. The offspring randomly inherit the best characteristics of their parents and continue this process under the control of the living environment. As evolution continues, the chromosomes of the group will gradually adapt to the environment and finally converge to a group of chromosomes that are most adapted to the environment, that is, the optimal solution to the problem is obtained. The core process can be described as: chromosome encoding, initialization of the population, design of fitness function, selection, crossover, and mutation.

[0054] The dynamic scheduling of power line carrier communication resources is achieved by effectively arranging communication tasks within a certain time range and frequency range. According to the usage characteristics of communication tasks, its basic constraints can be analyzed: time constraints and frequency constraints; time constraints: the duration required for the task is fixed, the time range required for the task is continuous, the task has a minimum start time and a latest end time, and the difference between the latest end time and the minimum start time must be greater than or equal to the duration required for the task; frequency constraints: the bandwidth required for the task is fixed, and the frequency range required for the task is continuous; According to the above description, the arrangement of multiple communication tasks can be characterized by a two-dimensional coordinate system, and the arrangement diagram is as follows Figure 2 shown.

[0055] In the process of power line carrier communication, since the time requirements and bandwidth requirements of each communication task are different, their different arrangement orders will lead to different resource utilization within the limited time and bandwidth range. The dynamic scheduling of power line carrier communication system resources is to formulate a series of optimal scheduling principles to finally obtain a set of optimal communication task arrangement sequences:

[0056] Assume that the given time range is 0T, in which case T should be greater than or equal to the maximum value of the latest end time of all tasks, and the given frequency range is 0F, then the optimal scheduling principle is as follows:

[0057] The frequency value represented by the frequency contour line, i.e., the maximum height value of the task arrangement diagram, is lower than the preset threshold;

[0058] The time value represented by the time contour line, that is, the maximum width value of the task sample graph is lower than the preset threshold.

[0059] Furthermore, according to the optimal scheduling principle, the design of the dynamic scheduling process of power line carrier resources includes:

[0060] Randomly initialize a sorted sequence with n communication tasks;

[0061] Take out each communication task in the order of the sorting sequence. For each task, define the earliest start time as t0, the latest start time as t1, and the duration as t. Then, in the time period of t0 to t0+t, find out whether there is idle frequency resource to support the task. If so, arrange the task block in the corresponding frequency range in the time period. If not, add an offset t' to the start time of the search time period, and repeat the above search process. If no available frequency resource is found when t0+t'+t>t1, mark the task as an unassignable task.

[0062] Calculate the total area Area0 of all the task blocks that are arranged, calculate the area Area within the frequency contour line and time contour line formed after the arrangement is completed, and finally calculate f = Area0 / Area;

[0063] Exchange task positions, adjust task arrangement, find the maximum value of f, and until f converges or meets the number of iterations, output the task arrangement result when f is maximum.

[0064] Theoretically, the proposed dynamic scheduling problem of resources in the power line carrier communication system belongs to the optimization calculation problem with the highest computational complexity - NP-complete problem. For this type of problem, it is very difficult or even impossible to search for the optimal solution in the global space. Therefore, a genetic algorithm is introduced to solve the optimal solution for task sorting. This algorithm can maximize the optimal solution to the problem with the minimum computational cost and improve computational efficiency.

[0065] The genetic algorithm solution process includes:

[0066] (1) Chromosome encoding and population initialization:

[0067] Interchange coding is used, such as 1, 2, 3, 4, ..., n, these numbers represent the number of communication tasks, n is the number of tasks, and at initialization, according to the size of the initial group M, M task sequences are randomly initialized. The expression of each sequence is as follows:

[0068] Q={q1,q2,q3,…,q n}

[0069] (2) Find the fitness function:

[0070] The fitness function is a measure of the adaptability of chromosomes in the population. The larger the value of the fitness function, the better the quality of the solution. According to the optimal scheduling, the fitness function is determined to be Z = Z 2 (f), where f = Area0 / Area, where Area0 is the total area of ​​the task blocks to be arranged, and Area is the area within the frequency contour line and time contour line formed after the arrangement is completed, and the maximum value of f is 1.

[0071] (3) Selection: The process of selecting chromosomes to enter the next generation population based on the size of their fitness values. The selection operation can avoid the loss of useful genetic information in the population, thereby allowing the population to slowly approach the optimal chromosome population.

[0072] For each chromosome in the initial population, the size of its fitness function value is calculated, and then the roulette algorithm is used to perform proportional selection operation according to the size of the chromosome fitness function value. The selection probability formula is:

[0073]

[0074] Where f(i) is the fitness function value of chromosome i. When selecting chromosomes, a number k is randomly generated, 0<k<1. If the random number k satisfies (P1+P2+…+P i-1 )<k<(P1+P2+…+P i ), then the i-th chromosome is selected;

[0075] (4) Crossover: Crossover simulates the process of evolution in nature, where certain gene positions of two chromosomes are exchanged to form new chromosomes and increase population diversity. The crossover operation in the genetic algorithm is to exchange the gene positions of two chromosomes from a certain position to form new chromosomes. The crossover operation first pairs the chromosomes in the group that has undergone the selection operation with random probability, and then selects a single-point crossover operator to perform the crossover operation, generating M chromosomes to form the offspring group.

[0076] The process of the single-point crossover operation based on the interchange coding is as follows: suppose the two chromosomes to be crossed are X and Y, a crossover position b is randomly generated within the range of 1n, the elements before b in X are copied to a new offspring chromosome newX as the front element, and the remaining elements are copied to newX in the order of their appearance in Y, and another new chromosome newY is obtained in the same way. An example of a single-point crossover operation is as follows Figure 3 shown.

[0077] (5) Mutation: Mutation in genetic algorithms is to transform the value of one or several gene positions in the population to form new chromosomes. The mutation operation prevents the population from converging to a local suboptimal solution and allows the algorithm to evolve in a more optimal direction. For the offspring chromosomes that have undergone the crossover operation, the position mutation operator is used to perform the mutation operation. Two mutation positions b1 and b2 are randomly generated within the range of 1n, and the two tasks located at b1 and b2 in the offspring chromosomes are swapped with a small probability.

[0078] (6) Elite retention: In order to speed up the convergence of the algorithm, the elite retention strategy is introduced to optimize the genetic algorithm. The elite retention strategy means that in order to prevent the optimal solution generated in the evolutionary process from being destroyed by crossover and mutation, the optimal solution in each generation is copied intact to the next generation; for the offspring chromosomes that have undergone mutation operations, they are arranged in turn and the corresponding fitness is calculated, and then the chromosome with the lowest fitness in the offspring chromosomes is replaced with the optimal chromosome recorded in the selection operation to obtain the corrected offspring population; the generated offspring population is continued to iterate in this genetic algorithm, and this algorithm process is repeated until the fitness function completes convergence or reaches the required maximum iteration cycle. At this time, the best chromosome in the population is taken out as the final task arrangement result.

[0079] Example 2

[0080] This embodiment is another embodiment of the present invention. This embodiment is different from the first embodiment in that it provides a verification test of a low-voltage power line carrier communication system resource dynamic management method. In order to verify and illustrate the technical effects adopted in this method, this embodiment adopts a traditional technical solution and the method of the present invention for comparative testing, and compares the test results by means of scientific argumentation to verify the actual effect of this method.

[0081] Traditional technical solutions: poor flexibility and scalability, it is difficult to achieve optimal use of resources, resource allocation is not flexible enough, resulting in low resource utilization, in order to verify that this method has higher resource utilization than traditional methods. In this embodiment, the traditional centralized communication system resource management (traditional method 1), distributed communication system resource management (traditional method 2), static communication system resource management (traditional method 3) and this method are used to respectively conduct real-time measurement and comparison of the resource management efficiency of the simulated low-voltage power line carrier communication system.

[0082] Test environment: The low-voltage power line carrier communication system is simulated and run on the simulation platform, and the generation of various data of the system is simulated. The traditional method and this method are used to start the automatic test equipment and the MATLB software is used to implement the simulation test of this method. The simulation data is obtained according to the experimental results. The results are shown in the following table.

[0083] Table 1: Comparison of experimental results.

[0084] Test samples Traditional method 1 Traditional method 2 Traditional method 3 Method of the present invention Resource Utilization 85.12％ 86.33％ 80.14％ 98.28％ flexibility Difference Difference Difference good Scalability Difference Difference Difference good

[0085] It can be seen from the above table that the method of the present invention has better robustness than other traditional methods.

[0086] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for dynamic resource management of a low voltage power line carrier communication system, characterized in that: include: Collecting data information of low-voltage power line carrier communication system resources, constructing a hierarchical topology structure of the low-voltage power line carrier communication system according to the collected data information, and performing hierarchical management of resources based on the resource hierarchical management strategy of the low-voltage power line carrier communication system and the hierarchical topology structure; Dynamically scheduling the resources according to the dynamic spectrum resource management strategy of the genetic algorithm to achieve dynamic management of the resources of the low-voltage power line carrier communication system; The collected data information is the distribution status of the physical resources of transformers, branch boxes and meter boxes. The low-voltage power line carrier communication network is a network composed of multiple nodes, and the nodes are divided into central nodes, ordinary nodes and terminal nodes; The hierarchical management strategy includes distributed and centralized architectures, distributing resource management functions to nodes in each network for execution, and establishing the central node on the multiple nodes to coordinate resource conditions among entities and make global optimization strategies; The hierarchical decision-making mechanism combining the distributed and centralized architecture calculates the optimal solution for the best working state scheduling in the low-voltage power line carrier communication network in the region , specifically including, in, represents the upper threshold, and Indicates the average arrival rate and service time of services within a given period of time; According to the usage characteristics of the communication tasks, the basic constraints of the dynamic scheduling of the low-voltage power line carrier communication resources are analyzed, including: Time constraints: The duration of the task is fixed, the time range of the task is continuous, the task has a minimum start time and a latest end time, and the difference between the latest end time and the minimum start time must be greater than or equal to the duration of the task; Frequency constraints: The bandwidth required for the task is fixed, and the frequency range required for the task is continuous; The dynamic scheduling of low voltage power line carrier communication system resources refers to obtaining a set of optimal communication task arrangement sequences by formulating a series of optimal scheduling principles: Assume that the given time range is 0T, in which case T should be greater than or equal to the maximum value of the latest end time of all tasks, and the given frequency range is 0F, then the optimal scheduling principle is as follows: The frequency value represented by the frequency contour line, i.e., the maximum height value of the task arrangement diagram, is lower than the preset threshold; The time value represented by the time contour line, that is, the maximum width value of the task sample graph is lower than the preset threshold; According to the optimal scheduling principle, the design of the low voltage power line carrier communication resource dynamic scheduling process includes: Randomly initialize a sorted sequence with n communication tasks; Take each communication task in turn according to the order of the sorting sequence, and for each task, define the earliest start time as , the latest start time is , the duration is , then in In the time period, find out whether there is idle frequency resource to support the task. If so, arrange the task block of the task in the corresponding frequency range in the time period. If not, add an offset to the start time of the search time period. , repeat the above search process, if If no available frequency resource is found, the task is marked as an unassignable task; Calculate the total area of ​​all queued task blocks , calculate the area within the frequency contour line and time contour line formed after the arrangement is completed , the final calculation ; Exchange task positions, adjust task arrangements, and find The maximum value of Converge or meet the iteration number, output The task arrangement result at the maximum.

2. The method for dynamic resource management of a low voltage power line carrier communication system according to claim 1, characterized in that: The power line carrier communication network includes a plurality of nodes, including a central node-transformer, a common node-branch box and a terminal node-meter box.

3. The method for dynamic resource management of a low voltage power line carrier communication system according to claim 2, characterized in that: The dynamic spectrum resource management strategy of the genetic algorithm includes chromosome encoding, initializing population, designing fitness function, selection, crossover and mutation.

4. The method for dynamic resource management of a low voltage power line carrier communication system according to claim 3, characterized in that: The solution process of the genetic algorithm includes: Chromosome encoding and population initialization: Using interchangeable coding, when initializing, according to the size of the initial population , randomly initialized There are task sequences, and the expression of each sequence is as follows: Find the fitness function: The fitness function is a measure of the adaptability of chromosomes in the population. The larger the fitness function value, the better the quality of the solution. The fitness function is determined according to the optimal scheduling as ,in ,in is the total area of ​​the task blocks that are arranged, It is the area within the frequency contour line and time contour line formed after the arrangement is completed. The maximum value is 1; Selection: The process of selecting chromosomes to enter the next generation population according to the size of the fitness value; For each chromosome in the initial population, the size of its fitness function value is calculated, and then the roulette algorithm is used to perform proportional selection operation according to the size of the chromosome fitness function value. The selection probability formula is: In the formula, Chromosome The fitness function value of the chromosome is randomly generated when selecting chromosomes. , , if the random number satisfy , then Chromosomes were selected; Crossover: First, the chromosomes in the selected population are paired with random probability, and then a single-point crossover operator is selected for crossover operation to generate Each chromosome constitutes the offspring population; The process of single-point crossover operation based on exchange coding is as follows: Suppose the two chromosomes to be crossed are and ,exist A random intersection is generated within the range ,from The Lieutenant General is located at The previous element is copied to a new daughter chromosome As the first element, the remaining elements are The order in which they appear is copied to , and another new chromosome is obtained in the same way ; Mutation: For the offspring chromosomes that have undergone crossover operations, a position mutation operator is used to perform mutation operations. Randomly generate 2 variants within the range , with a smaller probability, on the chromosomes of the offspring The two tasks are swapped; Elite retention: An elite retention strategy is introduced to optimize the genetic algorithm.

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