JP2017085388A - Routing table generation device, routing table generation method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To expand a range of a transfer device capable of setting route information that is obtained by any method.SOLUTION: A routing table generation device comprises: a sorting part for sorting an aggregate of ratios for each entry of a routing table regarding traffic volume for each outgoing/incoming node relating to the transfer device into groups for each destination of transfer by the transfer device; and a generation part for generating each of the entries in such a manner that a transfer destination corresponding to a group into which the ratio is sorted becomes a transfer destination in the case of meeting a condition of the entry relating to the ratio. The sorting part sorts for each group the aggregate of the ratios of the traffic volume for each entry in such a manner that a differential between a total sum of the ratios that are sorted into the group and a target value of the ratios of the traffic volume for each transfer destination that is inputted regarding the traffic for each outgoing/incoming node to the transfer destination corresponding to the group, is minimized.SELECTED DRAWING: Figure 3

Description

  The present invention relates to a routing table generation device, a routing table generation method, and a program.

  As a technique for efficiently accommodating traffic using limited network resources, a traffic engineering technique for predicting arrival traffic and controlling a traffic route based on a prediction result has been studied. As an example of traffic engineering, route control for the purpose of minimizing the maximum link utilization rate in the network can be considered. The maximum link utilization rate refers to the utilization rate of the most congested (highest utilization rate) link in the network. The link utilization rate refers to the ratio of traffic demand to the link bandwidth.

  In traffic engineering, route information is calculated using a mathematical optimization problem composed of traffic demand, network topology information, link information, and the like. Linear programming problems and integer programming problems are known as typical mathematical optimization problems for traffic engineering. The traffic demand is a predicted value of the traffic volume in the future.

  A linear programming problem for traffic engineering is shown in Equation 1 (Equations (1.1) to (1.6)) (Patent Document 2).

ここで、ネットワークは、有効グラフＧ（Ｖ、Ｅ）で表現される。Ｖはノードの集合、Ｅはリンクの集合を表す。また、ノードｉ∈Ｖからノードｊ∈Ｖまでのリンク容量はｃ_ｉｊ∈Ｅと表す。ノードｐからノードｑまでのトラヒック需要は、ｔ_ｐｑと表す。

Here, the network is represented by an effective graph G (V, E). V represents a set of nodes, and E represents a set of links. The link capacity from node i∈V to node j∈V represents the _{c ij} [epsilon] E. The traffic demand from the node p to the node q is expressed as _tpq .

は、トラヒック需要ｔ_ｐｑについて、リンク（ｉ，ｊ）の通過割合を示し、ルーティング変数と呼ばれる。通過割合とは、トラヒック需要ｔ_ｐｑに対して、リンク（ｉ，ｊ）に分配されたトラヒック量の割合をいう。例えば、２つのリンクを有する転送装置において、トラヒック需要ｔ_ｐｑについての一方のリンクの通過割合が０．３であれば、他方のリンクの通過割合は０．７である。ｒは、最大リンク利用率を示しており、数１ではｒを最小化するようなルーティング変数の値を求めている。

Indicates the passing rate of link (i, j) for traffic demand t _pq and is called a routing variable. The passage ratio refers to the ratio of the traffic amount distributed to the link (i, j) with respect to the traffic demand _tpq . For example, in a transfer apparatus having two links, if the passing rate of one link with respect to traffic demand _tpq is 0.3, the passing rate of the other link is 0.7. r represents the maximum link utilization rate, and in Equation 1, the value of the routing variable that minimizes r is obtained.

  Equation (1.1) shows an objective function that minimizes the maximum link utilization rate, and Equations (1.2) to (1.6) are constraints. Equations (1.2) and (1.3) show the flow conservation laws. Expression (1.4) indicates that the total traffic passing through the link (i, j) does not exceed the link capacity × the maximum link utilization rate. Equations (1.5) and (1.6) are the routing variables

と、最大リンク利用率ｒとの値域を示している。

And the range of the maximum link utilization rate r.

  In this linear programming problem, route information that minimizes the maximum link utilization in the network is obtained as a solution. The route information is obtained as a transmission ratio of traffic to a plurality of output ports in each transfer apparatus. In order to set the route information obtained here to the network, it is necessary that each transfer apparatus can divide the traffic into multipaths at an arbitrary ratio.

  There is an ECMP (Equal-Cost Multi-path) technique in an IP router as a technique for dividing traffic into multipaths. ECMP is a technique for equally dividing and transmitting traffic to output ports having the same cost, and multipath division cannot be performed at an arbitrary ratio.

  On the other hand, in OpenFlow 1.3 and later, traffic can be divided into multipaths with an arbitrary granularity by using the Select function in the Group Table. However, since the Select function is not an indispensable function that must be implemented in the OpenFlow 1.3 specification, even a switch that complies with OpenFlow 1.3 may not be used.

  Next, an integer programming problem for traffic engineering is shown in Formula 4 (Formulas (2.1) to (2.6)).

数４は、数１において、式（１．５）を式（２．５）に置き換えたものである。

Formula 4 is obtained by replacing Formula (1.5) with Formula (2.5) in Formula 1.

  In this integer programming problem, as in the case of Equation 1, route information that minimizes the maximum link utilization rate in the network is obtained as a solution. However, since the constraint condition is that the solution is an integer value according to Equation (2.5), the obtained route information becomes a single output port of traffic in each transfer device. When setting the obtained route information in the network, it is not necessary to divide the traffic into multipaths at an arbitrary ratio in each transfer device. For this reason, the route obtained by the integer programming problem can be set in a wider network than the route obtained by the linear programming problem.

Japanese Patent No. 5747393 Japanese Patent No. 7542981

  Comparing linear programming problems with integer programming problems in terms of computation time, linear programming problems have efficient algorithms such as the simplex method and interior point method as solutions, and solutions can be quickly derived even for large-scale problems. can do. On the other hand, the integer programming problem is known to be NP-hard, and there is no efficient algorithm for solution derivation. For this reason, in the integer programming problem, it is difficult to derive a solution in a realistic execution time in a large-scale problem.

  Next, when comparing the linear programming problem and the integer programming problem in terms of the performance of the optimal path obtained, the linear programming problem allows all real numbers including integers as solutions, whereas the integer programming problem , Only integers are allowed as solutions. Thus, since the linear programming problem can be derived from a wider solution space than the integer programming problem, the optimality of the obtained solution, that is, the performance of the optimal path is high. When the maximum link utilization rate in the network is an objective function as in the examples of Equation 1 and Equation 2, the optimum route obtained by the linear programming problem (Equation 1) is used in the maximum link utilization in the network. A path with a reduced rate is obtained.

  As described above, the optimal route calculation by the linear programming problem is excellent in terms of “calculation time” and “performance of the obtained route”, but there is a problem that a transfer device that can set the obtained optimum route is limited. Exists.

  Therefore, there is a need for a technique that can set route information obtained by an arbitrary method, such as optimal route calculation using a linear programming problem, in a transfer apparatus.

  The present invention has been made in view of the above points, and an object of the present invention is to extend the range of transfer apparatuses that can set path information obtained by an arbitrary method.

  Therefore, in order to solve the above-described problem, the routing table generation device uses a routing table configured by a plurality of entries each including different conditions and information indicating the traffic forwarding destinations that match the conditions, A classification unit for classifying the set of ratios for each entry with respect to the traffic amount for each transmission / reception node relating to a transfer apparatus that determines a transfer destination of traffic into a group for each transfer destination by the transfer apparatus, and a group into which the ratio is classified And a generation unit that generates each entry so that the transfer destination corresponding to the ratio matches the condition of the entry according to the ratio, and the classification unit includes the generation unit for each group. The sum of the percentages classified into groups, and the traffic by the above-mentioned destination node with respect to the forwarding destination corresponding to the group. It entered Te, the difference between the target value of the ratio of the transfer destination by the traffic volume so that the minimum, classified set of proportions of said entry-specific traffic amount.

  It is possible to extend the range of transfer devices that can set route information obtained by an arbitrary method.

It is a figure which shows the network structural example in embodiment of this invention. It is a figure which shows the hardware structural example of the routing table production | generation apparatus in embodiment of this invention. It is a figure which shows the function structural example of the routing table production | generation apparatus in embodiment of this invention. It is a flowchart for demonstrating an example of the process sequence which a routing table production | generation apparatus performs. It is a figure which shows the structural example of a certain transfer apparatus. It is a figure which shows an example of the route information calculated by the route calculation apparatus. It is a figure which shows an example of the traffic information regarding a certain transfer apparatus. It is a figure which shows the structural example of port link information. It is a figure which shows an example of the collection of the optimal traffic amount ratio according to output port. It is a figure which shows an example of the classification | category result of the set of the observation traffic volume ratio according to entry. It is a figure which shows an example of the production | generation result of a routing table.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a diagram illustrating a network configuration example according to an embodiment of the present invention. FIG. 1 shows terminals 50a to 50d, transfer devices 40a to 40c, a control device 20, a route calculation device 30, and a routing table generation device 10. Note that the terminals 50a to 50d are referred to as terminals 50 when not distinguished. Further, when the transfer devices 40a to 40c are not distinguished, they are referred to as transfer devices 40.

  Each terminal 50 is a device that generates traffic. That is, each terminal 50 corresponds to a traffic source or destination. Each terminal 50 is connected to one of the transfer devices 40 via a network. The traffic refers to a communication flow on the network, and the communication is constituted by, for example, a set of packets.

  Each transfer device 40 is a device that transfers (relays) traffic. An example of the transfer device 40 is a switch (OpenFlow switch) corresponding to SDN (Software Defined Network) / OpenFlow. Each transfer device 40 is connected to one of the terminals 50 or another transfer device 40 via a link. Each transfer device 40 has a routing table that is a set of routing entries, and determines an output port (transfer destination) as an output destination of traffic to be transferred in accordance with the routing table. The routing entry includes a matching rule that is a condition for traffic, and output port information indicating an output port (forwarding destination) of traffic that matches the matching rule. The matching rule includes traffic identification information (IP header information, TCP header information, MPLS (Multi-Protocol Label Switching) header information, etc.) and differs for each routing entry. In order for this embodiment to function effectively, an identifier other than the identification information of the arrival / departure node is added to the matching rule, and the arrival / departure node It is desirable to be able to perform traffic control with a finer granularity than another flow, for example, a macro flow for each node as shown in Patent Document 1 is suitable for this implementation.

  In the present embodiment, “node” refers to any transfer device 40 and does not include the terminal 50. Therefore, the traffic of interest in the present embodiment refers to the traffic on the links L1 to L3 connecting the transfer apparatuses 40 in FIG.

  Each transfer device 40 also measures the number of packets or the number of bytes (hereinafter referred to as “traffic amount”) for each routing entry, and transmits the measurement result to the control device 20.

  The control device 20 is a device that sets a routing table for each transfer device 40. An example of the control device 20 is a controller (OpenFlow controller) corresponding to SDN / OpenFlow. The control device 20 can also periodically access the transfer device 40 and acquire the matching rule and entry counter value of the routing entry at each time. The entry counter value indicates the amount of traffic transferred in accordance with the routing entry. In addition, the connection form of the control apparatus 20 and each transfer apparatus 40 is not limited to a predetermined thing.

The route calculation device 30 collects network configuration information and traffic information, and calculates route information indicating the optimum route for each traffic at each arrival / departure node and for each transfer device 40. The route information is calculated based on Equation 1. The route information x _ijpq calculated by the route calculation device 30 is that the node i is the j-th traffic for the traffic for each arrival / departure node transmitted from the source node p (transfer device 40) to the destination node q (transfer device 40). It represents the rate at which traffic is transmitted to the output link (i, j). Hereinafter, this route information x _ijqq is _referred to as “optimal traffic amount ratio by output link”. As described above, the “node” in the present embodiment refers to the transfer device 40. Therefore, the traffic classified by the arrival / departure node refers to the traffic classified between the transfer apparatuses 40.

  The routing table generation device 10 generates a routing table for each transfer device 40 based on the route information calculated by the route calculation device 30 and the traffic information acquired from the control device 20.

  FIG. 2 is a diagram illustrating a hardware configuration example of the routing table generation device according to the embodiment of the present invention. The routing table generation device 10 in FIG. 2 includes a drive device 100, an auxiliary storage device 102, a memory device 103, a CPU 104, an interface device 105, and the like that are mutually connected by a bus B.

  A program for realizing the processing in the routing table generating apparatus 10 is provided by a recording medium 101 such as a CD-ROM. When the recording medium 101 storing the program is set in the drive device 100, the program is installed from the recording medium 101 to the auxiliary storage device 102 via the drive device 100. However, the program need not be installed from the recording medium 101 and may be downloaded from another computer via a network. The auxiliary storage device 102 stores the installed program and also stores necessary files and data.

  The memory device 103 reads the program from the auxiliary storage device 102 and stores it when there is an instruction to start the program. The CPU 104 executes functions related to the routing table generation device 10 in accordance with a program stored in the memory device 103. The interface device 105 is used as an interface for connecting to a network.

  Note that the control device 20 and the route calculation device 30 may also have the same hardware configuration as in FIG. Further, the routing table device 10, the control device 20, and the route calculation device 30 may be realized using one or more common computers.

  FIG. 3 is a diagram illustrating a functional configuration example of the routing table generation device according to the embodiment of the present invention. In FIG. 3, the routing table generation device 10 includes an input information acquisition unit 11, a classification unit 12, a generation unit 13, and the like. Each of these units is realized by processing that one or more programs installed in the routing table generation apparatus 10 cause the CPU 104 to execute.

  The input information acquisition unit 11 acquires information necessary for generating the routing table from the control device 20 and the route calculation device 30. From the control device 20, the routing table of the transfer device 40 and the traffic information observed in the transfer device 40 are acquired. The route information calculated as the optimum route is acquired from the route calculation device 30.

  The classification unit 12 classifies each routing entry constituting the routing table of the transfer device 40 into a group for each output port of the transfer device 40 for each transfer device 40 based on the input traffic information and route information. To do. The classification method will be described later.

  The generation unit 13 generates (updates) the routing table of each transfer device 40 based on the classification result by the classification unit 12. More specifically, the generation unit 13 updates the output port information corresponding to the matching rule for each routing entry in the existing routing table.

  Hereinafter, a processing procedure executed by the routing table generation device 10 will be described. FIG. 4 is a flowchart for explaining an example of a processing procedure executed by the routing table generation device.

  In step S <b> 101, the input information acquisition unit 11 acquires the route information calculated for each transfer device 40 from the route calculation device 30, and acquires the routing table and traffic information of each transfer device 40 from the control device 20.

  In the present embodiment, for the sake of convenience, description will be given focusing on one transfer device 40 (hereinafter referred to as “transfer device X”). The transfer device X has a configuration as shown in FIG.

  As shown in FIG. 5, the transfer device X has three output ports identified by Port_a, Port_b, or Port_c. A link (Link_X, Link_Y, or Link_Z) is connected to each output port. In FIG. 1, each transfer device 40 is connected to one other transfer device 40, but for the transfer device X, for convenience, there are three links connected to the other transfer device 40. Suppose there is.

  The transfer device X also has a routing table T1. The routing table T1 includes Rule_1 to Rule_11 as matching rules. For example, traffic that matches Rule_1 or Rule_5 is output from Port_a, traffic that matches Rule_2 or Rule_4 is output from Port_b, and traffic that matches Rule_3 is output from Port_c. Is set. In the routing table T1, output ports for Rule_6 to Rule_11 are omitted for convenience.

  For such a transfer device X, the route calculation device 30 calculates the route information as shown in FIG.

  FIG. 6 is a diagram illustrating an example of route information calculated by the route calculation device. As shown in FIG. 6, the route information related to a certain transfer device 40 is a set of “optimum traffic amount ratio by arrival / departure node”, which is a ratio of traffic amount to each output link for traffic by arrival / departure node. is there.

  On the other hand, from the control device 20, the routing table T1 shown in FIG. 5 and the acquired traffic information as shown in FIG.

  As shown in FIG. 7, the traffic information acquired from the control device 20 with respect to the transfer device X is the ratio for each matching rule with respect to the traffic amount for each arrival / departure node observed in the transfer device X. This is a set of observed traffic volume ratios.

  Subsequently, the input information acquisition unit 11 processes the acquired route information and traffic information into a format convenient for the routing table generation processing (step S102).

  For example, the optimal traffic volume ratio for each output link shown in FIG. 6 is converted into the optimal traffic volume ratio for each output port. The conversion is performed using “port / link information” stored in the transfer apparatus X.

  FIG. 8 is a diagram illustrating a configuration example of the port / link information. As shown in FIG. 8, the port / link information indicates the correspondence between the output port and the output link. Basically, there is a one-to-one correspondence between output ports and output links. FIG. 8 shows port / link information in the transfer apparatus X of FIG. The port / link information is acquired from the transfer device X via the control device 20, for example.

  The “output link” corresponding to each output link optimum traffic rate ratio in FIG. 6 is replaced with “output port” based on the port link information in FIG. A set is obtained. FIG. 9 shows an example of a set of optimum traffic volume ratios by output port.

  The input information acquisition unit 11 also processes the traffic information acquired from the control device 20. In FIG. 7, for convenience, the “observed traffic amount ratio by entry”, which is the processing result, is shown, but strictly speaking, the traffic information acquired from the control device 20 is the “observed traffic amount by entry”. The input information acquisition unit 11 obtains a “per-entry observation traffic amount ratio” by obtaining a ratio of each entry-based observation traffic amount in units of arrival and departure nodes.

  Note that the routing table in the transfer device 40 stores a traffic value counter value for each routing entry. By measuring this counter value, it is possible to obtain “observation traffic amount by entry”.

  The routing table T1 generated from now on will be used in the future. Therefore, the “observed traffic volume by entry” is not used as it is, but the “observed traffic volume by entry” is based on the result of conversion into the predicted traffic demand predicted in the future. The “volume ratio” may be calculated. For example, the predicted value may be calculated by linear prediction, ARIMA, or the like. In the present embodiment, an example in which the “observed traffic amount by entry” is used as a predicted value as it is based on the assumption that the traffic demand is constant will be described.

  Subsequently, the classifying unit 12 classifies the set of observed traffic volume ratios for each entry / departure node for each departure / arrival node into a group for each output port to which the optimal traffic volume ratio for each output port is assigned for that departure / arriving node. (Step S103).

  P (p1, p2, p3,..., PN) is the optimal traffic volume ratio for each output port with respect to the specific traffic for each node, and the observed traffic volume ratio for each entry is F (f1, f2, f3,. , FM), the classification unit 12 generates an approximate traffic amount ratio A (a1, a2, a3,..., AN) for each output port by arbitrarily combining F. That is, a set of the observed traffic volume ratios by entry is classified into groups by output ports. A is represented by the formula (3.1).

ここで、ｕ_ｉｊは、Ｆの組み合わせを表す０−１変数であり、ａ_ｉにｆ_ｊが含まれる場合に１、それ以外の場合に０を表す。ｆ_ｊは、いずれか１つのａ_ｉにのみ含まれる。この条件について式（３．２）、（３．３）で表す。

_{Here, u ij} is a 0-1 variable representing the combination of F, represents 0 to 1, otherwise if it contains the _{f j} in _{a i.} f _j is included only in any one a _i . This condition is expressed by equations (3.2) and (3.3).

この際、分類部１２は、出力ポート別近似トラヒック量割合Ａと出力ポート別最適トラヒック量割合Ｐとの誤差（差分）が最も小さくなるように、出力ポート別近似トラヒック量割合Ａを生成する。出力ポート別近似トラヒック量割合Ａと出力ポート別最適トラヒック量割合Ｐとの誤差を式（３．４）で表す。

At this time, the classification unit 12 generates the approximate traffic amount ratio A for each output port so that the error (difference) between the approximate traffic volume ratio A for each output port and the optimal traffic amount ratio P for each output port becomes the smallest. An error between the approximate traffic volume ratio A for each output port and the optimal traffic volume ratio P for each output port is expressed by Expression (3.4).

式（３．１）から（３．４）により、以下の数理計画問題を定式化できる。

The following mathematical programming problems can be formulated by equations (3.1) to (3.4).

しかしながら、この数理計画問題は、目的関数が非線形関数であるため、効率的な解導出が困難である。そこで、誤差ベクトルＺ（ｚ_１，...，ｚ_N）を導入し、数８を、下記のような０−１整数計画問題へと変換する。

However, this mathematical programming problem is difficult to derive efficiently because the objective function is a nonlinear function. Therefore, an error vector Z (z ₁ ,..., Z _N ) is introduced, and Equation 8 is converted into the following 0-1 integer programming problem.

数９では、式（３．４）の非線形関数が、式（３．６）、（３．７）、及び（３．８）で表現されている。

In Equation 9, the nonlinear function of Equation (3.4) is expressed by Equations (3.6), (3.7), and (3.8).

The meaning of each parameter in Equation 9 will be described again as follows.
z _i is the difference (error) between the optimal traffic volume ratio for each output port and the approximate traffic volume ratio for each output port for the i-th output port group.
M is the number of routing entries in the routing table T1.
N is the number of output ports.
p _i is the optimum traffic volume ratio for each output port calculated for the i-th output port.
a _i is the total sum of the observed traffic volume ratios by entry classified into the group corresponding to the i-th output port.

The classification unit 12 obtains a mapping variable u _ij that minimizes the error vector Z by solving the optimization problem of Equation 9. As a result, the set of observation traffic volume ratios by entry is classified into groups by output ports so that the error vector Z is minimized.

FIG. 10 is a diagram illustrating an example of a classification result of a set of observation traffic volume ratios by entry. The “optimization problem” shown in FIG. By solving the optimization problem, the value of u _ij is obtained, and as a result, each matching rule is classified into a group for each output port. FIG. 10 shows an example in which three routing entries including Rule_1, Rule_2, or Rule_4 as a matching rule are classified into a Port_a group, and two routing entries including Rule_3 or Rule_5 as a matching rule are classified as Port_b. Has been.

In addition, in FIG. 10, although the calculation result of u _ij regarding the specific traffic for each node (Node1-Node2) is shown, u _ij is calculated for each traffic for each node observed in the transfer device X. The matching rules are classified into groups for each output port for each traffic at each node.

  Subsequently, the generation unit 13 generates (updates) the routing table T1 of the transfer device X based on the classification result by the classification unit 12 (step S104).

  FIG. 11 is a diagram illustrating an example of a routing table generation result. In FIG. 11, it is shown that the observed traffic volume ratio for each entry and the optimal traffic volume ratio for each output port are input to the routing table generation apparatus 10 and the routing table T1 is output from the routing table generation apparatus 10. The generated routing table T1 is set in the transfer device X by the control device 20. As a result, the transfer apparatus X executes path control that can effectively distribute traffic and improve the use efficiency of the network.

  The above processing procedure is also executed for each transfer device 40 other than the transfer device X.

  As described above, according to the present embodiment, it is possible to set the path obtained by the linear programming problem of Equation 1 even in the transfer apparatus 40 that does not have the traffic split function. Therefore, in an environment where a plurality of paths exist between the departure and arrival nodes, it is possible to approach the optimum route by effectively using the multipath. In addition, two advantages of the linear programming problem (“short calculation time” and “high performance of the obtained optimum path”) can be obtained. As a result, a high-performance optimum path can be set in various transfer devices in a realistic time for a large-scale network.

  Equation 9 is a problem for each transfer device and each node. Since it is possible to calculate Equation 9 in parallel between each transfer device and the arrival / departure node, an optimal route solution for the entire network can be derived at high speed by using a computer capable of parallel calculation in the routing table generation device 10.

  In the present embodiment, the example in which the route information calculated based on Equation 1 by the route calculation device 30 is used as the target value when generating the routing table has been described. However, the route information is input to the routing table generation device 10. The route information is not limited to such route information. For example, optimization of parameters other than the maximum link rate may be used as the objective function. Further, the target value of the optimal traffic volume ratio for each output port shown in FIG. 9 may be set arbitrarily by a person. Further, route information related to routes other than the optimum route may be input as a target value depending on what route is desired to be obtained.

  In the above description, the output port information is included as information indicating the transfer destination in the routing entry. However, the information indicating the transfer destination is information indicating the transfer path (transfer path) (hereinafter referred to as “transfer path”). Information ”)). That is, each routing entry includes a matching rule and forwarding path information. The transfer device 40 determines a transfer path based on a routing entry including a matching rule that matches the traffic to be transferred, and outputs the traffic from an output port corresponding to the transfer path. The correspondence information between the transfer path and the output port is stored in the transfer device 40. Further, the relationship between the transfer path and the output port is not necessarily one-to-one. In this case, the “output port” in the above may be replaced with a “transfer path”. For example, the route information calculated by the route calculation device 30 is information indicating the traffic amount ratio for each transfer path. Therefore, the “optimal traffic volume ratio by output port” in the above may be replaced with the “optimal traffic volume ratio by transfer path”.

  From the above, in the present embodiment, the output port and the transfer path are examples of transfer destinations by the transfer device 40.

  As mentioned above, although the Example of this invention was explained in full detail, this invention is not limited to such specific embodiment, In the range of the summary of this invention described in the claim, various deformation | transformation・ Change is possible.

DESCRIPTION OF SYMBOLS 10 Routing table production | generation apparatus 11 Input information acquisition part 12 Classification | category part 13 Production | generation part 20 Control apparatus 30 Path | route calculation apparatus 40a, 40b, 40c Transfer apparatus 50a, 50b, 50c, 50d Terminal 100 Drive apparatus 101 Recording medium 102 Auxiliary storage apparatus 103 Memory Device 104 CPU
105 Interface device B bus

Claims (5)

For each transfer node for a transfer device that determines a transfer destination of traffic to be transferred using a routing table formed by a plurality of entries each including a different condition and information indicating a transfer destination of traffic that matches the condition. A classifying unit for classifying the set of the ratios for each traffic amount into the groups for each transfer destination by the transfer device;
A generation unit that generates each of the entries so that a transfer destination corresponding to the group into which the ratio is classified matches a condition of the entry according to the ratio;
The classification unit, for each group, the sum of the ratios classified into the group, and the ratio of the traffic amount by transfer destination that is input with respect to the traffic by the destination node with respect to the transfer destination corresponding to the group Classifying a set of traffic volume ratios by entry so that the difference from the target value of
A routing table generation device characterized by the above. The classifier has the following optimization problem:

Where z _i is the difference between the target value and the sum for the i th destination group,
M is the number of entries in the routing table;
N is the number of forwarding destinations,
p _i is the ratio of the traffic volume by destination calculated for the i th destination,
a _i is the sum of the proportions classified into the group corresponding to the i th forwarding destination,
u _ij is 1 when the j-th routing entry is classified into the group corresponding to the i-th forwarding destination, 0 otherwise.
The routing table generation apparatus according to claim 1, wherein the set of traffic volume ratios for each entry is classified by solving the above. Traffic for each transmission / reception node related to a transfer device that determines a transfer destination of a traffic to be transferred using a routing table formed by a plurality of entries each including a different condition and information indicating a transfer destination of the traffic meeting the above condition A classification procedure for classifying the set of percentages for each entry with respect to a quantity into groups for each transfer destination by the transfer device;
The computer executes a generation procedure for generating each entry so that a transfer destination corresponding to the group into which the ratio is classified matches a condition of the entry related to the ratio,
The classification procedure includes, for each group, the sum of the ratios classified into the group and the ratio of the traffic amount for each forwarding destination that is input with respect to the traffic for each destination node with respect to the forwarding destination corresponding to the group. Classifying a set of traffic volume ratios by entry so that the difference from the target value of
A routing table generation method characterized by the above. The classification procedure includes the following optimization problem:

Where z _i is the difference between the target value and the sum for the i th destination group,
M is the number of entries in the routing table;
N is the number of forwarding destinations,
p _i is the ratio of the traffic volume by destination calculated for the i th destination,
a _i is the sum of the proportions classified into the group corresponding to the i th forwarding destination,
u _ij is 1 when the j-th routing entry is classified into the group corresponding to the i-th forwarding destination, 0 otherwise.
The routing table generation method according to claim 3, wherein the set of traffic volume ratios for each entry is classified by solving.   A program for causing a computer to execute the routing table generation method according to claim 3 or 4.

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