KR20170020188A - Apparatus and Method for Collecting Adaptive Flow Statistics Data in Carrier Network - Google Patents

Apparatus and Method for Collecting Adaptive Flow Statistics Data in Carrier Network Download PDF

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KR20170020188A
KR20170020188A KR1020150150209A KR20150150209A KR20170020188A KR 20170020188 A KR20170020188 A KR 20170020188A KR 1020150150209 A KR1020150150209 A KR 1020150150209A KR 20150150209 A KR20150150209 A KR 20150150209A KR 20170020188 A KR20170020188 A KR 20170020188A
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South Korea
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flow
collection
collection period
type
types
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KR1020150150209A
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Korean (ko)
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KR101990283B1 (en
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최태상
조충래
김영화
윤상식
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한국전자통신연구원
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/02—Standardisation; Integration
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/142—Network analysis or design using statistical or mathematical methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
    • H04L41/5061—Network service management, e.g. ensuring proper service fulfilment according to agreements characterised by the interaction between service providers and their network customers, e.g. customer relationship management

Abstract

The present invention relates to an apparatus for collecting adaptive flow statistical data includes a node type collecting unit which collects a flow by connecting to a network node, a flow type calculating unit which calculates two or more flow types according to a flow sustaining length and request the flow statistical data collection of a type corresponding to the node type collecting unit at each collection period corresponding to each of the two or more flow types, and a flow statistics storage unit which stores the two or more flow types calculated in the flow type calculating unit and stores the flow statistical data collected by the node type collecting unit as a table shape according to each of the two or more flow types. Accordingly, the present invention can secure resource expandability, accuracy, and heterogeneous independence of a large network at the same time.

Description

[0001] Apparatus and method for collecting adaptive flow statistics data in a carrier network [0002]

The present invention relates to a carrier network, and more particularly to an apparatus and method for collecting traffic flow statistical data.

Carrier networks are networks operated by large-scale wireline and wireless carriers such as cloud data centers, large enterprise networks, and wired and wireless carrier networks. The number of network devices that must be managed, such as routers and switches, is in the tens to hundreds of thousands. In order to collect traffic statistics information in such a large-scale network, it is important to ensure scalability and maintain accuracy basically.

In addition, due to the nature of carrier networks composed of large-scale wired and wireless networks including Software Defined Network (SDN) and Network Function Virtualization (NFV), there are various types of network equipment of this type, A possible solution is required.

However, the current traffic flow statistic data collection technology does not have a solution satisfying the above three conditions of scalability, accuracy and heterogeneous independence simultaneously. In other words, there are solutions that can guarantee scalability by collecting all flow statistical data without sampling or scalability guarantee solution by sampling, but it is difficult to guarantee scalability for large networks and can not accommodate heterogeneous network equipments.

The present invention provides an apparatus and method for collecting adaptive flow statistical data in a carrier network that simultaneously guarantees resource scalability, accuracy, and heterogeneity of a large network.

The present invention relates to an adaptive flow statistics data collecting apparatus, comprising: a node type collector for connecting to a network node and collecting a flow; calculating two or more flow types according to the flow duration length; A flow type calculation unit for requesting collection of an adaptive flow statistic data of a type corresponding to the node type collection unit for each collection period, and a flow type calculation unit for storing two or more flow types calculated in the flow type calculation unit, And a flow statistic storage unit for storing the flow statistical data collected by the two or more flow types in a table form.

The present invention relates to an adaptive flow statistical data collection method comprising the steps of: calculating two or more flow types according to a flow duration length; collecting, for each collection period corresponding to each of the two or more flow types, And storing the collected flow statistical data in a table form for each of the two or more flow types.

The present invention provides scalable, accurate, and flow statistical data collection mechanisms that are independent of the type of network equipment, thereby enabling large-scale carrier network operators to meet various customer service quality requirements in traffic management, It is possible to secure a favorable position for attracting customers through service differentiation.

Accordingly, the present invention can be applied to the performance, security, and billing management of a carrier network, which is a large-scale wired / wireless communication service provider that needs to collect traffic flow statistical data that ensures scalability, accuracy, and heterogeneity. It can be applied not only to carrier networks but also to performance, security, and billing management of networks such as existing and software-defined cloud data centers, large enterprises, and the Internet, which are small in size.

1 is a system configuration diagram including an apparatus for collecting adaptive flow statistics data in a carrier network according to an embodiment of the present invention.
2 is a flowchart illustrating a method of collecting adaptive flow statistics data in a carrier network according to an embodiment of the present invention.
3A to 3C are views for explaining a task according to a minimum collection period according to an embodiment of the present invention.
4A and 4B are views for explaining a task according to an n collection period according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the like elements throughout.

In the following description of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear.

The terms used throughout the specification are defined in consideration of the functions in the embodiments of the present invention and can be sufficiently modified according to the intentions and customs of the user or the operator. It should be based on the contents of.

1 is a system configuration diagram including an apparatus for collecting adaptive flow statistics data in a carrier network according to an embodiment of the present invention.

Referring to FIG. 1, an adaptive flow statistics data collection device 30 in a carrier network provides flow statistics data collected from a network equipment group 10 to an application / management system 20.

Here, the network equipment group 10 refers to various types of network equipment used in a wired / wireless carrier network to be a traffic flow collection target. As an example of a wired network equipment, a router and a switch equipment may be included. Examples of wireless network equipment include a Wi-Fi access pointer, a mobile communication switching device, a network equipment for a mobile communication core, an open flow switch supporting an SDN network, And the like. Therefore, according to an embodiment of the present invention, the network equipment group 10 can be classified and managed into various node types 10-1, 10-2, ... 10-m according to its type.

According to an embodiment of the present invention, the network equipment can support the function of calculating traffic statistical data for each flow. Flow statistical data calculation function is calculated by standard method such as Netflow in existing router or switch equipment, and internal flow statistics data is calculated by open flow switch. For devices that do not support this method, you can calculate flow statistical data in other ways yourself.

The application / management system 20 also includes various applications requiring traffic flow statistical data, a legacy management system such as an NMS (Network Management System) / OSS (Operations Support System), or a SDN (Software Defined Network) / NFV Network Function Virtualization) management system. Here, an example of the application may include traffic engineering, a traffic classifier for service chaining, network security, and billing.

The adaptive flow statistics data collecting apparatus 30 according to an embodiment of the present invention includes at least two flow collecting adapters 100-1, 100-2, ..., 100-m and a gateway 150 .

According to one embodiment, the flow acquisition adapters 100-1, 100-2, ..., 100-m connect to one of the heterogeneous network node types and collect flows occurring in the connected node type . For example, when the network node to be collected is an open flow switch, the node type collecting units 110-1 and 110-2 included in the flow collecting adapters 100-1, 100-2, ..., , ..., 110-m) collects the flow from the open-flow switch. When the network node to be collected is a router or a switch, the node type collecting units 110-1 and 110-2 included in the flow collecting adapters 100-1, 100-2, ..., and 100- , ..., 110-m) collects flows from routers or switches.

More specifically, the flow acquisition adapters 100-1, 100-2, ..., and 100-m include two or more node type collectors 110-1, 110-2, ..., Unit 120, a flow statistics storage unit 130, and a flow sampling unit 140.

Two or more node type collectors 110-1, 110-2,... 110-m connect to one of the heterogeneous network node types and collect flows occurring in the connected node type. More specifically, the two or more node type collecting units 110-1, 110-2, ..., 110-m access the network equipment group 10 at the request of the flow type calculating unit 120, And stores the collected flow statistical data in the flow statistic storage unit 130. The flow type calculation unit 120 calculates two or more flow types according to the flow duration length, and calculates the flow rate of each of the node type collectors 110-1, 110-2, ... 110 -m). < / RTI > That is, by varying the collection period according to the flow type, the statistical data collection period for the long-lasting flow can be made longer. Thus, the present invention can improve performance in flow collection.

Here, the two or more collection periods may include a minimum collection period and one or more collection periods having a multiple of the minimum collection period. For example, if the collection period is three, the minimum collection period is s, the medium length collection period can be s * m, the longest collection period can be s * l, and the entire collection period can be s * m * l. < / RTI >

In addition, one of the important features of the present invention is that among all current flows, a temporary flow is generated and terminated below a minimum period, and does not collect the corresponding temporary flows at the time of each collection. This temporary flow corresponds to most of the traffic currently flowing in the network equipment 10, and has the merit of solving both performance guarantee and scalability problems.

The flow sampling unit 140 provides a sampling flow set. When performing the type-specific flow collection performed by the flow-type calculation unit 120, the flow sampling unit 140 performs a function for sampling some flows other than all the flows in order to increase the efficiency of collection do. Here, various sampling algorithms including random, Top-n, statistical method, and the like can be used as the sampling method.

When the sampling is required, the flow type calculation unit 120 performs a sampling request for the type flow corresponding to the collection period to the flow sampling unit 140 at each collection period corresponding to each of the two or more flow types, (110-1, 110-2, ... 110-m) to a type flow sampling set corresponding to the collection period, as it receives a sampling set for the type flow corresponding to the collection period from the node type collection units To collect flow statistical data.

The flow type calculation unit 120 sets the timers corresponding to each of the two or more collection periods, and performs, in parallel, two or more tasks corresponding to each of the two or more collection periods as the timers are woken up. 1, the flow type calculation unit 120 may include a collection period setting unit 121, a minimum collection period task processing unit 122, and at least one n collection period task processing unit 123. [ For convenience of explanation, collectors other than the minimum collection period will be referred to as n collection periods. For example, if the collection period is three, the collection period of intermediate length or longest length can be classified into n collection periods. As described above, the minimum collection period task processor 122 and the at least one n collection period task processor 123 each request the flow collection adapter 110 to collect flow statistical data as the set timer is woken up.

However, according to one embodiment, when the current collection period is the initial collection period, the minimum collection period task processing unit 122 updates all of the node type collectors 110-1, 110-2, ... 110- Requests collection of statistical data for the flow type.

In addition, the minimum collection cycle task processor 122 may determine that the node type collectors 110-1, 110-2,... 110-m are in a full collection period with the current collection period having a common multiple of two or more collection periods, To collect statistical data for all flow types. Then, in the entire collection period, the minimum collection cycle task processor 122 performs the collection operation for all the flow types, so that the at least one n collection cycle task processor 123 omits the collection operation. Herein, in the entire collection period, the minimum collection cycle task processor 122 is described as performing collection operations for all flow types, but the present invention is not limited thereto. That is, in the entire collection cycle, only one of the minimum collection cycle task processor 122 and one or more n collection cycle task processors 123 may perform the collection operation for all the flow types.

The flow statistics storage unit 130 stores two or more flow types calculated by the flow type calculation unit 120 and stores the flow types collected by the node type collectors 110-1, 110-2, ..., 110-m The flow statistical data is stored in a table form for each of two or more flow types. Also, the flow statistics storage unit 130 performs flow storage lifecycle management such as modification, search, and deletion.

The gateway 150 delivers the flow statistical data retrieved from the flow statistics storage unit 130 according to a request from an external application or management system. That is, it functions as an external interface of the adaptive flow statistic data collection device 30.

2 is a flowchart illustrating an adaptive flow statistical data collection method according to an embodiment of the present invention.

Referring to FIG. 2, an adaptive flow statistical data collection device (hereinafter referred to as a " device ") 30 calculates two or more flow types according to the flow duration length and sets two or more corresponding collection periods ). Here, the collection period may be more than two, for example, the initial values for short, medium, long, and whole collection periods, which are types of flows, are set as default values. The two or more collection periods include a minimum collection period and one or more collection periods having a multiple of the minimum collection period. The device 30 sets up a task to be executed for each cycle in conjunction with a timer.

The device 30 then collects corresponding types of flow statistical data for each of the two or more flow types corresponding to each of the two flow types (S220).

The device 30 stores the collected flow statistical data in a table form for each of two or more flow types (S230), and transmits the stored flow statistical data according to a request of an external application or a management system (S240).

3A to 3C are views for explaining a task according to a minimum collection period according to an embodiment of the present invention. FIG. 3A is a flowchart of a task operation according to a minimum collection cycle by the flow type calculation unit 120, FIGS. 3B and 3C show a signal flow between internal components of the apparatus 30 for performing a task according to a minimum collection cycle Fig.

Referring to FIGS. 3A and 3B, the flow type calculation unit 120 of the apparatus 30 monitors whether the minimum collection cycle timer is woken up (S310). When the minimum collection cycle timer is woken up as a result of monitoring in S310, the flow type calculation unit 120 performs the minimum collection cycle task processing unit 122. [ The minimum collection period task processor 122 determines whether the current collection period is the initial collection period or the entire collection period (S320).

As a result of the determination in step S320, in the case of the first collection or the entire collection period, the flow type calculation unit 120 determines whether sampling is performed (S330).

As a result of the determination in S330, if the sampling is not to be performed, the flow type calculation unit 120 requests statistical collection of all flow entries (S340). That is, the flow type calculation unit 120 requests the node type collecting units 110-1, 110-2, ..., 110-m to collect statistical data for all flows (S341) 110-1, 110-2,... 110-m collect statistical data for all flows and store them in the flow statistics storage unit 130 (S342).

On the other hand, if it is determined in step S330 that sampling is to be performed, the flow type calculation unit 120 requests collection of all the flow entry statistics based on the sampling (S350). That is, the flow type calculation unit 120 requests the flow sampling unit 140 to perform sampling for all the flows (S351), and the flow sampling unit 140 generates a sampling set for all the flows, 120 (S352). Then, the flow type calculation unit 120 requests the node type collecting units 110-1, 110-2, ... 110-m to collect statistical data on the sampling flow sets for all the flows (S353) The node type collecting units 110-1, 110-2,... 110-m collect statistical data for the sampling flow set and store them in the flow statistic storage unit 130 (S354). Then, the minimum collection period task processor 122 slips during the minimum collection period (S360).

3A and 3C, the minimum collection period processing unit 122 recalculates all the stored flow types and stores the flow entries in the corresponding type-specific table (step S320) (S370). That is, the flow type calculation unit 120 requests all the flow searches stored in the flow statistics storage unit 130 (S371), and if all of the flow search information stored in the flow statistics storage unit 130 is answered (S372) Flow type calculation is performed again for all types of flows at present (S373). The flow type calculation unit 120 requests the flow statistics storage unit 130 to store all the newly calculated flow types (S374), and the flow statistics storage unit 130 responds to store all flows (S375).

Then, the minimum collection period task processor 122 determines whether sampling is performed (S380). If it is determined in step S380 that sampling is not to be performed, the minimum collection period task processor 122 requests collection of the minimum collection period flow entry statistics (S390). That is, the flow type calculating unit 120 requests the flow collecting adapter 110 to collect statistical data for the flow of the minimum length type (S386), and the node type collecting units 110-1, 110-2, ..., 110-m collect statistical data for the flow of the minimum length type and store it in the flow statistic storage unit 130 (S387).

On the other hand, if it is determined in step S380 that sampling is to be performed, the minimum collection period task processor 122 requests collection of only the sampling-based minimum collection cycle flow entry statistics (S395). That is, the flow type calculation unit 120 requests the flow sampling unit 140 to perform sampling for the minimum length flow (S391), and the flow sampling unit 140 generates a sampling set for the flow of the minimum length type, To the type calculation unit 120 (S392). Then, the flow type calculation unit 120 requests the node type collecting units 110-1, 110-2,... 110-m to collect statistical data on the sampling flow set for the flow of the minimum length type (S393 The node type collecting units 110-1, 110-2,... 110-m collect statistical data for the sampling flow set and store them in the flow statistic storage unit 130 (S394). Then, the minimum collection period task processor 122 slips during the minimum collection period (S360).

4A and 4B are views for explaining a task according to an n collection period according to an embodiment of the present invention. 4A is a flowchart of a task operation according to an n collection period by the flow type calculation unit 120, and FIG. 4B is a diagram illustrating a signal flow between internal elements of the apparatus 30 for performing a task according to a minimum collection period FIG.

Referring to FIG. 4, the n collection period task processor 123 of the device 30 monitors whether the n collection cycle timer is woken up (S410). When the n collection period timer is woken up as a result of the monitoring at S410, the n collection period task processor 123 determines whether the current collection period is the total collection period (S420). If it is determined in step S420 that this is the entire collection period, the n collection period processing unit 123 skips the collection operation and proceeds to step S460. This collects statistical data for all flow types in the minimum collection period task processor 122.

On the other hand, if it is determined in step S420 that the entire collection period is not satisfied, the n collection period task processing unit 123 determines whether sampling is performed (S430).

As a result of the determination in S430, if the sampling is not performed, the n collection period task processor 123 requests the statistics collection of the n collection period flow entry (S440). That is, the flow type calculation unit 120 requests the node type collecting units 110-1, 110-2, ..., 110-m to collect statistical data for n-length type flows (S441) The collecting units 110-1, 110-2,... 110-m collect statistical data for n-length type flows and store them in the flow statistic storage unit 130 (S442).

On the other hand, if it is determined in step S430 that sampling is to be performed, the n-collection period task processor 123 requests collection of flow entry statistics of the sampling-based n collection period (S450). That is, the flow type calculation unit 120 requests the flow sampling unit 140 to sample the flow of the n-length type (S451), and the flow sampling unit 140 generates a sampling set for the flow of the n-length type And transfers it to the flow type calculation unit 120 (S452). Then, the flow type calculation unit 120 requests the node type collecting units 110-1, 110-2, ... 110-m to collect statistical data on the sampling flow set for the flow of the n-length type (S453 ), And the node type collecting units 110-1, 110-2,... 110-m collect statistical data for the sampling flow set and store them in the flow statistic storage unit 130 (S454). Thereafter, the n collection period task processor 123 slips during the n collection period (S460).

Claims (17)

A node type collector for connecting to a network node and collecting a flow;
A flow type calculation unit for calculating two or more flow types according to the flow duration length and for collecting a flow statistic data of a type corresponding to the node type collection unit for each collection period corresponding to each of the two or more flow types;
And a flow statistics storage unit for storing two or more flow types calculated by the flow type calculation unit and storing the flow statistical data collected by the node type collection unit in a table form for each of the two or more flow types. Adapted flow statistics data collection device.
The method according to claim 1,
Further comprising a gateway for transferring the flow statistical data retrieved from the flow statistic storage unit according to a request from an external application or a management system.
The apparatus of claim 1, wherein the node type collector
And at least two node type collectors for connecting to one of the heterogeneous network node types and collecting flows occurring in the connected node type.
The method according to claim 1,
Further comprising an adaptive flow sampling unit for providing a sampling flow set,
The flow type calculation unit
Performing a sampling request for a type flow corresponding to a collection period in the sampling unit at every collection period corresponding to each of the two or more flow types, and receiving a sampling set for the type flow corresponding to the collection period from the sampling unit And requests the node type collection unit to collect flow statistical data for a type flow sampling set corresponding to the collection period.
2. The method of claim 1, wherein the two or more collection periods
A minimum collection period, and at least one collection period having a multiple of the minimum collection period.
6. The method of claim 5,
Wherein the minimum collection period is s, the medium length collection period is s * m, and the maximum length collection period is s * l when the collection period is three.
The apparatus of claim 1, wherein the flow type calculation unit
Wherein the node type collection unit requests collection of statistical data for all flow types when the current collection period is the minimum collection period and the initial collection period of the two or more collection periods.
The apparatus of claim 1, wherein the flow type calculation unit
And collects statistical data for all flow types in the node type collection unit when the current collection period is an entire collection period having a common multiple of the two or more collection periods.
The apparatus of claim 1, wherein the flow type calculation unit
Characterized in that it sets the timers corresponding to each of the two or more collection periods and performs in parallel the two or more tasks corresponding to each of the two or more collection periods as the timers are woken up .
10. The method of claim 9,
If the current collection period is a minimum collection period and a whole collection period with a common multiple of one or more collection periods with a multiple of the minimum collection period, then only one of the tasks will have And requesting statistical data collection.
Calculating two or more flow types according to the flow duration length,
Collecting flow statistics data of a corresponding type for each collection period corresponding to each of the two or more flow types;
And storing the collected flow statistical data in a table form for each of the two or more flow types.
12. The method of claim 11,
Further comprising the step of transmitting the stored flow statistical data according to a request of an external application or a management system.
12. The method of claim 11, wherein collecting comprises:
Wherein each of the nodes is connected to one of the heterogeneous network node types, and the flows occurring in the connected node types are separately collected.
12. The method of claim 11, wherein collecting comprises:
Acquiring a sampling set for a corresponding type flow corresponding to each of the two or more flow types at each collection period;
And collecting flow statistical data for a type flow sampling set corresponding to the collection period.
12. The method of claim 11, wherein the two or more collection periods
At least one collection period having a minimum collection period and a multiple of the minimum collection period,
The collecting step
Wherein statistical data for all flow types is collected when the current collection period is a minimum collection period and an initial collection period of at least two collection periods.
12. The method of claim 11, wherein the two or more collection periods
At least one collection period having a minimum collection period and a multiple of the minimum collection period,
The collecting step
And collecting statistical data for all flow types when the current collection period is an entire collection period having a common multiple of the two or more collection periods.
12. The method of claim 11, wherein collecting comprises:
Setting timers corresponding to each of the two or more collection periods,
Performing in parallel the two or more tasks corresponding to each of the two or more collection periods as the timers are woken up.
KR1020150150209A 2015-08-13 2015-10-28 Apparatus and Method for Collecting Adaptive Flow Statistics Data in Carrier Network KR101990283B1 (en)

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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7782793B2 (en) * 2005-09-15 2010-08-24 Alcatel Lucent Statistical trace-based methods for real-time traffic classification
US8300525B1 (en) * 2009-01-30 2012-10-30 Juniper Networks, Inc. Managing a flow table

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7782793B2 (en) * 2005-09-15 2010-08-24 Alcatel Lucent Statistical trace-based methods for real-time traffic classification
US8300525B1 (en) * 2009-01-30 2012-10-30 Juniper Networks, Inc. Managing a flow table

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