KR20170102104A - Service function chaining network system for path optimization and the method for thereof - Google Patents

Abstract

The present invention relates to a service function chaining network system for setting an optimal route, in a service function chaining network system including a control place and a data place, comprises: the control plane which receives input of traffic flow information and information of each node from the data plane, calculates a plurality of routes for chaining of each service function to correspond to a predetermined condition of each node, determines flow to be distributed to a route corresponding to the same, and transmits the result; and the data plane which receives input of the flow and the route result, transmitted from the control plane, and assigns the flow to each route. According to the present invention, an optimal route for each service function chaining (SFC) is determined by considering each SF instance arrangement type and linkage characteristics of a virtual link in a service function chaining network. Incoming traffic flow is optimally assigned to each node and provided. Accordingly, a mobile service provider can maximize a resource utilization rate without wasted resource.

Description

Technical Field [0001] The present invention relates to a service function chaining network system and a method thereof,

The present invention relates to a service function chaining network system and method for establishing an optimal path for efficient resource utilization in service function chaining.

Recently, as the network provides various services, dependency on SF (service function) such as firewall, deep packet inspection (DPI), network address translation (NAT) . Especially, in order to converge various network services in the future Internet environment, there are many studies to manage SF more flexibly through network function virtualization (NFV) technology which provides software virtualization of existing hardware based network service functions .

In addition, for the use of multiple SFs, a reasonable method is needed to transmit the traffic of the corresponding service to the user in a logical order. That is, Service Function Chaining (SFC) is required to order SF as one logical connection according to the requirements of a specific service traffic. The SFC is actively being standardized recently in the Internet Engineering Task Force Working Group (IETF), the international Internet standardization organization, and the ETSI ISG NFV (European telecommunications standards institute industry specification groups network function virtualization).

In addition, telecommunication carriers are also actively seeking to design an SFC framework based on the technical standards and specifications. However, research on effective dynamic algorithms, architectural / protocol specification for requirements has not been done yet. In particular, network resource management such as SF instances and virtual links is one of the important issues in constructing such an SFC framework. Therefore, it is important to set the amount of traffic allocated to each network resource, that is, the path for each service traffic, in order to fully utilize such network resources.

In the present invention, an optimal path for each SFC is set in consideration of the configuration type of each SF instance and the connectivity of a virtual link in a service function chaining network, and an incoming traffic flow is optimally allocated to each node, It is an object of the present invention to provide a service function chaining network system and a method thereof for setting an optimal path for optimizing utilization of SF instance and resources for a link in a chaining framework.

According to an aspect of the present invention, there is provided a service function chaining network system for setting an optimal path, the service function chaining network system including a control plane and a data plane, Information of SF instances installed in the SN, and link information of each node, calculates a plurality of paths for each service function chaining corresponding to predetermined conditions of the respective nodes, and determines a flow to be distributed to the corresponding path A control plane for conveying the result; And a data plane receiving the flow and path results transmitted from the control plane and allocating a flow to each path.

In particular, the control plane receives traffic flow information from the data plane, information of SF instances installed in the SN, link information of each node, and transmits the path result. A route calculation unit for calculating an optimal route using the received traffic flow, information of SF instances installed in the SN, and link information of each node; A condition determiner for determining and providing a predetermined condition of each node when calculating an optimal path in the path calculator; And a storage unit for storing condition data of each of the nodes.

In particular, the path calculation unit is characterized in that it calculates a flow rate assigned to each link and each SF instance.

In particular, the condition determination unit is characterized in that it is determined whether the amount of incoming flow for each node is equal to the amount of outgoing flow.

In particular, the data plane includes an ingress node for assigning a flow to each node corresponding to a traffic flow and a path result transmitted from the control plane; An SN node (Service Node) in which a plurality of servers are arranged to implement an SF (Service Function) instance in the form of a virtual machine; An SSF (Service Function Forwarder) node for forwarding the flow assigned by the ingress node to the SF instance of the SN node; And an Egress node for outputting a flow assigned to each path passing through the in-progress node, the SSF node, and the SN node.

According to another aspect of the present invention, there is provided a service function chaining method for an optimal path setting, the method comprising: receiving traffic flow information on a data plane, information on SF instances installed in an SN, Transmitting information to a control plane; The traffic flow information in the control plane, the information of the SF instances installed in the SN, and the link information of each node, and constructs a path optimization model corresponding to a predetermined condition of each node to generate a plurality of paths for each service function chaining Computing and determining a flow to be distributed to a path corresponding thereto; Delivering the calculated result for each path and the flow result distributed to each path; And assigning a flow to each node at the impression node of the data plane.

In particular, in the step of transmitting the traffic flow information, the SF instances installed in the SN, and the link information of each node to the control plane, the traffic flow currently entering the ingress node of the data plane And transmits link information between an SN node, an SFF node (Service Function Forwarder), and an SF installed in the SN node to the control plane.

In particular, in the step of determining the flow to be distributed, the control plane distinguishes the SFCs for the flow based on the flow and the SFC (Network Service) network topology information, and distributes the SFCs to each of the SFCs It is characterized in that it determines the flow.

In particular, the path optimization model is characterized in that it is constructed by calculating a flow rate assigned to each link and each SF instance.

In particular, the predetermined condition is characterized in that it is judged whether or not the amount of incoming traffic flow for each node is equal to the amount of outgoing traffic flow.

The effects of the present invention are as follows.

First, according to the present invention, an optimal path for each SFC is set in consideration of the configuration type of each SF instance and the connectivity of a virtual link in a service function chaining network, and an incoming traffic flow is optimally allocated to each node By offering Mobile operators can maximize resource utilization without wasting resources.

Second, since the present invention allocates and optimizes traffic flows to each node, a mobile user can receive traffic of many users in a service function chaining network You will feel faster and improved service satisfaction.

FIG. 1 schematically illustrates a configuration of a service function chaining network system in an SFC network topology according to an embodiment of the present invention; FIG.
Fig. 2 is a view schematically showing the configuration of the control plane of Fig. 1; Fig.
3 is a diagram illustrating an operation procedure in an SFC network for optimal path setting.
FIG. 4 is a flowchart illustrating a service function chaining network method for an optimal path setting according to an embodiment of the present invention; FIG.
5 is a diagram showing a result of an optimal path setting method according to an SFC flow amount of the present invention.
6 is a diagram showing a result of an optimal path setting method according to a link capacity of an SFC network of the present invention.

While the present invention has been described in connection with certain exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and similarities. It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, the present invention will be described in detail with reference to the accompanying drawings. In addition, numerals (e.g., first, second, etc.) used in the description of the present invention are merely an identifier for distinguishing one component from another.

Also, in this specification, when an element is referred to as being "connected" or "connected" with another element, the element may be directly connected or directly connected to the other element, It should be understood that, unless an opposite description is present, it may be connected or connected via another element in the middle.

Hereinafter, a cloud storage system and its management method for improving storage performance of a virtual environment according to the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a view schematically showing a configuration of a service function chaining network system of an SFC network topology according to an embodiment of the present invention, and FIG. 2 is a view schematically showing the configuration of the control plane of FIG.

As shown in FIG. 1, a service function chaining network system for optimal path setting according to an embodiment of the present invention includes traffic flow information from a data plane, information of SF instances installed in an SN, and link information A control plane 100 for calculating a plurality of paths for each service function chaining corresponding to a predetermined condition of each node, determining a flow to be distributed to the corresponding path, and transmitting the result, and a control plane 100 And a data plane 200 for receiving a flow and a path result transmitted from the path and allocating a flow to each path.

That is, the service function chaining system is divided into a data plane 200 and a control plane 100. In the data plane 200, each node transmits information necessary for setting a path to the control plane 100 And the SFC flow is processed based on the path set in the control plane 100. [ The control plane 100 sets the optimal path based on the collected information and transmits it to the ingress node of the data plane.

Referring to FIG. 2, the control plane 100 includes a communication unit 110, a path calculation unit 120, a condition determination unit 130, and a storage unit 140.

The communication unit 110 receives traffic flow information from the data plane 200, information of SF instances installed in the SN, and link information of each node, and outputs a path result and a flow allocation ratio calculated in the control plane to the data Plane.

The route calculation unit 120 calculates the optimal route using the input traffic flow information, information of SF instances installed in the SN and link information of each node, and calculates a flow rate allocated to each link and each SF instance .

More specifically, a flow refers to a packet flow of a particular path according to a combination of a plurality of flow entries of a series of packets or multiple switches sharing a value of at least one header field in terms of one switch can do. The open-flow network can perform path control, fault recovery, load balancing and optimization on a flow-by-flow basis.

The path calculation unit may extract flow information from the packet received as user traffic. The flow information includes identification information of an ingress port as a packet inflow port of the edge switch, identification information of an incoming port of the switch of the switch, packet header information (IP address of the source and destination, MAC address, port, And VLAN information, etc.), metadata, and the like.

In addition, information on each node of the data plane includes link information between an Ingress node, an SN node, an SFF node (Service Function Forwarder), and an SF installed in the SN node It will receive and calculate.

The condition determining unit determines and provides a predetermined condition of each node when calculating the optimal path in the path calculating unit, and determines whether the amount of flow incoming by each node is equal to the amount of outgoing flow.

The storage unit may store and manage statistics such as condition data of each node, the amount of traffic for each flow, the processing speed, the number of NFs passed through, and the type thereof.

Wherein the data plane comprises an ingress node for assigning a flow to each node corresponding to a traffic flow and a path result conveyed in a control plane; An SN node (Service Node) in which a plurality of servers are arranged to implement an SF (Service Function) instance in the form of a virtual machine; An SSF (Service Function Forwarder) node for forwarding the flow assigned by the ingress node to the SF instance of the SN node; And an Egress node for outputting a flow assigned to each path passing through the in-progress node, the SSF node, and the SN node.

An operation procedure for setting a path between the control plane and the data plane will be described.

3 is a diagram illustrating an operation procedure in an SFC network for optimal path setting. Referring to FIG. 3, a simple operation process in the present invention is as follows.

First, the ingress node of the data plane is information about the current incoming traffic flow, the SN node (service node) and the SFF node (service function forwarder) are connected to the currently installed SF, the link information between the SN and the SFF or SFF To the control plane. Based on the flow and SFC network topology information, the control plane distinguishes the SFCs for the flows and determines the various paths for each SFC and the flows to be distributed to the paths. The control plane delivers the computed result to the ingress node where the traffic flows. The ingress node of the data plane distributes the flow by each path through the received result. In particular, when distributing, the information about the route is transmitted together so that the SFF can forward it accordingly.

Here, if the route to each node is an SFC to be processed in the order of SF1-> SF2, for example, the ingress node may be divided into two paths: SFF1-> SFF2-> SFF3-> The SF2-> SFF3-> Egress node of SN3 and the SF1-> SFF1-> SFF2-> SN2 of SFF1-> SFF4-> 0.5Gbps, and 1.5Gbps, respectively.

4 is a flowchart of a service function chaining network method for an optimal path setting according to an embodiment of the present invention.

As shown in FIG. 4, the service function chaining method for optimal path setting according to another embodiment of the present invention includes: first, traffic flow information of a data plane, information of SF instances installed in an SN, The step of transmitting information to the control plane is performed (S401).

That is, information on a traffic flow currently entering an ingress node of the data plane is connected to an SN node (Service Node), an SFF node (Service Function Forwarder), and an SF installed in the SN node Link information to the control plane.

The traffic flow information in the control plane, the information of the SF instances installed in the SN, and the link information of each node are received, and a route optimization model is constructed corresponding to a predetermined condition of each node, and a plurality of paths And determining a flow to be distributed to a path corresponding thereto is performed (S402).

The control plane distinguishes the SFCs for the flows based on the flow and SFC (Network Service) network topology information and determines a plurality of paths for each SFC and a flow to be distributed to the corresponding paths, The flow rate assigned to each link and each SF instance is calculated and constructed.

In order to construct the path optimization system model, the structure of each node can be defined as follows.

로 나타낼 수 있다. 노드 집합 V는 SFF(service function forwarder), SN 노드(service node), 인그래스(ingress) 노드, 이그래스(egress) 노드로 구성되어 있으며, 각각은

로 나타낸다. More specifically, the Service Function Chaining (SFC) network topology includes a directional graph

. The node set V consists of a service function forwarder (SFF), an SN node (service node), an ingress node, and an egress node,

Respectively.

는 노드

를 서로 연결하는 링크들의 집합으로써

로 나타낼 수 있다.

는 링크 연결성을 나타내며, 그 값이 1일 경우에는

노드와

노드 간에 링크가 있다는 것을 의미하고, 그 해당 링크 캐패시티는

로 정의한다. 인그래스(Ingress) 노드와 이그레스(egress) 노드는 각각 트래픽 플로우들이 들어오고, 나가는 노드를 의미한다. 특히, 본 모델에서는 앞선 동작과정에서 설명했듯이 제어 평면으로부터 경로 설정에 대한 결과값을 받아 트래픽을 분류하는 IETF SFC의 분류기(classifier) 역할을 인그래스(ingress) 노드가 수행한다. 즉, 인그래스(ingress) 노드에서는 서비스 기능 패스(service function path : SFP)를 다른 노드들이 확인하기 위한 SFC 캡슐화(encapsulation)가 수행된다. Link aggregation

The node

As a set of links connecting

.

Indicates link connectivity, and when the value is 1

Node

Means that there is a link between the nodes, and its corresponding link capacity

. Ingress nodes and egress nodes represent the nodes through which traffic flows in and out, respectively. In particular, in this model, the ingress node performs the role of a classifier of the IETF SFC that classifies the traffic by receiving the result of routing from the control plane, as described in the previous operation. That is, at the ingress node, SFC encapsulation is performed to identify the service function path (SFP) by other nodes.

로 나타낼 수 있다. SN 안에서는 각 SFC의 들어오는 플로우 양에 따라서 다양한 VM 규격으로 SF 인스턴스가 생성될 수 있다. The SN can be regarded as a general-purpose server in which a specific service function SF (Service Function) instance can be implemented as a virtual machine (VM). An SN can have L resource types such as CPU, memory, disk, and so on. Thus, the capacity set of the L resource types of one SN i is

. In the SN, SF instances can be created in various VM standards according to the flow amount of each SFC.

개의 VM 클래스를 가정하며, 이 집합은

로 나타낼 수 있다. SN은

개 타입의 자원 유형을 가지고 있어 각 VM 클래스

는 SN에 대한

개 타입의 자원 요구량을 가지게 된다. 이 자원 요구량 집합은

로 나타낼 수 있으며, 이 자원 요구량에 따라서 미리 정의된 프로세싱 캐패시티를

로 정의한다. 또한, 한 SN

안의 SF

에 대한 각 클래스

개수의 집합은

로 나타낸다. So in this model

Assume that there are two VM classes,

. SN

Each type of resource class has its own class

For SN

Type resource needs. This resource requirement set

, And the pre-defined processing capacity according to the resource requirement

. Also, one SN

Inside SF

For each class

The set of numbers

Respectively.

In the network topology of this model, the SFF only serves as a forwarding function to the SF instances within another SFF or SN. This forwarding can be performed by checking the SFP information in the SFC encapsulation. Thus, the link connects the SFF or the SFF and the SN, including the ingress node and the egress node.

로 나타낼 수 있다. 또한

개의 SF로 구성될 수 있는

개의 네트워크 서비스, 즉

개의 SFC를 고려한다. 이 S개의 SFC 집합은

로 나타낼 수 있다. SFC

에 해당하는 트래픽 플로우들은 정의된 SF 순서

에 맞게 처리되어야 하며,

는 SFC

의

번째 SF를 뜻한다. 각 SFC에는 같은 SF라도 다른 순서에 배치될 수 있기 때문에 SFC의 집합과 SF 집합을 맵핑(mapping) 시키기 위해 SF 할당 함수

을 사용한다. 예를 들어,

이면, SFC

의

번째 SF는

이 된다. At this time, it is assumed that a total of M SFs can be implemented within the configured network topology. The M SF sets

. Also

Can be composed of SFs

Network services, namely

SFCs are considered. This S SFC set

. SFC

Lt; RTI ID = 0.0 > SF < / RTI &

Should be treated,

SFC

of

SF. In order to map the SFC set and the SF set to each SFC, the SF allocation function

Lt; / RTI > E.g,

If SFC

of

The second SF

.

에 대해서 다수의 SN에 VM 클래스

를 가지고 인스턴스가 생성될 수 있다. 따라서 이를 나타내기 위해 SF 인스턴스 배치에 대한 지시 함수인

을 도입한다. 예를 들어,

은 SF

의 인스턴스가 SN

안에 VM 클래스

를 가지고,

번째로 생성되었다는 것을 의미한다. 각 SFC가 요구되는 여러 사용자들에 의해서 발생된 트래픽 플로우는 인그래스(ingress) 노드에서 모인다고 가정하며, SFC s에 대한 트래픽 플로우 양은

로 정의한다. 직관적으로, 한 SF 인스턴스로 들어오거나 한 링크를 지나는 플로우의 양은 그 해당 캐패시티를 넘어설 수는 없다. 따라서 한 SFC s에 대한 플로우는 여러 개의 SFP로 분배될 수 있으며, 이를 위해서 각 링크와 SF 인스턴스에 할당되는 플로우 양을 구해야 한다. 이러한 양을 결정하기 위한 결정 변수로써 0과 1사이의 범위를 갖는

를

도입한다.

는 SF

를 이미 처리하고 링크

를 지나는 플로우 비율을 의미한다. 또한, 한 SF에 대해 다수의 인스턴스가 한 SN 안에 존재할 수 있기 때문에

는 SF

를 이미 처리하고 SN

의 VM class

에 해당하는 n번째 인스턴스로 분배되는 플로우 비율을 의미한다. 이러한

와

가 가질 수 있는 가능한 모든 값들의 집합을

라고 정의한다.Also, the same SF

RTI ID = 0.0 > VM < / RTI &

The instance can be created. Thus, to indicate this, we use an indicator function

Lt; / RTI > E.g,

SF

Instance of SN

Inside the VM class

Lt; / RTI &

It means that it was generated the second time. It is assumed that the traffic flow generated by multiple users requiring each SFC is aggregated at the ingress node, and the traffic flow amount for SFC s is

. Intuitively, the amount of flow that enters an SF instance or traverses a link can not exceed its corresponding capacity. Therefore, the flow for one SFC s can be distributed to several SFPs. To do this, the flow amount allocated to each link and SF instance must be obtained. As a decision variable for determining this amount, a range between 0 and 1

To

.

SF

Has already been processed and the link

Quot; flow rate " Also, since there can be multiple instances for one SF in one SN

SF

Lt; RTI ID = 0.0 > SN

VM class

Which is distributed to the n-th instance corresponding to the n-th instance. Such

Wow

The set of all possible values that

.

On the other hand, optimization constraints are designed based on the path optimization system model.

Optimization objective functions and constraints

에 대해서 네트워크 자원 사용량을 최소화하기 위해 모든 링크에 대한

와 모든 SF 인스턴스에 대한

를 구하는 것이다. 이는 활용할 수 있는 자원을 최대화시킬 수 있기 때문에 더 많은 플로우을 수용할 수 있으며, 네트워크 자원 이용률을 높일 수 있다. The purpose of the preceding optimization constraint is to give a given flow

To minimize network resource usage.

And for all SF instances

. This can maximize available resources, accommodate more flows, and increase network resource utilization.

은 하기 수식 1과 같이 나타낼 수 있다.The objective function of the optimization problem, the network resource usage

Can be expressed as Equation 1 below.

Equation 1

와

는 각각 링크의 수와 SF 인스턴스 수를 나타내며, 각 변수의

는 SFC

의 플로우가 어떠한 SF에 대해서도 아직 처리되지 않았다는 것을 의미한다.

Wow

Represents the number of links and the number of SF instances,

SFC

Of the flow has not yet been processed for any SF.

Based on this objective function, we next explain the constraints of the optimization problem.

First, we describe the constraints on traffic flow preservation. In particular, due to the nature of SFC, the flow must be preserved taking into account the ordered SF in the SFC. First, the amount of flow into and out of each SFF must be the same. In this case, it is important whether SFs ordered in each SFC are processed. Therefore, this constraint condition is expressed by the following equation same.

Equation 2

As with SFF, the amount of incoming flow and the amount of outgoing flow must be the same for SN. At this time, unlike the SFF, it is necessary to consider this because the flow processing is performed on the specific SF of each SFC in the SN. Therefore, this constraint condition is expressed by Equation 3 below.

Equation 3

Also, a flow can be assigned to an instance located at a different SN for the SF of one SFC. Therefore, the amount of flow into a plurality of SNs must be equal to the flow amount of the corresponding SFC. This constraint is shown in Equation 4 below.

Equation 4

Since the ingress node is the node from which the SFC flows, the flow from the ingress node must not be processed for any SF. This constraint can be expressed as Equation 5 below.

Equation 5

As an egress node, all flows must be processed for all SFs of the SFC, as opposed to an ingress node, as shown in Equation 6 below.

Equation 6

The relationship between the two flow rate variables, which is the final decision variable of the flow preservation constraint, is shown in Equation (7).

Equation 7

Next, the constraints related to the resource capacity are described. First, since the sum of the flow amounts passing through one link can not exceed the capacity of the link, it is expressed as the following Expression 8.

Equation 8

Similarly, the sum of the amount of flow that is allocated to an SF instance must not exceed the capacity of that instance (i.e., VM). This constraint is expressed by the following equation (9).

Equation 9

의 플로우가

에 의해서 처리가 되었다면, 다음은 SF

의 인스턴스가 존재하는 SN으로 유입되어야 한다. 이 제약 조건은 다음 수식 10과 같이 나타낼 수 있다.Finally, the flow must be processed to the SF order defined in the SFC as an important constraint in the SFC. For example, SFC

The flow of

, The next step is to perform the SF

Lt; RTI ID = 0.0 > SN < / RTI > This constraint can be expressed as in Equation 10 below.

Equation 10

와

에 대해서 선형적으로 설계되어 있기 때문에 선형 프로그래밍(LP: Linear Programming)라는 것을 알 수 있다. LP는 충분히 다항 시간 내에 풀어내는 종래의 알고리즘이 구현된 LP 솔버(solver)로 해결이 가능하다.Therefore, considering the objective function and the constraint condition of the path optimization condition of the present invention,

Wow

Linear programming (LP: Linear Programming). LP can be solved with a LP solver implemented with a conventional algorithm that solves the problem in polynomial time sufficiently.

Then, the calculated result for each path and the flow result distributed to each path are transmitted (S403).

In step S404, a flow is assigned to each node in the inline node of the data plane.

Example of simulation result

A simulation is implemented using a route optimization model of the service function chaining network system of the present invention.

The simulation topology used the Abliene network topology, which is a research network of Internet2, and four SFs (Firewall, Proxy, IDS, NAT) and two SFCs: 1) Firewall-IDS-NAT , And 2) Proxy-Firewall-NAT. In addition, only one resource type of the vCPU is assumed, and three VM classes (resource requirement-capacity: 1vCPU-0.5Gbps / 2vCPU-1Gbps / 4vCPU-2Gbps) are used. The result is compared with the optimal value (OPT: Optimal) solved using the LP solver and two algorithms.

)과 처리되지 못한 플로우 양 (

)로 보여준다.The first algorithm, uniform distribution (UD), is an algorithm that distributes the flows evenly regardless of the SF instance capacity. The second algorithm, PD (Proportional Distribution: PD), is an algorithm that distributes flows in proportion to the SF instance capacity to be. In particular, the performance measurement is based on the network resource usage (< RTI ID = 0.0 >

) And the amount of unprocessed flow (

).

FIG. 5 is a diagram showing a result of an optimal path setting method according to an SFC flow amount of the present invention, FIG. 6 is a diagram showing a result of an optimal path setting method according to link capacity of an SFC network of the present invention to be.

As shown in FIG. 5 and FIG. 6, the simulation topology is used to show the result when the given flow amount and link capacity of the SFC increase, respectively. OPT can see that it can handle all traffic flows by distributing the flow optimally regardless of flow amount and link capacity, while UD and PD can not fully utilize resources of some links and SF instances, An amount of flow occurs. In addition, since OPT and both algorithms are assigned more links and SF instances for a given capacity, network resource usage increases with increasing flow amount. Conversely, as the link capacity increases for a given flow, more flows can be allocated, so that as the link capacity increases, the network resource usage decreases.

The scope of the present invention is not limited to the above-described embodiments, but may be embodied in various forms of embodiments within the scope of the appended claims. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention as defined by the appended claims.

100 --- Control plane 110 --- Communication part
120 --- Path calculation unit 130 --- Condition determination unit
140 --- Storage part 200 --- Data plane
210 --- Ingram node 220 --- SN node
230 --- SFF node 240 --- SF node
250 --- Grease node

Claims (10)

A service function chaining network system comprising a control plane and a data plane,
Receiving traffic flow information from the data plane, information of SF instances installed in the SN, and link information of each node, calculating a plurality of paths for each service function chaining corresponding to a predetermined condition of each node, A control plane for determining a flow to be distributed to and delivering the result; And
And a data plane for receiving a flow and a path result transmitted from the control plane and allocating a flow to each path.
The method according to claim 1,
The control plane
A communication unit receiving traffic flow information from the data plane, information of SF instances installed in the SN, and link information of each node, and transmitting the path result;
A path calculation unit for calculating an optimal path using the received traffic flow information, information of SF instances installed in the SN, and link information of each node;
A condition determiner for determining and providing a predetermined condition of each node when calculating an optimal path in the path calculator;
And a storage unit for storing condition data of each of the nodes.
3. The method of claim 2,
Wherein the path calculation unit calculates a flow rate allocated to each link and each SF instance.
3. The method of claim 2,
Wherein the condition determination unit determines whether or not the amount of flow incoming by each node is equal to the amount of outgoing flow for each node.
The method according to claim 1,
The data plane
An ingress node for assigning a flow to each node corresponding to a traffic flow and a route result delivered from the control plane;
An SN node (Service Node) in which a plurality of servers are arranged to implement an SF (Service Function) instance in the form of a virtual machine;
An SSF (Service Function Forwarder) node for forwarding the flow assigned by the ingress node to the SF instance of the SN node;
And an Egress node for outputting a flow assigned to each path passing through the in-progress node, the SSF node, and the SN node.
Transmitting traffic flow information of a data plane, information of SF instances installed in the SN, and link information of each node to a control plane;
The traffic flow information in the control plane, the information of the SF instances installed in the SN, and the link information of each node, and constructs a path optimization model corresponding to a predetermined condition of each node to generate a plurality of paths for each service function chaining Computing and determining a flow to be distributed to a path corresponding thereto;
Delivering the calculated result for each path and the flow result distributed to each path; And
And assigning a flow to each node at the ingress node of the data plane as a result of the forwarding.
The method according to claim 6,
Information on the traffic flows currently entering the ingress node of the data plane in the step of transmitting the traffic flow information, the SF instances installed in the SN, and the link information of each node to the control plane, Link information and flow processing capacity connected between an SN node (Service Node), an SFF node (Service Function Forwarder), and an SF installed in the SN node are transmitted to a control plane. Functional chaining method.
The method according to claim 6,
In the step of determining the flow to be distributed, the control plane distinguishes the SFC for the flow based on the flow and the SFC (Network Service) network topology information, and determines a plurality of paths for each SFC and a flow to be distributed to each corresponding path And a service function chaining method for optimal path setting.
The method according to claim 6,
Wherein the path optimization model is constructed by calculating a flow rate allocated to each link and each SF instance.
The method according to claim 6,
Wherein the predetermined condition is to determine whether the amount of incoming traffic flow and the amount of outgoing traffic flow for each node are the same.

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