Optical network path planning method and device

Abstract

The present invention relates to the field of communication technology, and provides an optical network path planning method and device. The method comprises: generating an objective function and one or more constraint functions according to network topology, user services and user policies; combining the objective function and the constraint function to establish a mathematical model with the goal of minimizing the total number of relays, maximizing the number of services calculated through and minimizing the total path length; solving the mathematical model to obtain the optimal optical network path. The present invention can find the optimal optical network path, and compared with the traditional optical network path planning method, it can reduce the amount of calculation in the optical network path planning process, thereby speeding up the optical network path planning.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to an optical network path planning method and device. Background Art

[0002] OTN (Optical Transport Network) is a new technology that enhances performance monitoring and management and maintenance functions based on DWDM (Dense Wavelength Division Multiplexing). In order to meet the diverse service needs of users, OTN technology encapsulates user services into ODUk (Optical Channel Data Unit) particles at the electrical layer and completes service scheduling through ODUk cross-connection. The optical layer scheduling of OTN relies on the optical fork multiplexer to realize the multiplexing and demultiplexing of optical signals. The optical fork multiplexer at the site can usually be divided into local groups and directional groups. The local group is used for service uplink and downlink, and the directional group is used for directional scheduling of optical signals.

[0003] OTN sites usually include OADM (optical branch multiplexing) sites and OA (optical amplifier) ​​sites. OADM sites can realize the uplink and downlink and directional scheduling of user optical signals, while OA sites can only realize the optical amplification function. There may be multiple OA sites between two adjacent OADM sites. The user's signal is input through the client-side optical module and converged to the line-side optical module through electrical cross-connection. The line-side optical module sends out a signal, which is sent to a certain direction through the optical branch multiplexing of the OADM station. After optical fiber transmission and optical amplification of the OA station, it is finally received by the line-side optical module of the target site. This is called the establishment of an optical channel. The optical channel is usually bidirectional, that is, there are usually two optical signals from the source site to the destination site and from the destination site to the source site. Based on DWDM technology, one optical fiber can transmit multiple optical signals. For example, in the current mainstream 96-wave system, the optical fiber can carry 96 optical signals, which correspond to different frequencies. In the process of optical signal transmission, various losses will be experienced, and the main loss comes from optical fiber loss. In order to compensate for the attenuation of this signal strength, the OA station needs to amplify the signal, but optical amplification introduces additional noise into the signal. At the receiving end of the optical signal, the OSNR (Optical Signal-to-Noise Ratio) is used to measure the quality of the optical signal. Users usually have certain threshold requirements for the OSNR at the receiving end. When the OSNR at the receiving end cannot meet the requirements, a relay can be added to perform 3R regeneration (reshaping, re-amplification, and retiming) on ​​the signal. Since one relay can only correspond to one optical signal, the cost of the relay is usually very high. Each node usually corresponds to an OADM (Optical Add-Drop Multiplexing) site, which contains a combination of some optical branching multiplexing devices. These combinations are divided into local groups and directional groups according to the different responsibilities of the devices. Among them, the local group is used to process the optical signal, and the directional group is used to send the optical signal to the next link. Each directional group is bound to a link. Since the directional group is bound to the link, the wavelength uniqueness of the directional group is actually equivalent to the wavelength uniqueness of the link.

[0004] Optical network path planning is widely used in planning and control areas. In the planning field, optical network path planning is usually used for user initial service routing planning, capacity expansion routing planning, multi-point fault simulation, etc. Usually, users provide network topology and resources for planning, provide the service matrix to be planned and set the corresponding routing strategy, and the planning software outputs the corresponding routing results. In the control area, optical network path planning is also used for service fiber break rerouting. When a fiber failure is detected and rerouting is required, the control will input the service matrix that needs to be recalculated into the algorithm module, and the algorithm will output new available routes and resources.

[0005] In optical network path planning, users usually have multiple needs, and need to balance the pros and cons among the multiple needs to find the best planning path. In the prior art, the most common means to implement optical network path planning is the KSP algorithm (K-shortest paths, shortest path algorithm) or the traversal search method. Among them, due to the form of sequential allocation of single services in the KSP algorithm, when the paths are allocated to subsequent services, the required allocated paths have been occupied by other services, so that the optimal path cannot be obtained. The traversal search method may not be able to obtain the optimal path when the number of traversed paths is small. When the number of traversed paths is large, the amount of calculation increases exponentially, the amount of calculation is large, and it takes a long time. And when users have multiple needs, each new demand will increase the amount of calculation of the KSP algorithm and the traversal search method, further aggravating the computational complexity of path planning and extending the time spent on path planning.

[0006] In view of this, overcoming the defects of the prior art is an urgent problem to be solved in the field of this technology. Summary of the invention

[0007] The technical problem to be solved by the present invention is that the existing optical network path planning method cannot obtain the optimal optical network path according to various needs of users.

[0008] The present invention adopts the following technical solution:

[0009] In a first aspect, the present invention provides an optical network path planning method, comprising:

[0010] Generate an objective function and one or more constraint functions according to network topology, user services and user policies;

[0011] Combining the objective function and constraint function, a mathematical model is established with the goal of minimizing the total number of relays, maximizing the number of services that can be calculated, and minimizing the total path length;

[0012] Solve the mathematical model to obtain the optimal optical network path.

[0013] Preferably, the objective function is specifically:

[0014] Adding the path length of each link used by the service to obtain the path length of the service, and adding the path length of each service to obtain the total path length;

[0015] The number of relays under the service is calculated according to the number of sub-paths under the service, and the total number of relays under each service is obtained by adding the number of relays;

[0016] The total path length, the total number of relays, and the number of services calculated are multiplied by the corresponding weights to obtain the corresponding total path length weighted value, the total number of relays weighted value, and the number of services calculated;

[0017] The objective function is the weighted value of the total path length plus the weighted value of the total number of relays minus the weighted value of the number of services that can be calculated.

[0018] Preferably, in the objective function, the weights corresponding to the total path length, the total number of relays and the number of computing services respectively meet the following conditions:

[0019] The weight N of the total number of relays is greater than or equal to a first minimum weight, where the first minimum weight is a weighted value of the total path length corresponding to the maximum total path length allowed in the network;

[0020] The weight P of the service quantity is greater than or equal to the second minimum weight, and the second minimum weight is a weighted value of the total number of relays corresponding to the maximum total number of relays allowed in the network.

[0021] Preferably, the one or more constraint functions specifically include:

[0022] One or more of a source-destination node constraint function, a path connectivity constraint function, a loss constraint function, a link wavelength constraint function, a local group wavelength constraint function, and a relay quantity constraint function on a node.

[0023] Preferably, the source and sink node constraint functions are specifically:

[0024] For each service k, find the source node S of service k among all the links used by service k. k The starting link (S k , j) and the destination node D that reaches service k k Link (i, D k );

[0025] When service k is calculated, the link (S k , j) has only one corresponding link (i, D k ) has only one;

[0026] When service k is not calculated, there is no corresponding link for service k (S k , j) and link (i, D k ).

[0027] Preferably, the path connectivity constraint function is specifically:

[0028] For each non-relay node n under each service k, the wavelength w occupied by service k when entering and exiting node n remains unchanged, and among all the links entering and exiting node n under service k, the number of links (i, n) entering node n and occupied by wavelength w is the same as the number of links (n, j) departing from node n and occupied by wavelength w;

[0029] For each relay node m under each service k, the number of links (i, m) entering the node m under service k is the same as the number of links (m, j) departing from the node m under service k.

[0030] Preferably, the loss constraint function is specifically:

[0031] For each subpath h under each service k, the forward loss of each link (i, j) under subpath h is added to obtain the total forward loss of subpath h, and the reverse loss of each link (i, j) under subpath h is added to obtain the total reverse loss of subpath h;

[0032] The total forward loss of each sub-path h is less than or equal to the corresponding preset forward loss threshold, and the total reverse loss of each sub-path h is less than or equal to the corresponding preset reverse loss threshold.

[0033] Preferably, the link wavelength constraint function is specifically:

[0034] For each used link (i, j), when wavelength w can be occupied on link (i, j), service k that is occupying wavelength w on link (i, j) is 1 The number of services k occupying wavelength w in the reverse direction 2 The sum of the numbers of is less than or equal to one;

[0035] When wavelength w cannot be occupied on link (i, j), service k 1 With business k 2 None exist.

[0036] Preferably, the local group wavelength constraint function is specifically:

[0037] For each local group l that is used, when wavelength w can be occupied on local group l, service k that is positively occupying wavelength w on local group l 1 The number of services k occupying wavelength w in the reverse direction 2 The sum of the numbers of is less than or equal to one;

[0038] When wavelength w cannot be occupied on local group l, service k 1 With business k 2 None exist.

[0039] In a second aspect, the present invention further provides an optical network path planning device for implementing the optical network path planning method described in the first aspect, the device comprising:

[0040] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the processor to execute the optical network path planning method described in the first aspect.

[0041] In a third aspect, the present invention further provides a non-volatile computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are executed by one or more processors to complete the optical network path planning method described in the first aspect.

[0042] The present invention constructs a mathematical model by using an objective function and one or more constraint functions, and then solves the mathematical model, so as to find the optimal optical network path. Compared with the traditional optical network path planning method, the present invention can reduce the amount of calculation in the optical network path planning process, thereby speeding up the optical network path planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0044] Figure 1 is a flow chart of an optical network path planning method provided by an embodiment of the present invention;

[0045] Figure 2 is a flow chart of an optical network path planning method provided by an embodiment of the present invention;

[0046] Figure 3 This is a schematic diagram of an optical network topology provided by an embodiment of the present invention;

[0047] Figure 4 is a schematic diagram of a service path under an optical network topology provided by an embodiment of the present invention;

[0048] Figure 5 This is a schematic diagram of an optical network topology provided by an embodiment of the present invention;

[0049] Figure 6 It is a schematic diagram of the architecture of an optical network path planning device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0051] In the description of the present invention, the terms "inside", "outside", "longitudinal", "lateral", "upper", "lower", "top", "bottom" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and do not require that the present invention must be constructed and operated in a specific orientation. Therefore, they should not be understood as limitations on the present invention.

[0052] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0053] Embodiment 1:

[0054] Embodiment 1 of the present invention provides an optical network path planning method, such as Figure 1 As shown, including:

[0055] In step 201, an objective function and one or more constraint functions are generated according to network topology, user services and user policies.

[0056] In step 202, the objective function and the constraint function are combined to establish a mathematical model with the goals of minimizing the total number of relays, maximizing the number of services that are calculated, and minimizing the total path length.

[0057] In step 203, the mathematical model is solved to obtain the optimal optical network path.

[0058] This embodiment constructs a mathematical model by using an objective function and one or more constraint functions, and then solves the mathematical model, so as to find the optimal optical network path. Compared with the traditional optical network path planning method, it can reduce the amount of calculation in the optical network path planning process, thereby speeding up the optical network path planning.

[0059] In the above embodiment, since the total number of relays is required to be the minimum, the number of services is the maximum, and the total path length is the shortest, the implementation method of the objective function that can usually be associated is: the number of services minus the total number of relays minus the total path length is used as the objective function. When the value of the objective function is the maximum, it is the optimal optical network solution. However, in actual situations, there is a certain mutually exclusive relationship between the minimum number of total relays, the shortest total path length, and the maximum number of services in the optical network path planning. In order to maintain a balance between these three goals, there are the following preferred embodiments:

[0060] The objective function is Figure 2As shown, specifically:

[0061] In step 301, the path length of each link used by the service is added to obtain the path length of the service, and the path length of each service is added to obtain the total path length.

[0062] In step 302, the number of relays under the service is calculated according to the number of sub-paths under the service, and the number of relays under each service is added to obtain the total number of relays.

[0063] In step 303, the total path length, the total number of relays and the number of services calculated are multiplied by corresponding weights to obtain the corresponding total path length weighted value, total number of relays weighted value and number of services calculated.

[0064] In step 304, the objective function is the weighted value of the total path length plus the weighted value of the total number of relays minus the weighted value of the number of services that have been calculated.

[0065] The objective function is expressed in the form of a mathematical formula:

[0066]

[0067] It should be noted that in the description of the embodiments of the present invention, unless otherwise specified, the symbols in the upper right and lower right corners of the parameters in all formulas should not be understood as powers of the parameters, but as limited descriptions of the parameters, and different positions of the symbols represent different limitations (all symbols in the same position have the same meaning).

[0068] In order to better describe the above objective function, a basic form of a decision variable is provided here, and the decision variable is explained, wherein the decision variable is specifically:

[0069]

[0070] Among them, variables k, h, a, b, i, j, u, d and w are all used to limit or indicate x.

[0071] The variables i and j refer to the source node and destination node of the link respectively, that is, specify a link (i, j), where i∈V, j∈V, V is the set of all nodes in the network topology, and link (i, j)∈E, E is the set of all unidirectional links in the network topology.

[0072] The variable k refers to the service and is used to indicate whether the link (i, j) is used by the service k, k∈K, K is the set of services in the network topology.

[0073] The variable h refers to the subpath, and is used to indicate whether the link (i, j) is a link under the hth subpath under the service k. h is greater than or equal to 0 and less than or equal to H, where H is the maximum number of subpaths allowed in a service.

[0074] The variable a refers to the first link and is used to indicate whether the link (i, j) is the first link under the hth subpath under the service k. The value of a is 0 or 1.

[0075] The variable b represents the last link and is used to indicate whether the link (i, j) is the last link under the hth subpath under the service k. The value of b is 0 or 1.

[0076] The variable u refers to the local group u in node i; the variable d refers to the local group d in node j, u∈L i , d∈L j , L i is the set of local groups in node i, L j is the set of local groups in node j, and the set of all local groups in the topological network is L, and L i ∈L,L j ∈L.

[0077] The variable w refers to the wavelength. When i and j are limited to fixed values, the variable w is used to indicate whether the wavelength w is occupied on the link (i, j), w∈W, and W is the total wavelength space.

[0078] When u is defined as a fixed value, the variable w is used to indicate whether wavelength w is occupied on the local group u in node i.

[0079] When d is defined as a fixed value, the variable w is used to indicate whether wavelength w is occupied on the local group d in the node j.

[0080] In the actual use of the objective function or constraint function, the values ​​defined in the decision variables are different, and the meanings indicated by the decision variables are different. When the indicated meanings are established, The value of is 1, otherwise, The value is 0. In each function, a detailed explanation will be given.

[0081] The embodiment of the present invention also provides a corresponding network topology diagram for illustrating the relationship between network elements such as services, source nodes, sink nodes, sub-paths, relay nodes, and local groups.

[0082] As Figure 3 Take the network topology with 11 nodes as an example. If you want to establish service k from node 1 to node 6, the possible paths of service k include the following four types:

[0083] The service goes from source node 1 to sink node 6 through node 2, node 3, node 4, node 5 in sequence.

[0084] The service goes from source node 1 to sink node 6 through node 7, node 4, and node 5 in sequence.

[0085] The service goes from source node 1 to sink node 6 via nodes 7 and 8 in sequence.

[0086] The service goes from source node 1 to sink node 6 via nodes 2, 9, 10, and 11 in sequence.

[0087] Take the path where the service goes from source node 1 through node 2, node 3, node 4, node 5 to destination node 6 as an example. Assume that there are 3 local groups in each node. In this path, node 3 and node 4 are relay nodes. Then, this path includes 3 sub-paths, namely, sub-path 1 between source node 1 and node 3, sub-path 2 between node 3 and node 4, and sub-path 3 between node 4 and destination node 6. That is, the source node, relay node, and destination node are the demarcation points of the sub-paths under the service. When there is no relay node in the path where the service is located, the service only has one sub-path from the source node to the destination node.

[0088] by Figure 3 and Figure 4 For example, for decision variables To illustrate, when the wavelength w is not limited, such as limiting h to 1 and a to 1, the decision variable obtained is It represents whether link (i, j) is the first link of the first sub-path under service k. When link (i, j) is the first link of the first sub-path under service k, The value of is 1, such as Figure 4 The link (1, 2) in satisfies this condition, namely The value is 1; otherwise, Figure 4 Although the link (2, 3) in belongs to the first subpath under service k, it is not the first link. The value of is 0. For link (3, 4), since nodes 3 and 4 are adjacent and both are relay nodes, the formed sub-path 2 only contains link (3, 4). Therefore, link (3, 4) is both the first link and the last link of sub-path 2. and The value of is 1.

[0089] When limiting the wavelength w, the value of the decision variable also needs to be determined in combination with whether the wavelength w is occupied at the corresponding node or local group.

[0090] In the objective function, the total path length is:

[0091]

[0092] Among them, the decision variables The variables k, h, a, b, i, j, u, d, and w in are accumulated, and the value range of each variable during the accumulation is its default range. In this case, Indicates whether link (i, j) is used by service k. When link (i, j) is used by service k, The value of is 1, otherwise, The value of len is 0; ij Represents the path length of link (i, j).

[0093] Since k is accumulated, when When it is not 0, link (i, j) must be used by service k. Therefore, the meaning of this formula is: for each service k, find each link (i, j) used by service k, and replace the path length len of each link (i, j) used by service k ij Add them together to get the path length of service k, and then add the path lengths of all services together to get the total path length.

[0094] In the objective function, the total number of relays is:

[0095]

[0096] Among them, the decision variables The variables k, b, i, j, u, d, and w in are accumulated, and the value range of each variable is its default range during the accumulation, and the value of variable a is specified as 1. In this case, Indicates whether link (i, j) is the first link under the h-th subpath of service k. When link (i, j) is the first link under the h-th subpath of service k, The value of is 1, otherwise, The value of is 0.

[0097] Since the variable h starts to accumulate from 2, when When the value of is 1, link (i, j) must be the first link under the second or subsequent subpath under service k, so the meaning of this formula is: for each service k, starting from the first link under the second subpath of service k, count the first link under each subsequent subpath, and because there must be a first link under a subpath, it actually represents the number of subpaths in service k minus one. Furthermore, since the relationship between the number of subpaths and the number of relay nodes under service k is: the number of relay nodes is equal to the number of subpaths minus one, the formula actually calculates the sum of the number of relays for all services k.

[0098] The above formula is not the only form of expression of the total number of relays. For example, it can also be achieved by limiting the value range of h to 2 to H, and limiting the value of any one of a and b to 1, or limiting the value range of h to 1 to H, and limiting the value of any one of a and b to 1, thereby obtaining the number of sub-paths of the service, and then using the number of sub-paths of the service minus one to obtain the number of relays for the service, and adding the number of relays for all services to obtain the total number of relays.

[0099] In the objective function, the number of transactions is calculated as:

[0100]

[0101] When business k is calculated, t k The value of is 1, otherwise, t k The value of is 0.

[0102] This embodiment controls the proportions of the three objectives by weighting the total number of relays, the number of services that are calculated, and the total path length, thereby maintaining a relative balance among the three objectives according to the network topology or user needs.

[0103] In actual situations, network path planning usually takes the maximum number of services being calculated as the first goal, the total number of relays being as small as possible while ensuring the first goal, that is, the second goal, and the shortest total path length being the third goal. In this regard, in combination with the above preferred embodiments, there are also the following preferred implementations:

[0104] In the objective function, the weights corresponding to the total path length, the total number of relays, and the number of computing services respectively meet the following conditions:

[0105] The weight N of the total number of relays is greater than or equal to a first minimum weight, and the first minimum weight is a weighted value of the total path length corresponding to the maximum total path length allowed in the network.

[0106] The weight P of the service quantity is greater than or equal to the second minimum weight, and the second minimum weight is a weighted value of the total number of relays corresponding to the maximum total number of relays allowed in the network.

[0107] This preferred implementation method limits the ratio of M to N and P so that the weight of the number of restored services is much greater than the weight of the number of newly added relays, and then much greater than the weight of the total length of the path, thereby ensuring that service recovery is at most the first goal, the total number of relays is at least the second goal, and the total path length is the shortest as the third goal. One specific implementation method is: N≥|K|×H×maxLen×maxNum×M, P≥|K|×N×H, where maxLen is the maximum possible path length of the link, maxNum is the maximum possible number of links in the subpath, and |K| is the number of elements in the set of services in the network topology. That is, N is greater than or equal to the product of the maximum possible total path length in the network and M. P is greater than or equal to the product of the maximum possible number of relays in the network and N.

[0108] The one or more constraint functions specifically include:

[0109] One or more of a source-destination node constraint function, a path connectivity constraint function, a loss constraint function, a link wavelength constraint function, a local group wavelength constraint function, and a relay quantity constraint function on a node.

[0110] The source-destination node constraint function is used to constrain the transmission direction of the service between the source node and the destination node of the service to be calculated, so that the transmission direction of the service to be calculated is unique.

[0111] The path connectivity constraint function is used to constrain each link on the service transmission path to be usable by the service, so that the service can reach the destination node from the source node along the calculated path.

[0112] The loss constraint function is used to constrain the loss of each sub-path to not exceed the corresponding loss allowable range.

[0113] The link wavelength constraint function is used to constrain a wavelength on a link to be occupied at most once.

[0114] The local group wavelength constraint function is used to constrain a wavelength on a local group to be occupied at most once.

[0115] The relay quantity constraint function on the node is used to constrain the number of relays added to a node to not exceed the range of the corresponding number of relays allowed to be added.

[0116] The types, number and form of the constraint functions used above are not completely fixed, but one or more of them can be selected for corresponding constraints according to the network path planning requirements of the topological network. Among them, the source-destination node constraint function and the path connectivity constraint function can constrain the uniqueness and integrity of the service path, and the loss constraint function, link wavelength constraint function, local group wavelength constraint function and the number of relays on the node constraint function can constrain the wavelength used on the link or local group and the loss when reaching the relay node, thereby ensuring the normal arrival of the service. Based on the constraint function, the objective function is used to obtain the optimal optical network path.

[0117] The source and sink node constraint functions are specifically:

[0118] For each service k, find the source node S of service k among all the links used by service k. k The starting link (S k , j) and the destination node D that reaches service k k Link (i, D k ).

[0119] When service k is calculated, the link (S k , j) has only one corresponding link (i, D k ) has only one.

[0120] When service k is not calculated, there is no corresponding link for service k (S k , j) and link (i, D k ).

[0121] The source-destination node constraint function is expressed in the form of mathematical formulas as the following formulas 1 and 2, where formula 1 is:

[0122] in

[0123] Formula 2 is:

[0124] in

[0125] S k is the source node of service k, D k is the sink node of service k. When service k is calculated successfully, t k The value of is 1, otherwise, t k The value of is 0, It means that for any service in the network topology, the corresponding formula should be satisfied.

[0126] In formula 1, the decision variable The value of h is limited to 1, the value of a is limited to 1, and the value of i is limited to S k , in this case, Refers to the link (S k , j) is the first link under the first subpath of service k, when link (S k , j) is the first link under the first subpath of service k, The value of is 1, otherwise, The value of is 0; the value of i is limited to S k , or limiting the values ​​of h and a to 1. Both of these methods can indicate whether the corresponding link is the first link under the first sub-path of service k. Either one can be used. Here, the two methods are combined to reduce the amount of calculation.

[0127] That is When the value is 1, the link (S k , j) must be the first link under the first subpath of service k, so the meaning of formula 1 is: for any service k in the network topology, the following conditions must be met: when service k is calculated, the source node S used by service k from service k k There is only one link from which service k starts. k The direction of departure is unique; when k is not calculated, service k starts from source node S k No links are used after departure.

[0128] In formula 2, the decision variable The value of b is limited to 1, and the value of j is limited to D k , in this case, Refers to the link (i, D k ) is the last link under the hth subpath of service k. When link (i, D k ) is the last link under the hth subpath of service k, The value of is 1, otherwise, The value of is 0.

[0129] That is When the value of is 1, the link (i, D k ) must be the last link under the hth subpath of service k and reaches the sink node D of the service. k , so the meaning of formula 1 is: for any service k in the network topology, the following conditions should be met:

[0130] When service k is calculated, the destination node D used by service k to reach service k k There is only one outgoing link, that is, service k enters the sink node D kThe direction is unique; when k is not calculated, service k does not use any entry source node D k link.

[0131] The source-destination node constraint function jointly constrains the services in the network topology through Formula 1 and Formula 2, so that the directions of the services when they depart and arrive are unique, thereby ensuring that the transmission direction of the services is unique.

[0132] The path connectivity constraint function is specifically:

[0133] For each non-relay node n under each service k, the wavelength w occupied by service k when entering and exiting node n remains unchanged, and among all links entering and exiting node n under service k, the number of links (i, n) entering node n and occupied by wavelength w is the same as the number of links (n, j) departing from node n and occupied by wavelength w.

[0134] For each relay node m under each service k, the number of links (i, m) entering the node m under service k is the same as the number of links (m, j) departing from the node m under service k.

[0135] The path connectivity constraint function is expressed in the form of mathematical formulas as the following formulas 3 and 4, where formula 3 is:

[0136]

[0137] in h; n∈V and n≠S k And n≠D k ; w∈W

[0138] Formula 4 is:

[0139]

[0140] in h; n∈V and n≠S k And n≠D k

[0141] h; n∈V and n≠S k And n≠D k Represents the source node S of the service under any service k and sink node D k Any nodes other than should satisfy the corresponding formula.

[0142] On the left side of the equal sign in Formula 3, the decision variable The value of b is limited to 0, in which case, Indicates whether link (i, n) is the last link under the h-th path of service k and whether the w band on link (i, n) is occupied. When link (i, n) is the last link under the h-th subpath of service k, or when the w band on link (i, n) is not occupied, The value of is 0. Otherwise, when link (i, n) is the link under the h-th subpath of service k, and link (i, n) is not the last link under the h-th subpath of service k, and the w band on link (i, n) is occupied, The value of is 1.

[0143] On the right side of the equal sign in Formula 3, the decision variable The value of a is limited to 0, in which case, Indicates whether link (n, j) is the first link under the h-th subpath of service k and whether the w band on link (n, j) is occupied. When link (n, j) is the first link under the h-th subpath of service k, or when the w band on link (n, j) is not occupied, The value of is 0. Otherwise, when link (n, j) is the link under the hth subpath of service k, and link (n, j) is not the first link under the hth subpath of service k, and the w band on link (n, j) is occupied, The value of is 1.

[0144] Among them, link (i, n) and link (n, j) are links with node n as the sink node and node n as the source node respectively.

[0145] When node n is a relay node for service k, link (i, n) must be the last link of a subpath under service k, that is, is equal to 0, and link (n, j) must be the first link of a subpath under service k, that is, is equal to 0, so for the relay nodes in service k, formula 3 always holds true.

[0146] When n is a non-relay node of service k, the meaning of the left side of the equal sign of the above formula 3 is: among the links of service k, the number of links with wavelength w occupied by service k and whose sink node is non-relay node n; the meaning of the right side of the equal sign of the above formula 3 is: among the links of service k, the number of links with wavelength w occupied by service k and whose source node is non-relay node n. That is, the meaning represented by formula 3 is: when service k enters and exits node n, the occupied wavelength w remains unchanged, and among all the links entering and exiting node n under service k, the number of links (i, n) entering node n and occupied by wavelength w is the same as the number of links (n, j) departing from node n and occupied by wavelength w.

[0147] On the left side of the equal sign in Formula 4, the decision variable The value of b is limited to 1, in which case, Indicates whether link (i, n) is the last link under the h-th subpath of service k. When link (i, n) is the last link under the h-th path of service k, The value of is 1, otherwise, The value of is 0.

[0148] On the right side of the equal sign in Formula 4, the decision variable The value of b is limited to 1, in which case, Indicates whether link (n, j) is the last link under the h+1th subpath of service k. When link (n, j) is the last link under the h+1th path of service k, The value of is 1, otherwise, The value of is 0.

[0149] When node n is a non-relay node for service k, link (i, n) must not be the last link under the hth subpath of service k, that is, is equal to 0, link (n, j) must not be the first link under the h+1th subpath of service k, that is, is equal to 0, so for non-relay nodes in service k, formula 4 is always valid.

[0150] When node n is the relay node of service k, the left side of the equal sign of formula 4 represents the number of links with node n as the destination node used by service k, and the right side of the equal sign represents the number of links with node n as the source node used by service k; that is, the meaning represented by formula 4 is: for the relay node of any service, the condition should be met: the number of links entering the relay node in the service is the same as the number of links starting from the relay node in the service.

[0151] The loss constraint function is specifically:

[0152] For each sub-path h under each service k, the forward loss of each link (i, j) under sub-path h is added to obtain the total forward loss of sub-path h, and the reverse loss of each link (i, j) under sub-path h is added to obtain the total reverse loss of sub-path h.

[0153] The total forward loss of each sub-path h is less than or equal to the corresponding preset forward loss threshold, and the total reverse loss of each sub-path h is less than or equal to the corresponding preset reverse loss threshold.

[0154] The loss constraint function is expressed in the form of mathematical formulas as Formula 5 and Formula 6, where Formula 5 is:

[0155] in h

[0156] Formula 6 is:

[0157] in h

[0158] lf ij represents the forward loss of link (i, j), lf ij represents the reverse loss of link (i, j), Th represents the preset loss threshold, and the same Th value is used for both the forward and reverse directions. Th values ​​can also be set for Formula 5 and Formula 6, respectively, that is, a preset forward loss threshold is set for Formula 5, and a preset reverse loss threshold is set for Formula 6. Furthermore, a corresponding preset forward loss threshold and a preset reverse loss threshold can be set for each subpath, and the preset forward loss threshold and the preset reverse loss threshold are set by those skilled in the art according to the OSNR requirements of the user or the network topology. h represents that any sub-path under any service in the network topology should satisfy the corresponding formula.

[0159] Formula 5 means: for any sub-path under any service in the network topology, the forward loss of each link under the sub-path is added to obtain the forward loss of the sub-path, and the forward loss of the obtained sub-path should be less than or equal to the corresponding preset forward loss threshold; Formula 6 means: the reverse loss of each link under the sub-path is added to obtain the reverse loss of the sub-path, and the reverse loss of the obtained sub-path should be less than or equal to the corresponding preset reverse loss threshold.

[0160] The link wavelength constraint function is specifically:

[0161] For each used link (i, j), when wavelength w can be occupied on link (i, j), service k that is occupying wavelength w on link (i, j) is 1 The number of services k occupying wavelength w in the reverse direction 2 The sum of the numbers is less than or equal to one.

[0162] When wavelength w cannot be occupied on link (i, j), service k 1 With business k 2 None exist.

[0163] The link wavelength constraint function is expressed in the form of a mathematical formula:

[0164]

[0165] in w∈W

[0166] Iwij Indicates whether wavelength w can be occupied on the link. When wavelength w can be occupied on the link, I wij The value of is 1, otherwise, I wij The value of I is 0, wij It is set by those skilled in the art based on the demand analysis of the topology network. w∈W represents that for any link in the topological network and any wavelength in the total wavelength space, the corresponding formula should be satisfied.

[0167] On the left side of the above formula, the decision variable Indicates whether service k is positively occupying wavelength w on link (i, j). When service k is positively occupying wavelength w on link (i, j), The value of is 1, otherwise, The value of is 0.

[0168] Indicates whether service k occupies wavelength w in the reverse direction on link (i, j). When service k occupies wavelength w in the reverse direction on link (i, j), The value of is 1, otherwise, The value of is 0.

[0169] That is, the meaning represented by the left side of the above formula is: the number of all services occupying wavelength w in the forward direction on link (i, j) plus the number of all services occupying wavelength w in the reverse direction on link (i, j). The overall meaning of the above formula is: when wavelength w can be occupied on link (i, j), wavelength w is only occupied once on link (i, j), that is, if wavelength w is occupied during forward propagation, wavelength w should not be occupied in the reverse direction, and vice versa. When wavelength w cannot be occupied on link (i, j), there should not be any service occupying wavelength w on link (i, j).

[0170] The local group wavelength constraint function is specifically:

[0171] For each local group l that is used, when wavelength w can be occupied on local group l, service k that is positively occupying wavelength w on local group l 1 The number of services k occupying wavelength w in the reverse direction 2 The sum of the numbers is less than or equal to one.

[0172] When wavelength w cannot be occupied on local group l, service k 1 With business k 2 None exist.

[0173] The local group wavelength constraint function is expressed in the form of a mathematical formula:

[0174]

[0175] in w∈W; n satisfies l∈L n

[0176] I wl Indicates whether wavelength w can be occupied on local group l. If wavelength w can be occupied on local group l, then I wl The value of is 1, otherwise, I wl The value of I is 0, wl It is set by those skilled in the art based on the demand analysis of the topology network. w∈W; n satisfies l∈L n This means that for any local group under any node in the topological network and any wavelength in the total wavelength space, the corresponding formula should be satisfied.

[0177] In the service transmission process of the actual network topology, although each node has a corresponding local group, the local group on the node will be used by the service and the wavelength on the local group will be occupied only when the node is the source node, sink node or relay node of the service. That is, when node n is neither the source node or sink node of the service, nor the relay node of the service, the wavelength w on the local group of node n will not be occupied, that is, the corresponding decision variable and The value of is 0, which must satisfy the above formula. Therefore, in order to reduce the amount of calculation, the wavelength constraint function of the local group can be formulated to remove the corresponding non-source nodes, non-destination nodes and non-relay nodes.

[0178] On the left side of the above formula, the decision variable The variable a is defined as 1, which indicates whether the link (n, j) is the first link under any subpath of service k, and whether the wavelength w is positively occupied on the local group l of the source node n of the link (n, j). When the link (n, j) is the first link under any subpath of service k, and the wavelength w is positively occupied on the corresponding local group l, The value of is 1, otherwise, The value of is 0. When link (n, j) is the first link under any subpath of service k, node n must be the source node or relay node of service k, thereby reducing the amount of calculation.

[0179] Decision variables The variable b is limited to 1, which is used to indicate whether the link (i, n) is the last link under any subpath of service k, and whether the wavelength w is positively occupied on the local group l of the sink node n of the link (i, n). When the link (i, n) is the last link under any subpath of service k, and the wavelength w is positively occupied on the corresponding local group l, The value of is 1, otherwise, The value of is 0. When link (i, n) is the last link under any subpath of service k, node n must be the sink node or relay node of service k, thereby reducing the amount of calculation.

[0180] Therefore, the meaning represented by the left side of the above formula is: the number of services occupying wavelength w in the forward direction on the local group l of node n plus the number of services occupying wavelength w in the reverse direction on the local group l of node n. The overall meaning of the above formula is: when wavelength w on the local group l of node n can be occupied, wavelength w can only be occupied once on the local group l, that is, if wavelength w is occupied during forward propagation, wavelength w should not be occupied in the reverse direction, and vice versa. When wavelength w cannot be occupied on the local group l, there should not be any service occupying wavelength w on the local group l.

[0181] The relay quantity constraint function is specifically:

[0182] For each node n in the network, find the service k with node n as the relay node, and the number of services k corresponding to node n is less than or equal to the corresponding preset maximum number of relays.

[0183] The relay quantity constraint function is expressed in the form of a mathematical formula:

[0184] in

[0185] |R n | represents the maximum number of relays that can be set on node n, that is, the preset maximum number of relays, where R n is the set of relays that can be set on node n, |R n | is the number of elements in the set, and the preset maximum number of relays is set by those skilled in the art based on the analysis of path planning requirements in the topological network. It means that for any node in the topological network, the corresponding formula should be satisfied.

[0186] On the left side of the above formula, the decision variable a is limited to 1, and the cumulative range of h starts from 2, which is used to indicate whether link (n, j) is the first link under any subpath of service k except the first subpath. When link (n, j) is the first link under any subpath of service k except the first subpath, The value of is 1, otherwise, The value of is 0.

[0187] The meaning of the left side of the above formula is similar to the total number of relays in the objective function. The meaning of the above formula is: the number of relays set on node n. The overall meaning of the above formula is: the number of relays set on node n is less than or equal to the preset maximum number of relays |R n |.

[0188] Based on the above objective function and constraint function, a specific implementation method of solving the mathematical model includes:

[0189] Among one or more constraint functions, one or more constraint functions are selected as a basis to obtain all possible optical network path planning situations that satisfy the selected constraint functions, and then unselected constraint functions are used to limit all possible optical network path planning situations to narrow the range of optional optical network paths. Finally, the objective function is substituted to calculate the values ​​of the objective function corresponding to the various optical network path planning situations after limitation, and the optical network path corresponding to the minimum value of the objective function is selected as the optimal optical network path.

[0190] Another specific implementation method is to solve it by integer programming, and the algorithms that can be used include branch and bound method, cutting plane method, etc. In practical applications, since the scale of the topological network in practical applications is usually large, integer programming solvers are often used for solving, such as Cplex, Gurobi, etc.

[0191] According to the planned optical network corresponding to the optimal integer solution obtained by solving the data model, the number of services that can be calculated is the largest, the number of newly added relays is the smallest, and the total path length is the shortest under the premise of satisfying the constraint function.

[0192] Embodiment 2:

[0193] The present invention is based on the method described in Example 1, combined with specific application scenarios, and uses technical descriptions in related scenarios to illustrate the implementation process of the present invention in characteristic scenarios.

[0194] like Figure 5 It is a topological optical transmission network with 7 nodes, the network size is 100G, and all wavelengths between 1 and 80 can be used. Figure 5 As shown, the loss of each link is marked in the form of square brackets. Here, the forward loss and reverse loss of the link are the same as an example. The wavelengths that can be occupied by each link are marked in the form of round brackets. Each node corresponds to an OADM station. Each OADM station is configured with two local groups. The wavelengths that can be occupied in each local group are all wavelengths between 1 and 80. 10 relays can be set on nodes C and D respectively, and relays cannot be added on other nodes.

[0195] The corresponding total wavelength space is obtained as all wavelengths between 1 and 80; the set V of all nodes in the corresponding network topology is all nodes between node A and node G; the set L of all local groups in the topological network is all local groups of all nodes in the topological network; there are 9 links in the network topology, and each link can transmit forward or reverse, so the corresponding set of all unidirectional links is 9 forward links plus 9 reverse links, assuming that the preset forward loss threshold and the preset reverse loss threshold Th are both 20, and the maximum number of sub-paths H allowed in the service is 3. Figure 5 The square brackets in the figure correspond to the wavelength range that can be occupied by each link, from which the corresponding I wij For example, on the link between node C and node F, the range of available wavelengths is from 31 to 80. Then the I 30ij The value of is 0. Since the wavelengths that can be occupied in each local group are all wavelengths between 1 and 80, for any wavelength in the total wavelength space, I wl The value of is 1. Let |R C | and |R D The value of | is 10, and the corresponding |R n The value of | is 0.

[0196] The three goals are set in order of priority: to process the most services, to add the least relays, and to have the smallest total number of hops.

[0197] Set the value of M to 1, and calculate the values ​​of N and P based on N = |K| × H × maxLen × maxNum × M, P = |K| × N × H, where maxLen is set to 1, maxNum is set to 5, and there can be a maximum of 40 services in the network topology, that is, |K| is 40, then N = 40 × 3 × 1 × 5 × 1 = 600, P = 40 × 600 × 3 = 72000. Construct an integer programming model according to the objective function and constraints.

[0198] Call the integer programming solver to solve the model and get the decision variables and t kThe value of. If it is calculated that the path of the first service is from source node A through node C, node F, node G to destination node E, the link between node A and node C occupies wavelength 80, and the links between node C and node F, between node F and node G, and between node G and node E all occupy wavelength 52. The local groups in the topological network are numbered as a whole, such as numbering the two local groups in node A as local group 1 and local group 2, and numbering the two local groups in node B as local group 3 and local group 4, and numbering the local groups in sequence until the two local groups in node G are numbered as local group 13 and local group 14. Among them, service k occupies local group 1 on node A, local group 5 and local group 6 on node C, local group 11 and local group 12 on node F, local group 13 and local group 14 on node G, local group 9 on node E, and a relay node is set on node C. Thus, we get and t 1 The values ​​of are all 1. Since nodes F and G are non-relay nodes, although the local groups in nodes F and G participate in the path planning of the service, no resources are actually allocated to them.

[0199] Embodiment 3:

[0200] like Figure 6 , is a schematic diagram of the architecture of an optical network path planning device according to an embodiment of the present invention. The optical network path planning device according to this embodiment includes one or more processors 21 and a memory 22. Figure 6 A processor 21 is taken as an example.

[0201] The processor 21 and the memory 22 may be connected via a bus or other means. Figure 6 The example of connecting through bus is taken in the following.

[0202] The memory 22 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs and non-volatile computer executable programs, such as the optical network path planning method in Example 1. The processor 21 executes the optical network path planning method by running the non-volatile software programs and instructions stored in the memory 22.

[0203] The memory 22 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the memory 22 may optionally include a memory remotely arranged relative to the processor 21, and these remote memories may be connected to the processor 21 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0204] The program instructions / modules are stored in the memory 22, and when executed by the one or more processors 21, the optical network path planning method in the above-mentioned embodiment 1 and embodiment 2 is executed, for example, the above-described Figure 1 and Figure 2 The steps shown.

[0205] It is worth noting that the information interaction, execution process, etc. between the modules and units within the above-mentioned devices and systems are based on the same concept as the processing method embodiment of the present invention. The specific contents can be found in the description of the method embodiment of the present invention and will not be repeated here.

[0206] A person skilled in the art may understand that all or part of the steps in the various methods of the embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the storage medium may include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0207] 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 and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for optical network path planning, characterized in that: include: Generate an objective function and one or more constraint functions according to network topology, user services and user policies; Combining the objective function and constraint function, a mathematical model is established with the goal of minimizing the total number of relays, maximizing the number of services that can be calculated, and minimizing the total path length; Solve the mathematical model to obtain the optimal optical network path; Among them, the objective function is specifically: adding the path length of each link used by the service to obtain the path length of the service, and adding the path length of each service to obtain the total path length; calculating the number of relays under the service according to the number of sub-paths under the service, and adding the number of relays under each service to obtain the total number of relays; multiplying the total path length, the total number of relays and the number of calculated services by the corresponding weights to obtain the corresponding total path length weighted value, total relay number weighted value and calculated service number weighted value; the objective function is the total path length weighted value plus the total relay number weighted value minus the calculated service number weighted value.

2. The optical network path planning method according to claim 1, characterized in that: In the objective function, the weights corresponding to the total path length, the total number of relays, and the number of computing services respectively meet the following conditions: The weight N of the total number of relays is greater than or equal to a first minimum weight, where the first minimum weight is a weighted value of the total path length corresponding to the maximum total path length allowed in the network; The weight P of the service quantity is greater than or equal to the second minimum weight, and the second minimum weight is a weighted value of the total number of relays corresponding to the maximum total number of relays allowed in the network.

3. The optical network path planning method according to claim 1, characterized in that: The one or more constraint functions specifically include: One or more of a source-destination node constraint function, a path connectivity constraint function, a loss constraint function, a link wavelength constraint function, a local group wavelength constraint function, and a relay quantity constraint function on a node.

4. The optical network path planning method according to claim 3, characterized in that: The source and sink node constraint functions are specifically: For each service k, find the source node S of service k among all the links used by service k. k The starting link (S k , j) and the destination node D that reaches service k k Links (i, D k ); When service k is calculated, the link (S k , j) has only one corresponding link (i, D k ) There is only one; When service k is not calculated, there is no corresponding link for service k (S k , j) and link (i, D k ).

5. The optical network path planning method according to claim 3, characterized in that: The path connectivity constraint function is specifically: For each non-relay node n under each service k, the wavelength w occupied by service k when entering and exiting node n remains unchanged, and among all the links entering and exiting node n under service k, the number of links (i, n) entering node n and occupied by wavelength w is the same as the number of links (n, j) departing from node n and occupied by wavelength w; For each relay node m under each service k, the number of links (i, m) entering node m under service k is the same as the number of links (m, j) departing from node m under service k.

6. The optical network path planning method according to claim 3, characterized in that: The loss constraint function is specifically: For each sub-path h under each service k, the forward loss of each link (i, j) under sub-path h is added to obtain the total forward loss of sub-path h, and the reverse loss of each link (i, j) under sub-path h is added to obtain the total reverse loss of sub-path h; The total forward loss of each sub-path h is less than or equal to the corresponding preset forward loss threshold, and the total reverse loss of each sub-path h is less than or equal to the corresponding preset reverse loss threshold.

7. The optical network path planning method according to claim 3, characterized in that: The link wavelength constraint function is specifically: For each used link (i, j), when wavelength w can be occupied on link (i, j), the sum of the number of services k1 occupying wavelength w in the forward direction and the number of services k2 occupying wavelength w in the reverse direction on link (i, j) is less than or equal to one; When wavelength w cannot be occupied on link (i, j), both service k1 and service k2 do not exist.

8. The optical network path planning method according to claim 3, characterized in that: The local group wavelength constraint function is specifically: For each local group l that is used, when wavelength w can be occupied on local group l, the sum of the number of services k1 occupying wavelength w in the forward direction and the number of services k2 occupying wavelength w in the reverse direction on local group l is less than or equal to one; When wavelength w cannot be occupied in local group 1, service k1 and service k2 do not exist.

9. An optical network path planning device, characterized in that: The device comprises: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the processor to execute the optical network path planning method described in any one of claims 1-8.

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