A path evaluation method based on SRv6 deterministic network

Abstract

This application relates to a service path evaluation method based on an SRv6 deterministic network, comprising the following steps: defining key QoS attributes of the required service according to ITU standards; calculating the evaluation weights of each QoS and path cost of the service; calculating the service request time for each time period; calculating the final service cost of each path; and using an improved Topsis method to evaluate and rank all path methods and select the optimal path. By evaluating and ranking all path methods using the improved Topsis method, the optimal path selection for a specific service can be achieved in an SRv6 deterministic network.

Description

Technical Field

[0001] The present application relates to the field of service path selection, and in particular to a path evaluation method based on SRv6 deterministic network. Background Art

[0002] With the rapid development of the Internet in recent decades, the types of network services have continued to increase. Because different types of network services have different QoS requirements, Internet Service Providers (ISPs) face new challenges: providing differentiated network resources while also enabling customized networks. This demand for customized networks poses new challenges to network programmability.

[0003] SDN is a new network architecture proposed by Stanford University. It separates the data plane from the control plane and enables network programmability. SRv6 is a specific implementation of segment routing in the IPv6 forwarding plane. SRv6 offers all the advantages of segment routing while leveraging the programmability and scalability of the IPv6 extension header. The programmable data plane increases the programmability of the network data plane, enabling programmable switches to perform a series of processing on packets.

[0004] The reliability of IP networks is a classic research issue in the field of computer networks. The main research content is to ensure the uninterrupted transmission of data. Existing fault protection methods include fast reroute and network backup. Fast reroute refers to the calculation of the recovery path before the failure occurs. When a failure occurs, the data flow will be sent directly to the recovery path. Current fast reroute technologies include loop-free backup (LFA), remote loop-free backup (RLFA), and topology-independent loop backup (TI-LFA) algorithms. The TI-LFA mechanism supported by SRv6 is based on the segment routing model. Compared with LFA and RLFA, TI-LFA uses the source routing characteristics of segment routing to achieve topology-independent loop-free backup. However, TI-LFA only randomly selects the Q node closest to the protected node, which cannot meet the QoS requirements of the data flow.

[0005] In this context, deterministic network architecture is considered a key driver of this new trend. While ensuring path QoS quality, it can also provide deterministic, reliable paths for required services. Therefore, given the varying QoS requirements of each service, the system uses the required QoS quality to rate and score the service, calculating the evaluation weights for each QoS and path cost. A fitting function is derived by fitting the service request volume over different time periods, and the service request time for each period is calculated. The final service cost for each path is calculated by taking the cost of each path node and combining it with the service request time. Finally, an improved Topsis method is used to evaluate and rank all path methods, enabling optimal path selection for a specific service in an SRv6 deterministic network. Summary of the Invention

[0006] The purpose of the embodiments of the present application is to provide a service path evaluation method based on an SRv6 deterministic network. By using an improved Topsis method to evaluate and rank all path methods, the optimal path selection can be achieved for a specific service in an SRv6 deterministic network.

[0007] To achieve the above objectives, this application provides the following technical solutions:

[0008] This embodiment of the present application provides a service path evaluation method based on an SRv6 deterministic network, which selects different paths according to different QoS requirements of the service, including the following steps:

[0009] Step 1: Define the key QoS attributes of the required service, including bandwidth, latency, jitter, and packet loss rate, based on ITU standards.

[0010] Step 2: The importance of each QoS indicator is scored based on the QoS quality required by the service, and mapped to a triangular fuzzy value. The evaluation weights of each QoS and path cost of the service are calculated based on this value.

[0011] Step 3: Obtain the fitting function by fitting the service request volume in different time periods, and calculate the service request time in each time period;

[0012] Step 4: Calculate the final service cost of each path based on the service request time of each time period and the cost of each path node obtained in step 3;

[0013] Step 5: Based on the QoS evaluation weight of each path obtained in step 2 and the service cost obtained in step 4, use the improved Topsis method to evaluate and rank all path methods and select the optimal path;

[0014] The evaluation matrix EM in step 2 is:

[0015]

[0016] e x,y Indicates the importance of indicator x to indicator y in the service, and its value is the corresponding triangular fuzzy number, e x,y and e y,x are fuzzy numbers relative to each other.

[0017] In step 5, the global best and worst values ​​of each attribute are selected to form the best and worst points. The distance between the points corresponding to each path solution is then calculated:

[0018]

[0019] qos i represents the bandwidth, delay, jitter, and packet loss rate of the i-th path in DM, as well as the cost calculated above, best i Indicates the best value, worst i Indicates the worst value and calculates the Topsis of each solution C value

[0020]

[0021] With the largest Topsis C The path to the value is optimal.

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] 1. Rating and scoring the QoS requirements of services is used to calculate the evaluation weights of each QoS and path cost of the service. These weights can be used to better customize path plans for various services.

[0024] 2. Using an improved Topsis method, all path methods are evaluated and ranked, enabling optimal path selection for a specific service in an SRv6 deterministic network. This incorporates path cost calculation, facilitating traffic control engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 This is a flow chart of the method of this application. DETAILED DESCRIPTION

[0027] The technical solutions in the embodiments of the present application will be described below in conjunction with the accompanying drawings. It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0028] The terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0029] The following combination Figure 1 The specific implementation of the present invention is a path evaluation method based on an SRv6 deterministic network, which includes the following specific steps:

[0030] Step 1: Based on ITU standards, key QoS attributes of a service, such as network bandwidth, latency, jitter, packet loss rate, and cost, are calculated. Primary and secondary attributes represent the primary and secondary factors that affect user experience, respectively. Cost represents the cost level that the service incurs when using a specific path.

[0031] Step 2: Use triangular fuzzy numbers to score the relative importance of each QoS. Triangular fuzzy numbers are represented as (a, b, c), where a represents the lower bound of the fuzzy number, c represents the upper bound, and b represents the most likely value. The relative importance of each QoS indicator can be described as "relatively very important," "relatively important," "equally important," "relatively unimportant," and "relatively very unimportant." The importance of QoS indicators can be described using triangular fuzzy numbers, and the mapping relationship is shown in Table 1.

[0032] The formula of the evaluation matrix EM is

[0033] e x,y Indicates the importance of indicator x to indicator y in the service, and its value is the corresponding triangular fuzzy number. x,y and e y,x are fuzzy numbers relative to each other.

[0034] Table 1

[0035] QoS indicator relative importance score triangular fuzzy numbers Relatively important (0,0,0.25) Relatively important (0,0.25,0.5) Equally important (0.25,0.5,0.75) Relatively unimportant (0.5,0.75,1) Relatively unimportant (0.75,1,1

[0036] In order to determine the weight of each QoS in the service, first, each dimension of the EM matrix is ​​extracted into a separate matrix (A, B, C):

[0037]

[0038] Next, calculate the LESS, MIDDLE, and UPPER arrays

[0039]

[0040] Then, take a value from LESS, MIDDLE, and UPPER and sort them into a row of the matrix M. In each row, less is the smallest number, middle is the middle number, and upper is the largest number.

[0041] Then select any row in M, denoted as M x =(less x ,middle x ,upper x ), to calculate C Number :

[0042]

[0043] Finally, we get a matrix C with m rows and m-1 columns. Result :

[0044]

[0045] Select C Result The minimum value of each row in generates vector C Min :

[0046] C Min =(min1,min2,…,min m )

[0047] Finally, the weights of the indicators are normalized to obtain the normalized weight vector of each indicator:

[0048]

[0049] Step 3: To quantitatively describe the popularity of network usage in different periods, it is necessary to fit the network user data to obtain the time-division function F(x). After obtaining the fitted function, the deviation normalization method is used to normalize it to obtain the service request time for each period:

[0050]

[0051] Among them, F(x) min represents the minimum value of F(x), and F(x) max Represents the maximum value of F(x).

[0052] Step 4: Calculate the path cost, mainly considering the QoS value and node computing resource cost N The normalized values ​​of the primary and secondary attributes are used to calculate the overhead factor, expressed as

[0053]

[0054] Based on the QoS parameters and cost factors related to SRv6 deterministic networks, the QoS & Cost matrix of all paths can be generated.

[0055] Step 5: The improved Topsis method is used to evaluate each path. First, the global best and worst values ​​of each attribute are selected to form the best point and the worst point. Then the distance between the points corresponding to each path solution is calculated:

[0056]

[0057]

[0058] qos i represents the bandwidth, delay, jitter, and packet loss rate of the i-th path in DM, as well as the cost calculated above, best i Indicates the best value, worst i Indicates the worst value.

[0059] Calculate the Topsis for each solution C value

[0060]

[0061] With the largest Topsis C The value of the path is optimal, providing the best list of SRv6 segments to satisfy the service request.

[0062] Compared to existing technologies, this paper proposes a service path evaluation method based on SRv6 deterministic networks. First, according to ITU standards, the key QoS attributes of the required services are defined. The service's required QoS is scored and the evaluation weights of each service's QoS and path cost are calculated. A fitting function is obtained by fitting the service request volume in different time periods, and the service request time for each time period is calculated. The final service cost of each path is calculated by obtaining the cost of each path node and combining it with the service request time. All path methods are evaluated and ranked using an improved Topsis method, thereby achieving the optimal path selection for a specific service in an SRv6 deterministic network.

[0063] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A service path evaluation method based on SRv6 deterministic network, characterized in that: Selecting different paths based on the different QoS requirements of the service includes the following steps: Step 1: Define the key QoS attributes of the required service, including bandwidth, latency, jitter, and packet loss rate, based on ITU standards. Step 2: The importance of each QoS indicator is scored based on the QoS quality required by the service, and mapped to a triangular fuzzy value. The evaluation weights of each QoS and path cost of the service are calculated based on this value. Step 3: Obtain the fitting function by fitting the service request volume in different time periods, and calculate the service request time in each time period; Step 4: Calculate the final service cost of each path based on the service request time of each time period and the cost of each path node obtained in step 3; Step 5: Based on the QoS evaluation weight of each path obtained in step 2 and the service cost obtained in step 4, use the improved Topsis method to evaluate and rank all path methods and select the optimal path; The evaluation matrix EM in step 2 is ， Indicator For indicators in this service The importance of , whose value is the corresponding triangle fuzzy number, and are fuzzy numbers relative to each other.

2. A service path evaluation method based on SRv6 deterministic network according to claim 1, characterized in that: In step 5, the global best and worst values ​​of each attribute are selected to form the best point and the worst point, and then the distance between the points corresponding to each path solution is calculated: ， Generate a QoS & Cost matrix for all paths based on QoS parameters and cost factors related to SRv6 deterministic networks , represents the parameters of the i-th path in DM, represents the optimal value, Indicates the worst value and calculates the value ， With the maximum The path to the value is optimal.

Images