Improved efficient routing policies over two-tier networks

Abstract

The invention discloses an improved effective routing strategy on a double-layer network, and particularly relates to the field of information flow transmission in the network, a double-layer network model is constructed, and the model comprises a logic layer and a physical layer; the logic layer is responsible for generating a data packet, selecting a route, issuing an instruction and transmitting the data packet from a source node to a destination node according to a routing table which is determined in advance and updated in real time, and the physical layer is used for processing receiving and forwarding of the data packet and selecting an optimal physical path based on the routing table of the physical layer; analyzing a node degree value in the framework, calculating a probability degree index by taking the degree value as a cost function, distributing a weight for each link, and calculating an optimal data transmission path according to the weight of the edge and the path length; then, carrying out routing optimization in the logic layer according to the transmission capability of the nodes, the network topology and the weight distribution mode so as to improve the network transmission capacity; and finally, dynamically adjusting a probability index in combination with network state monitoring, and updating routing information in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of information flow transmission in a network, and more particularly to an improved effective routing strategy on a double-layer network. Background Art

[0002] A two-layer network usually consists of two different layers of networks, each with its own specific functions and characteristics. The basic network layer (usually called the physical layer) is responsible for the actual data transmission and connection, while the upper network layer (usually called the logical layer) builds more complex logical structures and routing paths based on the connections provided by the physical layer.

[0003] The transmission capacity of a network is an important indicator to measure the transmission capability of a network. The larger the transmission capacity of a network, the more load the network can transmit per unit time. With the rapid development of science and technology, the load that needs to be transmitted is also increasing day by day; for example, the rapid growth of traffic information networks in cities and the rapid growth of data on the Internet; However, it still has some shortcomings in actual use. For example, when the load to be transmitted exceeds the transmission capacity of the network, the network will be overloaded and data packets will not be transmitted in time. Summary of the invention

[0004] In order to overcome the above defects of the prior art, the embodiments of the present invention provide an improved effective routing strategy on a double-layer network to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: Step A1: Build a two-layer network model; Step A2: Calculate the probability index based on the node degree value; Step A3: assign a weight to each link of the physical layer in the two-layer network; Step A4: assign a weight to each link of the logical layer in the two-layer network according to the transmission capacity of the node and the network topology; Step A5: Dynamically adjust the probability index and update the routing information in real time according to the changes in the network status.

[0006] Preferably, in step A1, the two-layer network structure mainly includes a logical layer and a physical layer, the upper layer is the logical layer, and the lower layer is the physical layer; the nodes in the topmost logical layer send data packets to the destination node in the network according to the routing table determined in the logical layer; any link connecting two nodes in the upper logical layer corresponds to the physical path between two nodes in the lower physical layer; the lower physical layer sends the data packets in the network from the source node in the upper logical layer to the destination node according to the determined routing table of the physical layer.

[0007] Preferably, in step A2, the probability that a data packet in the network can smoothly pass through a node is calculated using the degree value of the node in the network as a cost function, and the calculation method of the probability degree index is specifically as follows: ,in, It is expressed as a probability index, Represented as the degree value of the node, Represented as a variable parameter.

[0008] Preferably, in step A3, in the physical layer, from node To Node The path can be marked as , and assign weights to the two connected nodes and The edge between two nodes on the physical layer in the two-layer network is calculated as follows: ,in, Represented as a node and nodes The weight of the edge between Expressed as a node The probability index when Represented as a node The probability index when In the two-layer network physical layer, from the node To Node The specific method for calculating the path weight is as follows: ,in, Represented as a slave node To Node The path weight, Represented as a slave node To Node The weight of the edge; n represents the path length, Represented as a sequence of nodes on a path; The sum of the weights of every two nodes transmitted during the path transmission process is added together, and the path with the smallest weight is the optimal path. If there are many paths with the same sum of weights during the data packet transmission process, the data packet will randomly select a path for the transmission task during the transmission process; By assigning weights to the links at the physical layer, the optimal path from the source node to the destination node is calculated, thereby optimizing the transmission path of the data packet; weight allocation guides the data packet to be evenly distributed in the network, avoiding overload of certain links and nodes, and improving the overall performance of the network; weight allocation reflects the actual transmission capacity of the link, allowing the data packet to select a link with stronger transmission capacity, thereby improving transmission efficiency.

[0009] Preferably, in step A4, the upper logical layer is responsible for generating data packets, and the lower physical layer is responsible for receiving and sending data packets in the network; in the entire double-layer network, the data packets in the network will choose the hub node in the network to perform the transmission task with a high probability; therefore, the routing table of the upper logical layer needs to bypass the hub node in the network to effectively improve the transmission capacity of the double-layer network; in the upper logical layer, the two connection nodes and The specific method for calculating the edge weight between is: ,in, Represented as a node and Assign weights to the edges between Represented as a node The probability index when Represented as a node The probability index when Represented as a node and Additional weight between ; Slave Node To Node The calculation method of the path weight is as follows: ,in, Represented as a node To Node The path weight, Represented as a slave node To Node The weight of the edge, n represents the path length, a represents the variable parameter, Represented as a sequence of nodes on a path; When planning the optimal path for transmitting data packets under this routing strategy, the parameter a that maximizes the transmission capacity of the network is the optimal parameter of the routing strategy; The best path is the path with the smallest sum of weights of each link in the logical layer; The weight of the logical layer link should reflect the transmission capacity of the node; the links of nodes with strong transmission capacity should be assigned higher weights to encourage data packets to be transmitted through these links, thereby improving the transmission efficiency of the overall network; in the network, some nodes are located on the critical path or have a higher degree of connectivity, and the links of these nodes should be assigned higher weights to ensure the connectivity and stability of the network; when some links and nodes in the network are overloaded, the weights are assigned to the links and nodes with low load balancing; by assigning different weights to different links, the data packets are guided to be evenly distributed in the network, thereby improving the reliability and stability of the network.

[0010] Preferably, in step A5, a network monitoring tool is deployed to continuously collect and analyze real-time data of the network and monitor key indicators such as node availability, latency, bandwidth utilization and packet loss rate; According to the monitored network status, the probability index between nodes is dynamically adjusted.

[0011] Technical effects and advantages of the present invention: The algorithm of the routing strategy of the present invention introduces probability degree as a new indicator at the cost of node degree, and uses the new indicator to define the weight of the edge in the logical layer and the physical layer, so as to determine the routing table for data packet transmission in the logical layer and the physical layer, and also adds a parameter a to make the parameter a with the largest network transmission capacity the optimal parameter; the present invention improves the transmission capacity of the network and alleviates network congestion through the above steps. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0013] Figure 2 Schematic diagram of the network model of the double-layer network of the present invention. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] See also Figure 1 As shown, the present invention provides an improved effective routing strategy on a double-layer network, and the method is as follows: Step A1: Build a two-layer network model; In the step A1, the double-layer network structure mainly includes a logical layer and a physical layer, the upper layer is the logical layer, and the lower layer is the physical layer; the nodes in the uppermost logical layer send data packets to the destination node in the network according to the routing table determined in the logical layer; any link connecting two nodes in the upper logical layer corresponds to the physical path between two nodes in the lower physical layer; the lower physical layer sends the data packets in the network from the source node in the upper logical layer to the destination node according to the determined routing table of the physical layer; The logic layer is responsible for the generation of data packets, routing selection, and the issuance of transmission instructions; the nodes in the logic layer, as the starting and ending points of data packet transmission, send data packets to the destination nodes in the network according to the routing table pre-determined and updated in real time in the logic layer; Any link in the logical layer represents a logical connection between two nodes; this connection does not exist directly physically, but is realized through the underlying physical layer; therefore, each link in the logical layer corresponds to a physical path between two nodes in the physical layer; these physical paths are the channels through which data packets are actually transmitted in the physical world; The physical layer is responsible for receiving and forwarding data packets and selecting physical paths. In the physical layer, data packets are transmitted along the optimal physical path from the source node to the destination node according to the routing table of the physical layer. The routing table is dynamically calculated and updated according to the actual operation of the network and performance requirements to ensure that the data packets can reach the destination node efficiently. Step A2: Calculate the probability index based on the node degree value; In step A2, the probability that a data packet in the network can smoothly pass through a node is calculated using the degree value of the node in the network as a cost function. The calculation method of the probability degree index is specifically as follows: ,in, It is expressed as a probability index, Represented as the degree value of the node, Represented as variable parameters; The probability degree index is a probability distribution function calculated based on the node degree value. It represents the probability that the degree of a randomly selected node in the network is exactly k. The probability degree index can reflect the distribution of node degree values ​​in the network. Step A3: assign a weight to each link of the physical layer in the two-layer network; In step A3, at the physical layer, from node To Node The path can be marked as , and assign weights to the two connected nodes and The edge between two nodes on the physical layer in the two-layer network is calculated as follows: ,in, Represented as a node and nodes The weight of the edge between Expressed as a node The probability index when Represented as a node The probability index when In the two-layer network physical layer, from the node To Node The specific method for calculating the path weight is as follows: ,in, Represented as a slave node To Node The path weight, Represented as a slave node To Node The weight of the edge; n represents the path length, Represented as a sequence of nodes on a path; The sum of the weights of every two nodes transmitted during the path transmission process is added together, and the path with the smallest weight is the optimal path. If there are many paths with the same sum of weights during the data packet transmission process, the data packet will randomly select a path for the transmission task during the transmission process; By assigning weights to the links at the physical layer, the optimal path from the source node to the destination node is calculated, thereby optimizing the transmission path of the data packet; weight allocation guides the data packet to be evenly distributed in the network, avoiding overload of certain links and nodes, and improving the overall performance of the network; weight allocation reflects the actual transmission capacity of the link, allowing the data packet to select a link with stronger transmission capacity, thereby improving transmission efficiency.

[0016] Step A4: assign a weight to each link of the logical layer in the two-layer network according to the transmission capacity of the node and the network topology; In step A4, the upper logical layer is responsible for generating data packets, and the lower physical layer is responsible for receiving and sending data packets in the network; in the entire two-layer network, the data packets in the network will choose the hub node in the network to perform the transmission task with a high probability; therefore, the routing table of the upper logical layer needs to bypass the hub node in the network to effectively improve the transmission capacity of the two-layer network; in the upper logical layer, the two connection nodes and The specific method for calculating the edge weight between is: ,in, Represented as a node and Assign weights to the edges between Represented as a node The probability index when Represented as a node The probability index when Represented as a node and Additional weight between ; Slave Node To Node The calculation method of the path weight is as follows: ,in, Represented as a node To Node The path weight, Represented as a slave node To Node The weight of the edge, n represents the path length, a represents the variable parameter, Represented as a sequence of nodes on a path; When planning the optimal path for transmitting data packets under this routing strategy, the parameter a that maximizes the transmission capacity of the network is the optimal parameter of the routing strategy; The best path is the path with the smallest sum of weights of each link in the logical layer; The edge between any two nodes in the network is defined as the sum of the probabilities that a data packet can pass through the node, and the path with the smallest product of the edge weights in the path is taken as the optimal path for transmitting the data packet; The weight of the logical layer link should reflect the transmission capacity of the node; the links of nodes with strong transmission capacity should be assigned higher weights to encourage data packets to be transmitted through these links, thereby improving the transmission efficiency of the overall network; in the network, some nodes are located on the critical path or have a higher degree of connectivity, and the links of these nodes should be assigned higher weights to ensure the connectivity and stability of the network; when some links and nodes in the network are overloaded, the weights are assigned to the links and nodes with low load balancing; by assigning different weights to different links, the data packets are guided to be evenly distributed in the network, thereby improving the reliability and stability of the network.

[0017] Step A5: dynamically adjust the probability index and update the routing information in real time according to the changes in the network status; In step A5, a network monitoring tool is deployed to continuously collect and analyze real-time data of the network and monitor key indicators such as node availability, latency, bandwidth utilization, and packet loss rate; According to the monitored network status, the probability index between nodes is dynamically adjusted; according to the monitored network status, the probability index between nodes is dynamically adjusted; the dynamic adjustment method is specifically as follows: Step 1: Set a reasonable update frequency based on the size, complexity and daily traffic of the network, with the update frequency being once every five minutes; Step 2: At every set 5-minute time interval, the system automatically calculates and updates the probability index of all links and nodes according to the probability index formula in step A2; and uses the data aggregation algorithm to calculate the weighted values ​​of the current and historical indicators; Step 3: When the packet loss rate, delay, bandwidth utilization and other indicators of the monitored link exceed the set threshold, recalculation is triggered; if the packet loss rate of a link often exceeds the standard when under high load, the contribution of the link to the total probability indicator is automatically reduced; Based on business needs and network characteristics, set the threshold of each indicator. The packet loss rate is set to 0.1% to 1%; the delay is set to 50ms; when the bandwidth utilization is set to greater than 85%, optimized traffic scheduling is required; Step 4: Use historical monitoring data and anomaly detection algorithms to predict fluctuations in link status and trigger updates in a timely manner. Then use the isolation forest algorithm to detect anomalies and determine whether link performance is abnormal. A weighted algorithm is used to assign different weights to different network status factors to generate more accurate probability indicators; Once the probability index is updated, the system should immediately recalculate the routing information and determine the best path for the data packet; each node continuously adjusts and updates the routing table based on its own and neighboring node status information.

[0018] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An improved effective routing strategy on a two-layer network, characterized in that: include: Step A1: Build a two-layer network model; Step A2: Calculate the probability index based on the node degree value; Step A3: assign a weight to each link of the physical layer in the two-layer network; Step A4: assign a weight to each link of the logical layer in the two-layer network according to the transmission capacity of the node and the network topology; Step A5: Dynamically adjust the probability index and update the routing information in real time according to the changes in the network status.

2. The improved efficient routing strategy on a dual-layer network according to claim 1, characterized in that: In step A1, the two-layer network structure mainly includes a logical layer and a physical layer, the upper layer is the logical layer, and the lower layer is the physical layer; the nodes in the uppermost logical layer send data packets to the destination node in the network according to the routing table determined in the logical layer; any link connecting two nodes in the upper logical layer corresponds to the physical path between two nodes in the lower physical layer; the lower physical layer sends the data packets in the network from the source node in the upper logical layer to the destination node according to the determined routing table of the physical layer.

3. The improved efficient routing strategy on a dual-layer network according to claim 1, characterized in that: In step A2, the probability that a data packet in the network can smoothly pass through a node is calculated using the degree value of the node in the network as a cost function. The calculation method of the probability degree index is specifically as follows: ,in, It is expressed as a probability index, Represented as the degree value of the node, Represented as a variable parameter.

4. The improved efficient routing strategy on a dual-layer network according to claim 1, characterized in that: In step A3, at the physical layer, from node To Node The path can be marked as And assign weights to the two connected nodes and The edge between two nodes on the physical layer in the two-layer network is calculated as follows: ,in, Represented as a node and nodes The weight of the edge between Expressed as a node The probability index when Represented as a node The probability index of time.

5. The improved efficient routing strategy on a dual-layer network according to claim 4, characterized in that: In the two-layer network physical layer, from the node To Node The specific method for calculating the path weight is as follows: ,in, Represented as a slave node To Node The path weight, Represented as a slave node To Node The weight of the edge; n represents the path length, Represented as a sequence of nodes on a path.

6. The improved efficient routing strategy on a dual-layer network according to claim 1, characterized in that: In step A4, the upper logical layer is responsible for generating data packets, and the lower physical layer is responsible for receiving and sending data packets in the network; in the entire two-layer network, the data packets in the network will choose the hub node in the network to perform the transmission task with a high probability; therefore, the routing table of the upper logical layer needs to bypass the hub node in the network to effectively improve the transmission capacity of the two-layer network; in the upper logical layer, the two connection nodes and The specific method for calculating the edge weight between is: ,in, Represented as a node and Assign weights to the edges between Represented as a node The probability index when Represented as a node The probability index when Represented as a node and The additional weight between .

7. The improved efficient routing strategy on a dual-layer network according to claim 6, characterized in that: Slave Node To Node The specific calculation method of the path weight is: ,in, Represented as a node To Node The path weight, Represented as a slave node To Node The weight of the edge, n represents the path length, a represents the variable parameter, Represented as a sequence of nodes on a path.

8. The improved efficient routing strategy on a dual-layer network according to claim 1, characterized in that: In step A5, a network monitoring tool is deployed to continuously collect and analyze real-time data of the network and monitor key indicators such as node availability, latency, bandwidth utilization, and packet loss rate; According to the monitored network status, the probability index between nodes is dynamically adjusted; the dynamic adjustment method is as follows: Step 1: Set a reasonable update frequency based on the size, complexity and daily traffic of the network, with the update frequency being once every five minutes; Step 2: At every set 5-minute time interval, the system automatically calculates and updates the probability index of all links and nodes according to the probability index formula in step A2; and uses the data aggregation algorithm to calculate the weighted values ​​of the current and historical indicators; Step 3: When the packet loss rate, delay, bandwidth utilization and other indicators of the monitored link exceed the set threshold, recalculation is triggered; if the packet loss rate of a link often exceeds the standard when under high load, the contribution of the link to the total probability indicator is automatically reduced; Based on business needs and network characteristics, set the threshold of each indicator. The packet loss rate is set to 0.1% to 1%; the delay is set to 50ms; when the bandwidth utilization is set to greater than 85%, optimized traffic scheduling is required; Step 4: Use historical monitoring data and anomaly detection algorithms to predict fluctuations in link status and trigger updates in a timely manner; then use the isolation forest algorithm to detect anomalies and determine whether link performance is abnormal.

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