A local area network point-to-point transmission method based on unicast

Abstract

The present invention relates to the technical field of data transmission, and in particular to a unicast-based local area network point-to-point transmission method, comprising: obtaining local area network node function status data at multiple sampling moments; constructing a resource transmission path model based on the node function status data, and constructing all path sequences from a seed node to a resource holding node for a resource request; calculating a path selectability coefficient based on path activity and path length; calculating a path confidence based on the path selectability coefficient and extracting potential transmission paths; extracting an optimal transmission path from the potential transmission paths; so as to realize efficient and accurate transmission of data in a local area network.

Description

Technical Field

[0001] The present invention relates to the technical field of data transmission, and in particular to a local area network point-to-point transmission method based on unicast. Background Art

[0002] In the Internet environment, P2P peer-to-peer download is a method of file transfer using a distributed network architecture; during the P2P download process, each user participating in the file download is both a downloader and an uploader, and can directly exchange file fragments with each other without relying on a single central server for file transfer. However, due to network topology, security policies and other reasons, enterprise-level LAN environments usually cannot directly use P2P technology for file transfer, and other methods are needed to optimize the data transmission efficiency within the LAN.

[0003] At present, data transmission within enterprise-level LANs usually uses baseband transmission technology. Baseband transmission technology has the advantages of high transmission rate and low bit error rate, but it still has the following problems in point-to-point transmission scenarios:

[0004] Low resource utilization: Point-to-point transmission within a LAN is usually just a simple resource allocation, which fails to fully utilize the high efficiency of baseband transmission, resulting in low resource utilization and difficulty in achieving efficient and accurate data transmission within the LAN;

[0005] Network congestion risk: Access to each network segment within the LAN is restricted, and uncontrolled point-to-point downloads may cause congestion in the network backbone and affect the normal operation of other services. Summary of the invention

[0006] In order to achieve efficient and accurate transmission of data in a local area network, the purpose of the present invention is to provide a local area network point-to-point transmission method based on unicast, and the technical solution adopted is as follows:

[0007] A local area network point-to-point transmission method based on unicast, the method comprising:

[0008] Obtaining LAN node function status data at multiple sampling times;

[0009] Build a resource transmission path model based on node function status data, and construct all path sequences from seed nodes to resource holding nodes for resource requests;

[0010] Calculate the path selectivity coefficient based on path activity and path length;

[0011] Calculate path confidence based on path selectability coefficient and extract potential transmission paths;

[0012] Extract the optimal transmission path from potential transmission paths.

[0013] Furthermore, a resource transmission path model is constructed based on the node function status data, and a path sequence from the seed node to the resource holding node is constructed for each resource request, including:

[0014] For the seed node that initiates the resource request, a list of resource nodes storing the target resources is extracted;

[0015] Use graph algorithms to calculate the path sequence of all resource nodes;

[0016] Calculate the activity of each node on the path sequence and determine the length of the path sequence.

[0017] Furthermore, calculating the path selectability coefficient based on the path activity and the path length includes:

[0018] Take a weighted average of the activity of each node on the path sequence to get the mean path activity;

[0019] The selectivity coefficient is calculated based on the path sequence length and the mean path activity.

[0020] Further, calculating the path confidence based on the path selectability coefficient and extracting the potential transmission path includes:

[0021] Obtain the difference in path selectability coefficient and path sequence length between the current sampling time and the next sampling time in the same time window;

[0022] The ratio of the difference in selectability coefficient to the difference in path sequence length was calculated, and the path confidence was determined using an exponential function;

[0023] Extract potential transmission paths based on path confidence.

[0024] Further, extracting the optimal transmission path from the potential transmission paths includes:

[0025] The objective function is constructed according to the confidence of potential transmission paths and the transmission performance of seed nodes to extract the optimal transmission path.

[0026] Furthermore, the objective function is constructed according to the confidence of the potential transmission path and the transmission performance of the seed node, and the optimal transmission path is extracted including:

[0027] Get the transmission coefficient of the seed node;

[0028] Calculate the mean transmission coefficient of the seed nodes of the potential transmission path;

[0029] An objective function is constructed, and the potential transmission path that minimizes the objective function is taken as the optimal transmission path.

[0030] Furthermore, obtaining the transmission coefficient of the seed node includes:

[0031] Determine the number of resource types that the seed node can distribute;

[0032] The inverse of the number of distributable resource types is defined as the transmission coefficient of the seed node.

[0033] Furthermore, constructing the objective function includes:

[0034] The transmission cost of the potential transmission path is evaluated based on the mean value and confidence of the seed node transmission coefficient of the potential transmission path.

[0035] Further, the objective function includes a first constraint, which is defined as minimizing the length of the potential transmission path.

[0036] Furthermore, the objective function also includes a second constraint condition, which is defined as minimizing the mean of the seed node transmission coefficients.

[0037] The present invention has the following beneficial effects:

[0038] The unicast-based local area network point-to-point transmission method provided by the present invention realizes efficient and accurate data transmission from seed nodes to resource holding nodes based on unicast technology, calculates path confidence based on path selectability coefficient and extracts potential transmission paths, can avoid using seriously congested paths, reduces the waiting time of data packets during transmission, and reduces network congestion; then the optimal transmission path is selected from the potential transmission paths, and a unicast point-to-point transmission channel is established between adjacent seed nodes, and the required resource information is transmitted through this channel. This transmission mode not only ensures the accurate delivery of data, but also minimizes the consumption of network resources by identifying the optimal transmission path under the current network state, and finally realizes efficient and accurate transmission of data in the local area network, and improves the speed and efficiency of data transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. 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 paying creative work.

[0040] Figure 1 A flow chart of a local area network point-to-point transmission method based on unicast provided by one embodiment of the present invention;

[0041] Figure 2 A schematic diagram of a process for extracting potential transmission paths provided by an embodiment of the present invention;

[0042] Figure 3 A schematic diagram of a flow chart of extracting an optimal transmission path provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a unicast-based local area network point-to-point transmission method proposed by the present invention in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0044] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0045] A specific scheme of a unicast-based local area network point-to-point transmission method provided by the present invention is described in detail below with reference to the accompanying drawings.

[0046] See also Figures 1 to 3 , which shows a method flow chart of a unicast-based local area network point-to-point transmission method provided by an embodiment of the present invention. The unicast-based local area network point-to-point transmission method includes:

[0047] Step S100: Obtain the functional status data of the LAN nodes at multiple sampling times; specifically, in a P2P (Peer-to-Peer) network, limiting the role function of the node is an effective strategy to optimize network performance, ensure smooth transmission and improve efficiency. This application preferably adopts this strategy. The nodes in the P2P network are no longer just equal peers, but are given different roles according to their functions and resources, such as seed nodes, proxy nodes, index nodes, tracker nodes (Tracker), etc.; by clarifying the division of roles, the allocation and use of network resources are more finely controlled, avoiding blind consumption of resources; in step S100, the functional status data of key nodes (mainly seed nodes and proxy nodes) in the LAN at multiple time points are collected, including but not limited to key performance indicators such as memory size, network delay, network packet loss rate, and throughput.

[0048] Step S200: constructing a resource transmission path model based on the node function status data, and constructing all path sequences from the seed node to the resource holding node for the resource request;

[0049] Step S200 specifically includes:

[0050] Step S210: for the seed node that initiates the resource request, extract the list of resource nodes that store the target resources; specifically, the connection information of all nodes in the local area network can be collected through network management tools or protocols (such as SNMP, LLDP, etc.) to build a network topology map; at the same time, the resource information owned by each seed node is recorded to form a resource distribution map; then, for the seed node that initiates the resource request, the dispatch center database can be queried to obtain a list of other seed nodes that store the target resources;

[0051] Step S220: Calculate the path sequence of all resource nodes using graph algorithms; for each node that can provide the required resources, start from the requesting node, calculate all possible paths to the resource node using graph algorithms, and express these paths in sequence form, for example, as S i,j , that is, the path information between the i-th seed node and the j-th node with the required resource information. Each element in the sequence represents a node or hop that needs to be passed on the path;

[0052] Step S230: Calculate the activity of each node on the path sequence and determine the length of the path sequence; the activity of the node can be based on historical data, such as data transmission volume, response time, packet loss rate, throughput, error rate, etc., by presetting a series of indicators reflecting the activity, assigning weights to each indicator and performing weighted average to obtain the activity of each node; the activity of the node is obtained by giving a comprehensive analysis of indicators with different activity impacts, giving different weights to different indicators, and normalizing them. Different weights are assigned to the above indicators according to their impact on network transmission efficiency; for example, response time and packet loss rate have a greater impact on transmission efficiency, so they are given a higher weight; while data transmission volume and throughput are important, but their contribution to direct transmission efficiency is slightly smaller, so they are given a relatively lower weight; then these indicators are normalized to eliminate the impact of dimensions and ensure data consistency between different indicators. Comparability. Common normalization methods include maximum and minimum normalization and z-score standardization. After normalization, the activity of each node can be obtained by weighted average calculation based on the selected indicators and the corresponding weights assigned to the indicators. For each path, the average activity of all nodes on the path is calculated as the activity indicator of the path. A high activity of a node or path means that it has performed more stably and efficiently in past data transmission. The path sequence length can be the actual number of physical hops (i.e., the number of nodes on the path) or the estimated sum of transmission delays, depending on actual needs and network characteristics. A shorter path often means lower delay and faster data transmission speed. Then, the average activity of all nodes on the path is calculated as the activity indicator of the path. The shorter the path sequence and the higher the activity, the higher the transmission efficiency of the path sequence.

[0053] Step S300: Calculate the path selectivity coefficient based on the path activity and path length. Specifically, perform weighted average on the activity of each node on the path sequence to obtain the mean path activity, and then calculate the selectivity coefficient based on the path sequence length and the mean path activity. The expression is:

[0054]

[0055] In the formula, KX i,j represents the path sequence S between the i-th seed node and the j-th node with the required resource information i,j The path selectivity coefficient is represents the path sequence S between the i-th seed node and the j-th node with the required resource information i,j The average activity of all nodes, l i,j Represents the path sequence S i,j ; This embodiment combines the activity with the path length through a division operation to obtain a quantitative indicator that comprehensively considers the two, namely, the selectivity coefficient; The selectivity coefficient reflects the balance between the activity and the length of the path. The larger the selectivity coefficient value, the better the balance between the activity and the length of the path, and therefore the more suitable it is as a preferred path for data transmission; The selectivity coefficient can comprehensively evaluate the overall activity level of the entire path, rather than the performance of a single node.

[0056] Step S400: Calculating path confidence based on path selectability coefficients and extracting potential transmission paths;

[0057] Step S400 specifically includes:

[0058] Step S410: Obtain the difference in path selectability coefficients and path sequence lengths between the current sampling time and the next sampling time in the same time window; for example, for a pair of nodes i and j, calculate the path sequence S at two consecutive sampling times. i,j and its estimated sequence at the next moment The difference between the path sequence S i,j It is calculated based on the node status and network topology at the current sampling moment, and the estimated sequence at the next moment It is calculated based on the analysis of the current sequence and the prediction of the future network state; the estimated sequence at the next moment The acquisition of can be achieved by analyzing the node's past network behavior, including the changing trends of indicators such as data transmission volume, response time, and packet loss rate, to predict the node state at the next moment. Machine learning models, such as time series analysis and neural networks, can be used to predict the future state of each node in the network based on historical data, and then infer the path sequence at the next moment; the knowledge and experience of experts in the field can also be combined to manually predict the path sequence at the next moment; the difference can be calculated directly by the absolute value of the vector difference, or by measurement methods such as cosine similarity; similarly, the difference in the path selectability coefficient between two adjacent sampling moments is calculated based on the same principle;

[0059] Step S420: Calculate the ratio of the selectable coefficient difference to the path sequence length difference, and use an exponential function to determine the path confidence, which is expressed as:

[0060]

[0061] In the formula, LZ i,j represents the path sequence S between the i-th seed node and the j-th node with the required resource information i,j The path transmission confidence, Represents the path sequence S at the current sampling time i,j The path sequence at the next sampling moment The difference Indicates the path sequence selection coefficient KX at the current sampling time i,j The path selectability coefficient of the path sequence at the next sampling time The formula is used to compare the relative degree of change in path length and path selectivity, measure the degree of change of the path over time, and does not care about the direction of the change (increase or decrease). The use of absolute values ​​ensures that changes in any direction will be included in the evaluation and will not be ignored due to the cancellation of positive and negative signs. It can also be directly characterized by comparing the relative difference in the number of nodes between the two sequences.

[0062] When the path sequence difference is small relative to the path selectivity coefficient difference (i.e., the ratio is small), the negative exponential part of the exponential function is close to 0, so LZ i,j If the ratio is close to 1, it means that the path is very stable; on the contrary, if the ratio is large, the negative exponential part of the exponential function will be a large negative number, resulting in LZ i,j A value close to 0 indicates that the path is unstable or unreliable. A higher path confidence indicates that the path S is reliable despite changes in resource distribution or network status. i,j The reliability is still high and is suitable for resource transmission. The existence of is to evaluate the change of path selectivity. If the path selectivity does not change at a certain moment, that is, Then, directly using this formula may result in a division by zero error. To avoid this error, a selectivity change threshold can be set. If the path selectivity change is not large (less than the selectivity change threshold), the selectivity change threshold can be used instead of the actual change. The selectivity change threshold represents a reasonable approximation of the actual situation within the error range. You can also add a preset positive number to the above formula to avoid the problem of the denominator being 0. The expression is:

[0063]

[0064] In the formula, ε represents a positive number, and the preferred value of ε is 0.0001;

[0065] For example, suppose there are three paths, namely the first path, the second path and the third path, and the path sequence difference and path selectivity coefficient difference of each path are as follows:

[0066] First path: the path sequence difference is 1, and the path selectability coefficient difference is 5;

[0067] Second path: The path sequence difference is 3, and the path selectability coefficient difference is 1;

[0068] The third path: The path sequence difference is 2, and the path selectability coefficient difference is 2.

[0069] Based on this information, the confidence of each path was calculated: the confidence of the first path is about 0.819; the confidence of the second path is about 0.050; the confidence of the third path is about 0.368; comparing the confidence values ​​of these three paths, it is found that the first path has the highest confidence; then in this case, we choose the first path as the potential transmission path.

[0070] Step S430: extract potential transmission paths based on path confidence; specifically, a confidence threshold can be set, and the value of the confidence threshold is preferably 70%-80%, and the confidence threshold can be further adjusted according to network load and data transmission requirements; then, based on the calculated path transmission confidence, paths with confidence higher than the threshold are selected as potential transmission paths, indicating that these paths do not change much over time and their transmission potential remains stable, and are reliable transmission paths. By selecting high-confidence paths for data transmission, transmission delay and packet loss rate can be effectively reduced, and data transmission quality can be improved.

[0071] Step S500: extracting the optimal transmission path from the potential transmission paths; specifically, constructing an objective function according to the potential transmission path confidence and the transmission performance of the seed node, and extracting the optimal transmission path; since the obtained path transmission confidence is the possibility of transmission between seed nodes considered from the distribution status of a single resource, but the actual data transmission between local area networks is a comprehensive overall process, it is necessary to consider the transmission status of multiple resources, especially in the process of extended spread differentiation data transmission, the seed node has a role change between sending and receiving, and for the seed node, its data transmission load requirement is higher, and it is more necessary to realize the smooth progress of multiple types of data transmission tasks;

[0072] Step S500 specifically includes:

[0073] Step S510: Obtain the transmission coefficient of the seed node; determine the number of resource types that the seed node can distribute; for the above potential transmission path sequence, this embodiment needs to record the intermediate nodes on the potential transmission path, which can be expressed as P r ; It is also necessary to determine the number of resource types that can be distributed by each seed node. The number of resource types that the node can process and distribute can be determined based on the configuration information of the seed node. The configuration information of the seed node at least includes data about the hardware, software, and functions of the seed node. The seed node configuration information provides a basic basis for determining the number of resource types that can be distributed by each seed node;

[0074] Step S520: The inverse of the number of distributable resource types is defined as the transmission coefficient of the seed node, which is expressed as:

[0075]

[0076] In the formula, τ r represents the seed node transmission coefficient of the rth seed node, reflecting its ability and efficiency in distributing resources, n r represents the number of resource types that can be distributed by the rth seed node; the node transmission coefficient reflects the potential burden of the rth seed node during the transmission process, that is, the more distribution capabilities a node has, the more concurrent requests it may need to process, thus affecting its transmission efficiency; for each path, we need to calculate the average transmission coefficient of all seed nodes on it Specifically, this can be done by summing the transmission coefficients of all seed nodes on the path and then dividing by the number of seed nodes, which is used to reflect the average distribution capacity and efficiency of the nodes on the path;

[0077] Step S530: Calculate the mean transmission coefficient of the seed nodes of the potential transmission path;

[0078] Step S540: construct an objective function, and take the potential transmission path that minimizes the objective function as the optimal transmission path; evaluate the transmission cost of the potential transmission path based on the mean value and confidence of the seed node transmission coefficient of the potential transmission path. The objective function includes a first constraint and a second constraint. The first constraint is defined as minimizing the length of the potential transmission path, and the second constraint is defined as minimizing the mean value of the seed node transmission coefficient. The expression of the objective function is:

[0079]

[0080] In the formula, f(S i,j ) represents the path sequence S between the i-th seed node and the j-th node with the required resource information i,j The objective function of the transmission cost is represents the path sequence S between the i-th seed node and the j-th node with the required resource information i,j The mean seed node transmission coefficient of the seed node, R represents the number of all seed nodes of all path sequences obtained by a single seed node for a certain type of resource; the objective function aims to pursue the comprehensive optimal solution of the following three core objectives:

[0081] Maximizing path transmission confidence: via LZ in the numerator of the objective function i,j (Path Confidence), the goal is to select potential transmission paths that remain highly stable and reliable even when network conditions change, that is, to select paths with small sequence differences and small changes in selectability coefficients, to ensure low error rate and high efficiency during data transmission;

[0082] Minimize the seed node load on the path: by (Node transmission mean), the goal is to reduce the resource distribution pressure of each node on the path; the smaller the transmission coefficient of each node, the more types of resources the node is responsible for distributing, and the higher the potential load. By minimizing the seed node load, network resources can be balanced, individual nodes can be avoided from being overloaded, and the smoothness of resource transmission can be promoted;

[0083] Taking into account both path length and overall seed node load balance: In the additional condition of the objective function, by minimizing l i,j (path length) and find the minimum average value of seed node transmission coefficient The goal is to focus on transmission efficiency (short paths mean low latency) and global network resource utilization efficiency. The average value of node transmission coefficients is particularly focused on ensuring that no single node becomes a bottleneck due to taking on too many distribution tasks, promoting overall network load balancing;

[0084] The core of this objective function is to find the best balance between ensuring the efficiency and reliability of data transmission and the reasonable allocation of network resources, so as to optimize the resource transmission in the entire LAN. i,j ), to find the best balance between ensuring path quality and node transmission capacity, while satisfying the constraints of path length and node transmission coefficient, so as to optimize resource transmission; to obtain the optimal transmission path that can both efficiently transmit data and maintain network health and stability. Finally, according to the obtained optimal transmission path, and in accordance with the order of seed nodes in the path sequence corresponding to the optimal transmission path, adjacent seed nodes establish unicast point-to-point transmission channels, and transmit the resource information required by the node, and gradually expand to all seed nodes on the optimal path to achieve the transmission of the resource information required by the node, thereby achieving efficient and accurate transmission of data in the local area network with the minimum transmission cost; this method not only takes into account the characteristics of the path itself, but also deeply analyzes the transmission capacity of the seed node and the dynamics of the network over time, thus providing a comprehensive and flexible solution for resource allocation and transmission in complex network environments. For resource allocation and transmission in complex network environments, this method provides a comprehensive and flexible solution that can effectively respond to the dynamic changes of network resources, ensure efficient allocation and transmission of resources, and maximize the utilization efficiency of network resources through continuous monitoring and timely adjustment, reduce transmission delays and congestion, and improve the overall user experience and network performance.

[0085] It should be noted that the above-mentioned unicast-based LAN point-to-point transmission method can realize efficient, stable and intelligent resource allocation through the centralized management of the dispatching center and the distributed collaboration of nodes, combined with key technologies such as automatic spread of resource requests, hand-raising competition mechanism, resource pool update, path optimization and closed-loop control. In actual deployment, the main roles include the dispatching center, proxy nodes and seed nodes. As the network hub, the dispatching center needs to deploy high-performance servers to be responsible for the centralized storage and management of resources. Through the cluster mode, the reliability and processing capacity of the service are improved. The dispatching center should have functions such as resource discovery, allocation, and monitoring, and be able to dynamically adjust the resource allocation strategy; resource requests start from the dispatching center and automatically spread in the network through proxy services and seed services. After receiving the request, the proxy services and seed services feedback their status and capabilities to the dispatching center, and use the broadcast mechanism of the P2P protocol, combined with a custom request propagation algorithm, to ensure that the request can be quickly and accurately spread throughout the network. The proxy service and seed service need to implement a monitoring mechanism to capture and process requests from the dispatching center.

[0086] It should be noted that the sequence of the above embodiments of the present invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0087] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A local area network point-to-point transmission method based on unicast, It is characterized in that The method comprises: Obtaining LAN node function status data at multiple sampling times; The resource transmission path model is constructed based on the node function status data, and all path sequences from the seed node to the resource holding node are constructed for resource requests, including: For the seed node that initiates the resource request, extract the list of resource nodes that store the target resources; use the graph algorithm to calculate the path sequence of all resource nodes; calculate the activity of each node on the path sequence and determine the length of the path sequence; Among them, based on historical data, by presetting a series of indicators reflecting activity, assigning weights to each indicator and performing weighted average, the activity of each node is obtained; The calculation of path selectivity coefficient based on path activity and path length includes: Take a weighted average of the activity of each node on the path sequence to get the mean path activity; The selectivity coefficient is calculated based on the path sequence length and the mean path activity. The calculation formula is: In the formula, KX i,j represents the path sequence S between the i-th seed node and the j-th node with the required resource information i,j The path selectivity coefficient is represents the path sequence S between the i-th seed node and the j-th node with the required resource information i,j The average activity of all nodes, l i,j Represents the path sequence S i,j The path length; Calculating path confidence based on path selectability coefficient and extracting potential transmission paths include: Obtain the difference in path selectivity coefficient and path sequence length between the current sampling time and the next sampling time in the same time window; calculate the ratio of the selectivity coefficient difference to the path sequence length difference, and use the exponential function to determine the path confidence. The calculation formula is: In the formula, LZ i,j represents the path sequence S between the i-th seed node and the j-th node with the required resource information i,j The path transmission confidence, Represents the path sequence S at the current sampling time i,j The path sequence with the next sampling moment The difference Indicates the path sequence selection coefficient KX at the current sampling time i,j The path selectability coefficient of the path sequence at the next sampling time differences; Extract potential transmission paths based on path confidence; Extract the optimal transmission path from potential transmission paths.

2. A local area network point-to-point transmission method based on unicast according to claim 1, It is characterized in that Extracting the optimal transmission path from potential transmission paths includes: The objective function is constructed according to the confidence of potential transmission paths and the transmission performance of seed nodes to extract the optimal transmission path.

3. A local area network point-to-point transmission method based on unicast according to claim 2, It is characterized in that The objective function is constructed based on the confidence of the potential transmission path and the transmission performance of the seed node, and the optimal transmission path is extracted, including: Get the transmission coefficient of the seed node; Calculate the mean transmission coefficient of the seed nodes of the potential transmission path; An objective function is constructed, and the potential transmission path that minimizes the objective function is taken as the optimal transmission path.

4. A local area network point-to-point transmission method based on unicast as claimed in claim 3, It is characterized in that Obtaining the transmission coefficient of the seed node includes: Determine the number of resource types that the seed node can distribute; The inverse of the number of distributable resource types is defined as the transmission coefficient of the seed node.

5. A local area network point-to-point transmission method based on unicast as claimed in claim 3, It is characterized in that Constructing the objective function includes: The transmission cost of the potential transmission path is evaluated based on the mean value and confidence of the seed node transmission coefficient of the potential transmission path.

6. A local area network point-to-point transmission method based on unicast as claimed in claim 5, It is characterized in that The objective function includes a first constraint, which is defined as minimizing the length of a potential transmission path.

7. A local area network point-to-point transmission method based on unicast as claimed in claim 6, It is characterized in that The objective function also includes a second constraint, which is defined as minimizing the mean of the seed node transmission coefficients.

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