Network health assessment method and device for financial cloud backbone network

Abstract

The present invention provides a method and device for evaluating the network health of a financial cloud backbone network. The method comprises: determining the traffic of different paths between a head office and branches in the financial cloud backbone network, and determining the level of the traffic of different paths according to the bandwidth overhead required by the determined traffic of different paths; the different paths include a main path and a protection path corresponding to the main path; based on the determined level of the traffic of different paths, calculating the network reliability and network carrying capacity of each level of traffic in different paths between each head office and each branch; calculating the health of each level of traffic based on the calculated network reliability and network carrying capacity, and summing the calculated health of each level of traffic to obtain the network health of each level of traffic; performing weighted summation based on the obtained network health of each level of traffic to obtain the network health of the overall network.

Description

Technical Field

[0001] The present invention relates to the technical field of network health assessment, and particularly to a method and device for assessing the network health of a financial cloud backbone network. Background Art

[0002] The financial cloud backbone network currently generally adopts an architecture of "two places and three centers". As Figure 1 shown, network services are mainly concentrated in the head office data centers (such as data centers A, B, and C in the figure) and the first-level branch data centers. Users are widely distributed at various levels inside and outside the bank. Each local branch accesses the head office data center through the backbone network. The P (Provider) devices in the same city (such as core routers) are interconnected through wavelength division or bare optical fibers. The P devices include WAN-P devices, DC-P devices, etc. The P devices in different places and between the first-level branch PE (Provider equip) devices (such as edge routers) and the data centers are interconnected through leased lines of the operator's MSTP (Multi-Service Transfer Platform, an SDH-based multi-service transmission platform). The PE devices include BR-PE devices, DC-PE devices, etc. All the PE and P devices in the data centers and the PE devices in the first-level branches form the backbone network, and the data traffic between the head office and the branches is propagated through the backbone network.

[0003] In order to improve its own revenue, the network operator hopes to ensure the reliability of services while effectively carrying the service traffic in the financial backbone network. In the financial cloud backbone network, whether the service traffic is effectively carried and whether the service provided to the service is reliable are closely related to the network policies defined by the operator. In order to indicate whether the network policies defined by the operator are effective, we need to evaluate the state of the network under the current policies to provide guidance for the operator on whether to change its network policies.

[0004] The existing network assessment schemes mainly evaluate the network from the perspectives of topology, traffic, and resources. When evaluating the network from the topology perspective, only the topological characteristics of the network are considered while ignoring the characteristics of network resources and traffic itself; when evaluating the network from the resource perspective, the performance of the network when carrying traffic is not considered; when evaluating the network from the traffic perspective, the preferences of different types of traffic for resource requirements (such as large bandwidth, low latency, etc.) are ignored. The business types of the financial backbone network are complex and the number of branches is large. It is extremely challenging to comprehensively and effectively evaluate the network quality and service quality. Therefore, in order to indicate whether the network policies defined by the operator are effective, there is an urgent need for a network health assessment method to evaluate the state of the network under the current policies. Summary of the Invention

[0005] In view of this, an embodiment of the present invention provides a method and device for evaluating the network health of a financial cloud backbone network, which helps operators measure whether their current network policies are healthy, provides guidance on whether operators need to change their network policies, and timely changes their network policies to improve the operation speed of the network and bring a better experience to users.

[0006] One aspect of the present invention provides a method for evaluating the network health of a financial cloud backbone network, the method comprising the following steps:

[0007] Determine the traffic of different paths between the head office and branches in the financial cloud backbone network, and determine the level of the different path traffic according to the bandwidth overhead required for the determined different path traffic; the different paths include a main path and a protection path corresponding to the main path, and the protection path is the transmission path of traffic in the network when the main path fails;

[0008] Based on the determined levels of different path traffic, calculate the network reliability and network carrying capacity of each level of traffic on different paths between each head office and each branch; calculate the health of each level of traffic based on the calculated network reliability and network carrying capacity, and sum up the calculated health of each level of traffic to obtain the network health of each level of traffic;

[0009] Perform weighted sum by proportion based on the obtained network health of each level of traffic to obtain the network health of the overall network.

[0010] In some embodiments of the present invention, the calculating the network reliability of each level of traffic on different paths between each head office and each branch includes:

[0011] Calculate the service reliability determined by each main path and the protection path of the main path between each head office and branch according to a predetermined path protection policy;

[0012] Calculate the congestion degree on each main path between each head office and each branch according to the congestion rate of the current path;

[0013] Calculate the network reliability based on the obtained service reliability and congestion degree;

[0014] Wherein, there is a one-to-many correspondence between the main path and the protection path.

[0015] In some embodiments of the present invention, the network carrying capacity is the maximum number of traffic of a predetermined level that can be carried between the main path and the protection path of the head office and branch in the network, and the calculating the network carrying capacity of each level of traffic on different paths between each head office and each branch includes:

[0016] The network carrying capacity is calculated based on the maximum available bandwidth of each main path between each head office and each branch office and the bandwidth overhead required for each level of traffic.

[0017] In some embodiments of the present invention, the health of each level of traffic satisfies the following formula:

[0018]

[0019] where k represents the level of traffic, m represents the head office, n represents the branch office, M represents the set of head offices, N represents the set of branch offices, represents the main path between head office m and branch office n, represents the set of main paths between head office m and branch office n, represents the traffic demand ratio matrix of branch office n to head office m, represents the main path between head office m and branch office n of network reliability, represents the main path between head office m and branch office n for the carrying capacity of k-level traffic.

[0020] In some embodiments of the present invention, the network reliability is obtained by multiplying the service reliability and the congestion degree;

[0021] The service reliability is the probability that at least one of the main path and the protection path opposite to the main path does not fail.

[0022] In some embodiments of the present invention, the congestion degree includes:

[0023] When the variance of the network link congestion rate distribution is less than a predetermined variance value, the congestion degree is the difference between the average link congestion rate of the path and the link congestion threshold;

[0024] When the variance of the network link congestion rate distribution is greater than or equal to the predetermined variance value, the congestion degree is the difference between the maximum link congestion rate of the path and the link congestion threshold.

[0025] In some embodiments of the present invention, the weighted weight is the ratio of the demand traffic of each branch office to each head office.

[0026] In some embodiments of the present invention, the financial cloud backbone network is constructed as an undirected graph model, and the undirected graph is represented as G=(V, E), where V represents the set of nodes and E represents the set of links.

[0027] Another aspect of the present invention provides a network health assessment device for a financial cloud backbone network. The device includes a computer device, which includes a processor and a memory. Computer instructions are stored in the memory, and the processor is configured to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the device implements the steps of the method described above.

[0028] The network health assessment method and device for the financial cloud backbone network provided by the present invention can consider the network's carrying capacity and reliability, perform a weighted sum of the network's carrying capacity and reliability to obtain the network health, to help the operator measure whether the current network strategy is effective, to provide guidance on whether the operator needs to change its network, and to promptly change its network strategy to improve the network operation speed and bring a better experience to users.

[0029] Furthermore, the network health assessment method and device for the financial cloud backbone network provided by the present invention can calculate the network carrying capacity by giving the maximum traffic that different paths between the head office and branches can carry; can calculate the network reliability by the service reliability determined by the path protection mechanism and the network congestion degree; and then, perform a weighted sum based on the obtained network reliability and network carrying capacity to obtain the network health, so as to help the operator measure the current network health status.

[0030] The additional advantages, objectives, and features of the present invention will be partially described below and will become partially apparent to those of ordinary skill in the art after studying the following text, or can be learned from the practice of the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in the description and the drawings.

[0031] Those skilled in the art will understand that the objectives and advantages that can be achieved by the present invention are not limited to the above specific descriptions, and the above and other objectives that the present invention can achieve will be more clearly understood according to the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The drawings described herein are used to provide a further understanding of the present invention, form a part of this application, and do not limit the present invention. In the drawings:

[0033] Figure 1 It is a typical architecture diagram of the financial cloud backbone network.

[0034] Figure 2 It is a schematic diagram showing the difference between the network health assessment and the prior art.

[0035] Figure 3 It is a schematic diagram of the network health assessment method for the financial cloud backbone network in an embodiment of the present invention.

[0036] Figure 4 This is an undirected graph of the financial cloud backbone network in an embodiment of the present invention.

[0037] Figure 5 This is an architecture diagram of the protection path and the main path in an embodiment of the present invention. Detailed implementation manners

[0038] To make the objectives, technical solutions and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the implementation manners and the drawings. Herein, the illustrative implementation manners of the present invention and the descriptions thereof are used to explain the present invention, but not to limit the present invention.

[0039] Herein, it should also be noted that in order to avoid obscuring the present invention with unnecessary details, only the structures and / or processing steps closely related to the solutions of the present invention are shown in the drawings, while other details less relevant to the present invention are omitted.

[0040] It should be emphasized that the term "comprising / including" when used herein refers to the presence of features, elements, steps or components, but does not exclude the presence or addition of one or more other features, elements, steps or components.

[0041] Herein, it should also be noted that if not otherwise specified, the term "connection" herein can refer not only to direct connection, but also to indirect connection with an intermediate.

[0042] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0043] In order to help operators measure whether their current network strategies are effective, that is, whether the current network status is healthy, in the modeling of network health, the present invention takes into account the network's carrying capacity and the network's reliability. Its network carrying capacity considers the maximum number of flows that can be carried between a given head office and branch offices; its network reliability considers the service reliability determined by the path protection mechanism and the network congestion degree. When calculating the health degree at a given traffic level, the network health degree at the given traffic level is obtained by weighted summation according to the traffic ratio between the head office and branch offices. When calculating the overall network health degree, the present invention first considers calculating the health degree of the network under different levels of traffic, and then obtains the overall network health degree by weighted summation, so as to provide guidance for operators on whether they need to change their networks and timely change their network strategies to improve the network operation speed and bring a better experience to users.

[0044] Figure 2 This is a schematic diagram showing the differences between the network health assessment and the prior art, as Figure 2As shown, in existing network evaluation schemes, the network is mainly evaluated from the perspectives of topology, traffic, and resources. When evaluating the network from the topology perspective, only the topological characteristics of the network are considered while ignoring the characteristics of network resources and traffic itself; when evaluating the network from the resource perspective, the performance of the network when carrying traffic is not considered; when evaluating the network from the traffic perspective, the preferences of different types of traffic for resource requirements (such as large bandwidth, low latency, etc.) are ignored; while the network health assessment of the financial cloud backbone network lies in evaluating the performance and reliability of the network when carrying various types of traffic.

[0045] Figure 3 As shown in the following figure, it is a schematic diagram of the network health assessment method for the financial cloud backbone network in an embodiment of the present invention. Figure 3 As shown, the network health assessment method for the financial cloud backbone network includes:

[0046] Step S110, determine the traffic of different paths between the head office and branch offices in the financial cloud backbone network, and determine the level of the different path traffic according to the bandwidth overhead required for the determined different path traffic; the different paths include the main path and the protection path corresponding to the main path.

[0047] In this step, there are multiple paths between the head office and branch offices in the financial cloud backbone network, and the proportion of the traffic of different paths in the total traffic is different. First, determine the traffic of different paths between the head office and branch offices in the network, and then determine the level of the different path traffic according to the bandwidth overhead required for the determined different path traffic, where the different paths are the main path and the protection path corresponding to the main path.

[0048] In an embodiment of the present invention, the "two places and three centers" structure of the financial cloud backbone network is constructed as an undirected graph model. As Figure 4 shown, its undirected graph is represented as G=(V, E), where V represents the set of nodes (such as a, b, c...x, y, z in the figure), E represents the set of links (the paths formed between each node in the figure, such as the a-b path, b-c path...y-z path), and the undirected graph model also includes the head office set. As Figure 4 shown, the head office data center node set (A, B, C), the branch office data center node set (1, 2, 3,..., 4, 5, 6), which is only an example, and the present invention is not limited thereto. In this embodiment, the description of each parameter is shown in Table 1:

[0049] Table 1 Description of the parameters of the undirected graph model of the financial cloud backbone network

[0050]

[0051]

[0052] In some embodiments, the architecture diagram of the protection path and the main path is asFigure 5 As shown, the architecture diagram includes the head office data center node A, the branch data center node 1, and nodes (a, b, c... h, i) that can form paths. As an example, in this architecture diagram, the path a - b - c formed by nodes a, b, and c is the main path, and the paths formed between other nodes are the protection paths of the main path a - b - c. The head office data center node A transmits the traffic in the network to the branch data center node 1 through the main path (a - b - c). When the main path (a - b - c) fails, the traffic in the network will automatically be transmitted to the branch data center node 1 through the protection path (a - d - c) or the protection path (a - d - h - i - e - c) or the protection path (a - f - g - h - d - c) or the protection path (a - f - g - h - i - e - c), protecting the safe and effective transmission of the traffic in the network. The above architecture of the protection path and the main path is only an example, and the present invention is not limited thereto.

[0053] In some embodiments, the levels of different path traffic are determined according to the bandwidth overhead required for the traffic of different paths. The bandwidth overhead can be the bandwidth of the frequency band occupied by the traffic signal on the transmission path or the transmission rate of the transmitted data. The above is only an example, and the present invention is not limited thereto.

[0054] In some embodiments, the levels of different path traffic are determined according to the bandwidth of the frequency band occupied by the traffic of different paths. The larger the bandwidth of the frequency band it occupies on the transmission path, the lower its level, and the longer its transmission time in the network, and the greater the carrying capacity required for its transmission path; the traffic level is determined according to the transmission rate. The transmission rates of the traffic are in descending order, and the levels of the traffic are in descending order. And the traffic with a higher level and a larger transmission rate requires a shorter transmission time in the network; of course, the levels of different path traffic in the network can also be determined by combining the occupied transmission frequency band and the transmission rate. The above is only an example, and the present invention is not limited herein.

[0055] Step S120, based on the determined levels of different path traffic, calculate the network reliability and network carrying capacity of each level of traffic on different paths between each head office and each branch; calculate the healthiness of each level of traffic based on the calculated network reliability and network carrying capacity, and sum up the calculated healthiness of each level of traffic to obtain the network healthiness of each level of traffic.

[0056] In this step, based on the levels of different path flows determined in step S110, the network reliability and network carrying capacity of different paths between each head office and each branch are calculated. The network reliability can be obtained by calculating the service reliability and congestion degree, and the network carrying capacity can be obtained by calculating the maximum available bandwidth and the bandwidth overhead required for each level of traffic. Then, based on the obtained network reliability and network carrying capacity, the health degree of each level of traffic is calculated, and the health degrees of each level of traffic obtained by calculation are summed to obtain the network health degree of each level of traffic.

[0057] In the embodiment of the present invention, since the health degree of the network under different levels of traffic is different, the present invention first calculates the health degree under a given traffic level. Assume that there are K different levels of traffic in the backbone network G, and the bandwidth overhead required for the given k-level traffic is Cost k , and the set of bandwidth overheads required for K levels of traffic is Cost K . For a given head office m ∈ M, the traffic demand ratios of different branches n ∈ N are different. Assume that the traffic demand ratio matrix of the given branch n for the given head office m is , and the set of traffic demand ratio matrices of N branches for M head offices is . The sum of each row is equal to 1, which is expressed as:

[0058]

[0059] . The set of ratio matrices can be expressed as:

[0060]

[0061] For a given head office m and a given branch n, assume that the ratio of the number of primary paths to the number of protection paths is 1:b, and the set of all disjoint paths between the head office and the branch is . The set of primary paths between the head office m and the branch n is . The number of primary paths is expressed as:

[0062] (rounded down);

[0063] That is to say, when there is 1 primary path in the network, there are b corresponding protection paths, and the sum of the number of primary paths and the number of protection paths is the number of disjoint paths, that is, the sum of the set of primary paths and the set of protection paths is equal to the set of disjoint paths. Select the first paths with the largest available bandwidth in the disjoint set as the primary paths between the head office m and the branch n, and each primary path has b protection paths.

[0064] In the embodiments of the present invention, for calculating the health of a given hierarchical traffic, since there are multiple primary paths between each head office and branch office, the present invention first calculates the network reliability of one primary path, and the network reliability is calculated from two aspects: determining the service reliability by the path protection mechanism and the congestion degree of the network. First, calculate the service reliability determined by each primary path and its corresponding protection path between each head office and branch office according to the path protection mechanism. The service reliability is the probability that at least one of the primary path and the protection path opposite to the primary path does not fail. Assume that represents the set of protection paths of the primary path . represents the set of the primary path and the protection path . represents a case of selecting i paths from the set of the primary path and the protection path , represents the set of all combinations of selectable i paths. For a given primary path The primary path provides a service reliability of defined as follows

[0065]

[0066] where p z represents the reliability of path z. The definition of the above formula is the probability that at least one path of the primary path and its corresponding set of protection paths does not fail. p z is defined as follows,

[0067] p z =∏ l∈z p l ;

[0068] where p l represents the availability of link l, and p z represents the probability that all links l∈z in path z are reliable, that is, the probability that path z is reliable.

[0069] Then, calculate the congestion degree of each primary path between each head office and each branch office according to the bandwidth rate already used by the links on the current path, that is, the link congestion rate. Assume that is an index related to the congestion degree (congestion rate), defined as follows:

[0070]

[0071] where u l represents the link congestion rate of link l, represents the primary path between head office m and branch office m The length, σ represents the standard deviation of the link congestion level. When the standard variance of the link congestion level is less than 0.5, its value is the average link congestion rate; when the standard variance of the link congestion level is greater than or equal to 0.5, its value is the maximum link congestion rate in the path. Its standard deviation is defined as:

[0072]

[0073] Where u represents the average value of the link congestion level, e is a link in the link set E, and u e is the utilization rate of link e. Its congestion level is expressed as:

[0074]

[0075] Where u represents the threshold of link congestion. When the standard deviation of the network link congestion rate is less than 0.5, the congestion level is the difference between the average link congestion rate of the path and the link congestion threshold; when the standard deviation of the network link congestion rate is greater than or equal to 0.5, the congestion level is the difference between the maximum link congestion rate of the link in the path and the link congestion threshold. The value 0.5 is only an example, and the present invention is not limited thereto.

[0076] In some embodiments, the path protection mechanism is that when the primary path (working path) fails or its performance is lower than the required level, the primary path (working path) will be automatically replaced by the protection path, and the data signal will be transmitted by the protection path. Among them, the path protection mechanism can be reversible or irreversible, which is not limited in the present invention.

[0077] Based on the reliability of the service determined by each main path and its corresponding protection path between each head office and each branch and the congestion level on each main path between each head office and each branch, the product of the service reliability and the congestion level is used as the network reliability of each main path between each head office and each branch, which is defined as follows:

[0078]

[0079] Where represents the network reliability of the main path between head office m and branch n.

[0080] In some embodiments, the reliability of the network can also be obtained by normalizing the values of the service reliability and the congestion level and then weighting them with a weight coefficient. The above method of multiplying the service reliability and the congestion level as the network reliability is only an example, and the present invention is not limited thereto.

[0081] In the embodiments of the present invention, for calculating the health of the given - level traffic, the network carrying capacity also needs to be calculated. For the network carrying capacity, it is defined as the maximum number of the given - level traffic that can be carried between the head office and the branch. First, calculate the maximum number of the given - level traffic that each main path between each head office and each branch can carry. The maximum number of the given - level traffic that each main path between each head office and each branch can carry can be calculated by dividing the maximum available bandwidth of each main path between each head office and each branch by the bandwidth overhead required for the given - level traffic. Then, the carrying capacity is defined as:

[0082]

[0083] Wherein, represents the carrying capacity of the main path between head office m and branch n for the k - level traffic, represents the main path between head office m and branch n of the maximum available bandwidth, and Cost k is the bandwidth overhead required for the given k - level.

[0084] Based on the above - calculated network reliability and network carrying capacity the health h of the network under the k - level traffic is obtained k and defined as:

[0085]

[0086] Substituting the definitions of network reliability and network carrying capacity into the above formula, we can get:

[0087]

[0088] It can be concluded from the equation that when the congestion rate is smaller, the network reliability is larger, and the health h k is larger. Therefore, the lower the link congestion degree, the healthier the network; the larger the network carrying capacity is, the larger the health h k is. Therefore, the larger the number of k - level traffic that the network can carry, the healthier the network.

[0089] Based on the health of each main path between each head office and each branch under the k - level traffic obtained above, adding the health of all main paths in the network gives the network health of each head office and branch under the k - level. Correspondingly, according to the above method, the present invention can calculate the network health of each level of traffic.

[0090] Step S130: Based on the network health degrees of each level of traffic obtained, perform weighted summation according to the proportion to obtain the network health degree of the overall network.

[0091] In this step, based on the network health degrees of each level of traffic calculated in step S120, perform weighted summation according to the traffic proportion between each head office and branch office to obtain the network health degree of the overall network. Among them, the weighting factor is the proportion of each branch office's traffic demand for each head office's traffic demand. That is, for a given head office, the traffic demand proportion of each branch office is different, and the sum of the traffic demand proportions of each branch office is equal to 1. However, the greater the traffic proportion between the head office and the branch office, the greater the impact on the health degree.

[0092] In the embodiment of the present invention, after calculating the health degrees of the current network under traffic of all levels, perform weighted summation according to the proportion of different levels of traffic in the total traffic to obtain the overall network health degree. The network health degree is defined as:

[0093]

[0094] where f k is the proportion of the traffic of level k in the total traffic, ∑ k∈k f k = 1, f K is the set of proportions of the traffic of K levels in the total traffic, H is the network health degree of the overall network obtained by performing weighted summation according to the proportion of each level of traffic, and the greater the proportion of the traffic of a given traffic type (level), the greater the impact on the health degree of the overall network

[0095] The network health degree evaluation method and device of the financial cloud backbone network of the present invention can obtain the reliability of the network through the service reliability determined by the path protection mechanism and the congestion degree of the network; can obtain the bearing capacity of the network through the maximum traffic volume that can be carried between a given head office and branch office; perform weighted summation based on the obtained network reliability and network bearing capacity to obtain the network health degree. The present invention can help the operator measure whether its current network strategy is effective, that is, whether the current network condition is healthy, provide guiding opinions on whether the operator needs to change its network strategy, and change the network strategy in a timely manner to improve the operation speed of the network and bring a better experience to users.

[0096] Corresponding to the above method, the present invention also provides a network health degree evaluation device for a financial cloud backbone network. The device includes a computer device, the computer device includes a processor and a memory, the memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the device implements the steps of the method described above.

[0097] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the foregoing edge computing server deployment method are implemented. The computer-readable storage medium may be a tangible storage medium, such as a random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, register, floppy disk, hard disk, removable storage disk, CD-ROM, or any other form of storage medium known in the art.

[0098] Those of ordinary skill in the art should understand that the various exemplary components, systems, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Specifically, whether to implement in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, and so on. When implemented in software, the elements of the present invention are programs or code segments used to perform the required tasks. The program or code segment can be stored in a machine-readable medium or transmitted via a data signal carried in a carrier wave on a transmission medium or a communication link.

[0099] It should be clear that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, the detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order between steps after understanding the spirit of the present invention.

[0100] In the present invention, the features described and / or illustrated for one embodiment can be used in the same or similar manner in one or more other embodiments, and / or combined with the features of other embodiments or replace the features of other embodiments.

[0101] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, various changes and modifications can be made to the embodiments of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for evaluating the network health of a financial cloud backbone network, characterized in that: The method comprises the following steps: Determine the traffic of different paths between the head office and the branches in the financial cloud backbone network, and determine the level of the traffic of different paths according to the bandwidth overhead required by the determined traffic of different paths; the different paths include a main path and a protection path corresponding to the main path, and the protection path is a transmission path of the traffic in the network when the main path fails; Based on the determined levels of traffic on different paths, the network reliability and network carrying capacity of different paths between each head office and each branch of traffic of each level are calculated; based on the calculated network reliability and network carrying capacity, the health of the traffic of each level is calculated, and the calculated health of the traffic of each level is summed to obtain the network health of the traffic of each level; Based on the obtained network health of each level of traffic, the weighted sum is calculated to obtain the network health of the overall network; The health of each level of traffic satisfies the following formula: Among them, k represents the level of traffic, m represents the head office, n represents the branch, M represents the head office set, and N represents the branch set. It is represented as the main path between the head office m and the branch office n. It is represented as the set of main paths between the head office m and the branch office n. It is represented as the traffic demand ratio matrix of branch n to head office m, Indicates the main path between the head office m and branch n network reliability, Indicates the main path between the head office m and branch n For the carrying capacity of k-level traffic; in, Satisfies the following formula:

2. The method according to claim 1, characterized in that The calculation of network reliability of different paths between each head office and each branch for each level of traffic includes: Calculate the service reliability of each main path between each head office and branch and the protection path of the main path according to a predetermined path protection strategy; Calculate the congestion level on each main path between each head office and each branch according to the congestion rate of the current path; The network reliability is calculated based on the obtained service reliability and congestion level; There is a one-to-many correspondence between the primary path and the protection path.

3. The method according to claim 1, characterized in that The network carrying capacity is the maximum number of predetermined levels of traffic that can be carried between the main path and the protection path of the head office and the branches in the network. The calculation of the network carrying capacity of different paths between each head office and each branch for each level of traffic includes: The network carrying capacity is calculated based on the maximum bandwidth available on each main path between each head office and each branch and the bandwidth overhead required for each level of traffic.

4. The method according to claim 2, characterized in that: The network reliability is obtained by multiplying the service reliability and the congestion level; The service reliability is the probability that one of the main path and the protection path relative to the main path does not fail.

5. The method according to claim 2, characterized in that: The congestion levels include: When the variance of the network link congestion rate distribution is less than a predetermined variance value, the congestion degree is the difference between the average link congestion rate of the path and the link congestion threshold; When the variance of the network link congestion rate distribution is greater than or equal to a predetermined variance value, the congestion degree is the difference between the maximum link congestion rate of the links in the path and the link congestion threshold.

6. The method according to claim 1, characterized in that The weighted value is the proportion of each branch's demand flow to each head office.

7. The method according to claim 1, characterized in that The financial cloud backbone network is constructed as an undirected graph model, and the undirected graph is represented by G=(V, E), where V represents a node set and E represents a link set.

8. A device for evaluating the network health of a financial cloud backbone network, comprising a processor and a memory, characterized in that: The memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the device implements the steps of the method as claimed in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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