A network resource re-allocation method

Abstract

The application relates to a network resource redistribution method, and belongs to the technical field of network switching. The method comprises the following steps: initializing system parameters; when entering a path maintenance period, setting a current path serial number, entering a path of the current serial number; traversing all current paths generated based on a bisection firefly optimization method, and performing path maintenance on the current paths; checking the states of nodes in the current paths, if there is a failed node, adopting a network resource scheduling method based on the bisection firefly optimization method to perform resource redistribution of the failed node; checking the states of links in the current paths, if there is a failed link or a congested link, regarding the failed link or the congested link as a failed link, and adopting the network resource scheduling method based on the bisection firefly optimization method to perform resource redistribution of the failed link; and re-entering the cycle until the system ends work. The application solves the problem that a resource scheduling strategy cannot be locally corrected when the resource scheduling strategy is invalid.

Description

Technical Field

[0001] This application relates to the field of network switching technology, and in particular to a method for reallocating network resources. Background Technology

[0002] During network operation, resource scheduling strategies are typically calculated under specific network topology, node states, and link conditions. However, when the network environment undergoes dynamic changes—such as frequent topology changes, damage or disconnection of some nodes, external interference to links, or channel congestion or even outages—the original resource scheduling strategies often become inapplicable and cannot continue to guarantee stable network operation and efficient utilization. In such cases, network resources must be reallocated.

[0003] Existing technologies, especially in resource scheduling scenarios using intelligent algorithms, often involve complex optimization calculations and model inference during the global recalculation process, consuming significant processor computing power. This significantly increases the energy consumption of network devices and can even lead to a decline in overall system performance, making it unbearable in practical applications. Regardless of whether existing technologies employ traditional non-machine learning scheduling methods or advanced scheduling methods relying on intelligent algorithms such as deep learning and reinforcement learning, most resource reallocation methods typically discard the original scheduling strategy and recalculate globally to generate a new scheduling scheme. However, this approach has significant drawbacks: when resource scheduling strategies fail, network topology changes rapidly. If every change triggers a complete recalculation process, it is impossible to make fine-grained dynamic adjustments to resource scheduling within a local scope, lacking flexibility. Therefore, in application scenarios with scarce resources, limited energy, and limited computing power, it often exhibits problems such as untimely response, low resource utilization, and excessive energy consumption, making it difficult to meet the practical application requirements for high efficiency, low energy consumption, and real-time performance. Summary of the Invention

[0004] This application provides a network resource reallocation method that can solve the problems of poor flexibility and high consumption of computing resources and energy when resource scheduling strategies fail due to the inability to make local adjustments.

[0005] To achieve the above objectives, according to a first aspect of this application, a network resource reallocation method is provided, the method comprising the following steps: S1. Enter the path maintenance cycle, set the current path number, and enter the path with the current number; S2. Generate a rescheduled path for the path with the current sequence number; S3. Check the status of each node in the scheduled path. If there are failed nodes, reallocate the resources of the failed nodes. S4. Check the status of each link in the scheduled path. If there is a failed link or a congested link, treat the failed link or congested link as a failed link and reallocate the failed link resources. S5. Re-enter S1 until there is no longer a need to reallocate resources for failed nodes and failed links.

[0006] Optionally, before entering S2, the process further includes: system initialization, wherein the parameters for system initialization include the current path. Failure Node Count Threshold Failed link number threshold Number of sub-path adjustments .

[0007] Furthermore, S3 includes the following steps: S301, Number of failed nodes detected along the path ; S302, if If the condition is met, proceed to S303; otherwise, proceed to S304. S303. The current service path is determined to be a failed path. The service path is regenerated using a network resource scheduling method based on the binary moth optimization method, and the current resource reallocation ends. S304, Read all failed nodes in the path respectively The previous node in and the next node Obtain the set of adjusted nodes ; S305, Adjust the node set as described above. The local path marker matrix of the failed node is obtained based on the business fitness weight multi-sampling method. ,in ; S306. Initialize local path number ; S307, Configure Sub-Source Nodes and sub-target nodes To obtain the local path ,in For matrix Line 1, page q Column elements, and so on; S308, using local paths Replace path Sub-paths between the same nodes are used to obtain the adjusted path. ; S309, if the adjustment path There are two or more identical nodes If the condition is met, proceed to S310; otherwise, proceed to S311. S310. Delete the path between the first and last nodes, keeping only one node. Enter S309; S311, if ,but If the condition is met, proceed to S307; otherwise, proceed to S312. S312. Complete the calculation of all adjustment paths and select the adjustment path with the best business adaptability. Replace path .

[0008] Furthermore, the steps for generating the local path are as follows: Specify the source and destination nodes, and use the remaining TTL (Time To Live) of the packets as the maximum path length. A local path is generated using a network resource scheduling method based on the binary moth optimization algorithm. The remaining TTL (Time To Live) of packets is calculated by the following formula:

[0009] in For path Remove nodes and nodes The length of the remaining path between the nodes and nodes These are the source and destination nodes specified for this local path, respectively. This refers to the corresponding path to which this local path belongs.

[0010] Furthermore, the service adaptability of S312 is calculated according to the following formula:

[0011] in , , and These are the latency coefficient, bandwidth coefficient, packet loss coefficient, and jitter coefficient, respectively. , , and These are the business paths. j The delay function, bandwidth function, packet loss function, and jitter function.

[0012] Furthermore, the time delay function of S312 Bandwidth function Packet loss function and jitter function Defined by the following formulas respectively:

[0013]

[0014]

[0015]

[0016] in , , and All are coefficients greater than 0. , , and Paths The Middle The latency, bandwidth, packet loss rate, and jitter of each node. For path The total number of nodes in the middle.

[0017] Furthermore, S305 includes the following steps: S3051. Calculate the average service fitness of local paths:

[0018]

[0019]

[0020]

[0021] in, For path Average business adaptability For path The number of jumps, For path Middle node With nodes The path between, and the nodes With nodes Cannot be used as a path at the same time The source node and the destination node; S3052. Select the option with the highest business adaptability. Local paths ,in Used to label the business adaptability ranking sequence number; S3053. The adjusted local path marker matrix is ​​obtained according to the following formula. : .

[0022] Furthermore, S4 includes the following steps: S401, Number of failed paths detected ; S402, if If the condition is met, proceed to S403; otherwise, proceed to S404. S403, Change the current business path j If the path is determined to be invalid, the network resource scheduling method based on the binary moth optimization method is used to regenerate the service path, and the current resource reallocation ends. S404, Read all failed links on the path respectively Middle front-end node Backend nodes Front-end nodes and backend nodes To obtain the adjusted node set ; S405, Adjust the node set as described above. The local path flag matrix is ​​obtained based on the business fitness weight multi-sampling method. ; S406. Initialize local path sequence number ; S407, Set Sub-Source Node and sub-target nodes To obtain the local path ; S408, using local paths Replace path Sub-paths between the same nodes are used to obtain the adjusted path. ; S409, if the adjustment path There are two or more identical nodes If the condition is met, proceed to S410; otherwise, proceed to S411. S410. Delete the path between the first and last nodes, keeping only one node. Enter S409; S411, if ,but If the condition is met, proceed to S407; otherwise, proceed to S412. S412. Complete the calculation of all adjustment paths and select the adjustment path with the best business adaptability. Replace path .

[0023] Furthermore, step S405 includes the following steps: S4051. Calculate the average service fitness of local paths:

[0024]

[0025]

[0026]

[0027]

[0028]

[0029]

[0030] The aforementioned local path is not a path. ; S4052. Select the option with the highest business adaptability. Local paths superscript ; S4053. The local path marker matrix is ​​obtained according to the following formula. : .

[0031] To achieve the above objectives, according to a second aspect of this application, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the steps of the network resource reallocation method as described in the first aspect.

[0032] This application proposes a network resource reallocation method based on the binary moth optimization algorithm. When the resource scheduling strategy fails, addressing issues such as link disconnection, link congestion, and node failure in already generated paths, the method employs resource reallocation for failed nodes and links based on the binary moth optimization algorithm to reallocate network resources. Then, a local path is generated and integrated with the original path to form a new path. The method described in this application can modify the resource scheduling strategy according to changing network conditions without requiring rescheduling. Attached Figure Description

[0033] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0034] Figure 1This is a flowchart illustrating the network resource reallocation method based on the binary moth optimization algorithm provided in this application. Figure 2 This is a flowchart illustrating the resource reallocation process for failed nodes provided in this application; Figure 3 A flowchart illustrating the process of obtaining the local path marker moments of failed nodes using the business fitness weighted multi-sampling method provided in this application; Figure 4 This is a schematic diagram illustrating an example provided in this application. Detailed Implementation

[0035] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0036] like Figure 1 A binary moth optimization method for network resource reallocation includes the following steps: S1. Initialize system parameters, including the current path. Failure Node Count Threshold Failed link number threshold Number of sub-path adjustments ; S2. When entering the path maintenance cycle, set the current path number and enter the path with the current number; S3. Traverse all current paths generated based on the binary moth optimization method, and maintain the path index of each current path. ; S4. Check the current path If there are failed nodes, a network resource scheduling method based on the binary moth optimization method is used to reallocate the resources of the failed nodes. S5. Check the current path If there is a failed link or a congested link in each link status, the failed link or congested link is regarded as a failed link, and the network resource scheduling method based on the binary moth optimization method is used to reallocate the resources of the failed link. S6, re-enter S2, until the system finishes working.

[0037] like Figure 2 As shown, the specific workflow for resource reallocation of failed nodes in S4 is as follows: S401, Number of failed nodes detected along the path ; S402, if If the condition is met, proceed to S403; otherwise, proceed to S404. S403. If the current service path is determined to be a failed path, the service path is regenerated using a network resource scheduling method based on the binary moth optimization method, and the current resource reallocation ends. S404, Read all failed nodes in the path respectively The previous node in and the next node Obtain the adjusted node set:

[0038] S405, Adjust the node set as described above. The local path marker matrix of the failed node is obtained based on the business fitness weight multi-sampling method. ,in ; S406. Initialize local path sequence number ; S407, Set Sub-Source Node and sub-target nodes To obtain the local path ,in For matrix Line 1, page q Column elements, and so on; S408, using local paths Replace path Sub-paths between the same nodes are used to obtain the adjusted path. ; S409, if the adjustment path There are two or more identical nodes If the condition is met, proceed to S410; otherwise, proceed to S411. S410. Delete the path between the first and last nodes, keeping only one node. Enter S409; S411, if ,but If the condition is met, proceed to S407; otherwise, proceed to S412. S412. Complete the calculation of all adjustment paths and select the adjustment path with the best business adaptability. Replace path .

[0039] Furthermore, the steps for generating the local path are as follows: Specify the source and destination nodes, and use the remaining TTL (Time To Live) of the packets as the maximum path length. A local path is generated using a network resource scheduling method based on the binary moth optimization algorithm. The remaining TTL (Time To Live) of packets is calculated by the following formula:

[0040] in For path Remove nodes and nodes The length of the remaining path between the nodes and nodes These are the source and destination nodes specified for this local path, respectively. This refers to the corresponding path to which this local path belongs.

[0041] Furthermore, the service adaptability of S412 is calculated according to the following formula:

[0042] in , , and These are the latency coefficient, bandwidth coefficient, packet loss coefficient, and jitter coefficient, respectively. , , and These are the business paths. j The delay function, bandwidth function, packet loss function, and jitter function are defined by the following formulas:

[0043]

[0044]

[0045]

[0046] in , , and All are coefficients greater than 0. , , and Paths The Middle The latency, bandwidth, packet loss rate, and jitter of each node. For path The total number of nodes. The latency function measures the real-time performance of the service path, providing a basis for path selection; the bandwidth function serves as an optimization target during resource allocation, avoiding path overload and ensuring maximum utilization of link resources; the packet loss function measures the reliability of the service path and is a key indicator in resource scheduling; the jitter function measures the smoothness of transmission, ensuring transmission continuity. Through these four functions, this application can more precisely evaluate and select service paths.

[0047] like Figure 3 As shown in S405, the local path flag matrix of the failed node is obtained based on the business fitness weight multi-sampling method. Includes the following steps: S4051. Calculate the average service fitness of local paths:

[0048]

[0049]

[0050]

[0051] in, For path Average business adaptability For path The number of jumps, For path Middle node With nodes The path between, and nodes With nodes Cannot be used as a path at the same time The source node and the destination node; S4052. Select the option with the highest business adaptability. Local paths ,in Used to label the business adaptability ranking sequence number; S4053. The local path marker matrix is ​​obtained according to the following formula. : .

[0052] Furthermore, S5 includes the following steps: S501, Number of failed paths detected ; S502, if If the condition is met, proceed to S503; otherwise, proceed to S504. S503, Change the current business path jIf the path is determined to be invalid, the network resource scheduling method based on the binary moth optimization method is used to regenerate the service path, and the current resource reallocation ends. S504, Read all failed links on the path respectively Middle front-end node Backend nodes Front-end nodes and backend nodes The adjusted node set is obtained as follows:

[0053] S505, Adjust the node set as described above. The local path flag matrix is ​​obtained based on the business fitness weight multi-sampling method. ; S506. Initialize local path sequence number ; S507, Configure Sub-Source Nodes and sub-target nodes To obtain the local path ; S508, using local paths Replace path Sub-paths between the same nodes are used to obtain the adjusted path. ; S509, if the adjustment path There are two or more identical nodes If the current state is not specified, proceed to S510; otherwise, proceed to S511. S510. Delete the path between the first and last nodes, keeping only one node. Enter S509; S511, if ,but If the condition is met, proceed to S507; otherwise, proceed to S512. S512. Complete the calculation of all adjustment paths and select the adjustment path with the best business adaptability. Replace path .

[0054] Furthermore, step S505 includes the following steps: S5051. Calculate the average service fitness of local paths:

[0055]

[0056]

[0057]

[0058]

[0059]

[0060]

[0061] The aforementioned local path is not a path. ; S5052. Select the option with the highest business adaptability. Local paths superscript ; S5053. The adjusted local path flag matrix is ​​obtained according to the following formula. : .

[0062] The present invention will be illustrated by the following examples.

[0063] Combination Figure 4 The example shown is a network system with 8 nodes. Assuming the TTL (Time To Live) of a packet is 7, the path... If you need to access the nodes and The path is recalculated, i.e., a local path is generated, then the child source node is... The sub-destination node is The remaining TTL (Time To Live) message lifespan is 5.

[0064] Taking the above system as an example, we will illustrate the resource reallocation of failed nodes. , For the path If node , and If a node fails, resources on the failed node will be reallocated. Read the nodes separately. and The previous node and the next node The adjusted node set is obtained as follows:

[0065] Calculate local path , , , and The average business fitness, if obtained:

[0066] Then adjust the local path flag matrix. for:

[0067] against Generate respectively and , and , and The local paths between them yield:

[0068] After integrating this local path, Since there are duplicate nodes, after deletion we get... .

[0069] Similarly, targeting ,get ;against ,get .

[0070] Finally, from the path and Select the path with the best business adaptability as the resource reallocation path. .

[0071] Similarly Figure 4 The system shown is used as an example to illustrate the reallocation of resources on failed links. , For the path If node and Links and nodes between and If a link between nodes fails, resources on the failed link will be reallocated. Read the data from the front-end nodes respectively. Backend nodes Front-end nodes Backend nodes To obtain the adjusted node set as follows:

[0072] Calculate local path , , , , , , , , , and The average business fitness, if obtained:

[0073] Then adjust the local path flag matrix. for:

[0074] against Generate respectively and , and The local path between them, if we get:

[0075] After integrating this local path, we get .

[0076] Similarly, targeting ,get ;against ,get .

[0077] Finally, from the path and Select the path with the best business adaptability as the resource reallocation path. .

[0078] This application also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements each step of the aforementioned optimization method and can achieve the same beneficial effects as the aforementioned optimization method. To avoid repetition, it will not be described again here.

[0079] In the embodiments provided in this application, it should be understood that the disclosed methods and apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0080] Furthermore, the functional units in the embodiments of this application can be integrated into one processing unit, or each unit can be physically comprised separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0081] The above description is the preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principles described in this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for reallocating network resources, characterized in that, The method includes the following steps: S1. Enter the path maintenance cycle, set the current path number, and enter the path with the current number; before entering S2, it also includes: system initialization, the parameters of which include the current path. Failure Node Count Threshold Failed link number threshold Number of sub-path adjustments ; S2. Generate a rescheduled path for the path with the current sequence number; S3. Check the status of each node in the scheduled path. If there are failed nodes, reallocate the resources of the failed nodes. S3 includes the following steps: S301, Number of failed nodes detected along the path ; S302, if If the condition is met, proceed to S303; otherwise, proceed to S304. S303. The current service path is determined to be a failed path. The service path is regenerated using a network resource scheduling method based on the binary moth optimization method, and the current resource reallocation ends. S304, Read all failed nodes in the path respectively The previous node in and the next node Obtain the set of adjusted nodes ; S305, Adjust the node set as described above. The local path marker matrix of the failed node is obtained based on the business fitness weight multi-sampling method. ,in ; S306. Initialize local path number ; S307, Configure Sub-Source Nodes and sub-target nodes To obtain the local path ,in For matrix Line 1, page q Column elements, and so on; S308, using local paths Replace path Sub-paths between the same nodes are used to obtain the adjusted path. ; S309, if the adjustment path There are two or more identical nodes If the condition is met, proceed to S310; otherwise, proceed to S311. S310. Delete the path between the first and last nodes, keeping only one node. Enter S309; S311, if ,but If the condition is met, proceed to S307; otherwise, proceed to S312. S312. Complete the calculation of all adjustment paths and select the adjustment path with the best business adaptability. Replace path ; S4. Check the status of each link in the scheduled path. If there is a failed link or a congested link, treat the failed link or congested link as a failed link and reallocate the failed link resources. S5. Re-enter S1 until there is no longer a need to reallocate resources for failed nodes and failed links.

2. The network resource reallocation method according to claim 1, characterized in that, The steps for generating the local path are as follows: Specify the source and destination nodes, and use the remaining TTL (Time To Live) of the packets as the maximum path length. A local path is generated using a network resource scheduling method based on the binary moth optimization algorithm. The remaining TTL (Time To Live) of packets is calculated by the following formula: in For path Remove nodes and nodes The length of the remaining path between the nodes and nodes These are the source and destination nodes specified for this local path, respectively. This refers to the corresponding path to which this local path belongs.

3. The network resource reallocation method according to claim 2, characterized in that, The service adaptability of S312 is calculated according to the following formula: in , , and These are the latency coefficient, bandwidth coefficient, packet loss coefficient, and jitter coefficient, respectively. , , and These are the business paths. j The delay function, bandwidth function, packet loss function, and jitter function.

4. The network resource reallocation method according to claim 3, characterized in that, The time delay function of S312 Bandwidth function Packet loss function and jitter function Defined by the following formulas respectively: in , , and All are coefficients greater than 0. , , and Paths The Middle The latency, bandwidth, packet loss rate, and jitter of each node. For path The total number of nodes in the middle.

5. The network resource reallocation method according to claim 4, characterized in that, S305 includes the following steps: S3051. Calculate the average service fitness of local paths: in, For path Average business adaptability For path The number of jumps, For path Middle node With nodes The path between, and the nodes With nodes Cannot be used as a path at the same time The source node and the destination node; S3052. Select the option with the highest business adaptability. Local paths ,in Used to label the business adaptability ranking sequence number; S3053. The local path marker matrix is ​​obtained according to the following formula. : 。 6. The network resource reallocation method according to claim 5, characterized in that, S4 includes the following steps: S401, Number of failed paths detected ; S402, if If the condition is met, proceed to S403; otherwise, proceed to S404. S403, Change the current business path j If the path is determined to be invalid, the network resource scheduling method based on the binary moth optimization method is used to regenerate the service path, and the current resource reallocation ends. S404, Read all failed links on the path respectively Middle front-end node Backend nodes Front-end nodes and backend nodes To obtain the adjusted node set ; S405, Adjust the node set as described above. The local path flag matrix is ​​obtained based on the business fitness weight multi-sampling method. ; S406. Initialize local path sequence number ; S407, Configure Sub-Source Node and sub-target nodes To obtain the local path ; S408, using local paths Replace path Sub-paths between the same nodes are used to obtain the adjusted path. ; S409, if the adjustment path There are two or more identical nodes If the current state is not specified, proceed to S410; otherwise, proceed to S411. S410. Delete the path between the first and last nodes, keeping only one node. Enter S409; S411, if ,but If the condition is met, proceed to S407; otherwise, proceed to S412. S412. Complete the calculation of all adjustment paths and select the adjustment path with the best business adaptability. Replace path .

7. The network resource reallocation method according to claim 6, characterized in that, Step S405 includes the following steps: S4051. Calculate the average service fitness of local paths: The aforementioned local path is not a path. ; S4052. Select the option with the highest business adaptability. Local paths superscript ; S4053. The local path flag matrix is ​​obtained according to the following formula. : 。 8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, it implements the steps of the network resource reallocation method as described in any one of claims 1-7.

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