CN112491601B - Traffic topology generation method and device, storage medium and electronic equipment - Google Patents
Traffic topology generation method and device, storage medium and electronic equipment Download PDFInfo
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- CN112491601B CN112491601B CN202011282086.3A CN202011282086A CN112491601B CN 112491601 B CN112491601 B CN 112491601B CN 202011282086 A CN202011282086 A CN 202011282086A CN 112491601 B CN112491601 B CN 112491601B
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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
- H04L41/12—Discovery or management of network topologies
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/12—Avoiding congestion; Recovering from congestion
- H04L47/125—Avoiding congestion; Recovering from congestion by balancing the load, e.g. traffic engineering
Abstract
The disclosure relates to a traffic topology generation method, a traffic topology generation device, a storage medium and an electronic device, and aims to provide a new traffic topology generation mode and improve traffic topology generation efficiency. The traffic topology generation method comprises the following steps: acquiring log information of a source station load balancing node, wherein the source station load balancing node is deployed in a data center where a source station is located, and the log information comprises flow parameter information of a plurality of user requests received by the source station; analyzing the flow parameter information included in the log information; and generating a directed acyclic graph according to the analyzed traffic parameter information so as to determine traffic topological structures corresponding to the multiple user requests.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for generating a traffic topology, a storage medium, and an electronic device.
Background
In the design of modern computer software systems, high availability is becoming a need to be met that industry must follow. In order to achieve high availability, a plurality of copies of a storage resource and business logic are usually deployed in a distributed manner, and business services are provided in a distributed cluster manner, and the failure of any one node in the cluster does not affect the system to provide the business services.
In the related art, a distributed architecture generally adopts disaster tolerance architectures such as dual activities in the same city, multiple activities in different places and the like. In this case, the traffic path for user traffic into the enterprise data center becomes complex. If a traffic path fails, troubleshooting difficulties can result. Therefore, an efficient traffic topology generation method for monitoring the user traffic path is needed.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
In a first aspect, the present disclosure provides a traffic topology generating method, where the method includes:
acquiring log information of a source station load balancing node, wherein the source station load balancing node is deployed in a data center where a source station is located, and the log information comprises flow parameter information of a plurality of user requests received by the source station;
analyzing the flow parameter information included in the log information;
and generating a directed acyclic graph according to the analyzed traffic parameter information so as to determine traffic topological structures corresponding to the multiple user requests.
In a second aspect, the present disclosure provides a traffic topology generating apparatus, the apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring log information of a source station load balancing node, the source station load balancing node is deployed in a data center where a source station is located, and the log information comprises flow parameter information of a plurality of user requests received by the source station;
the analysis module is used for analyzing the flow parameter information included in the log information;
and the generating module is used for generating a directed acyclic graph according to the analyzed traffic parameter information so as to determine traffic topological structures corresponding to the multiple user requests.
In a third aspect, the present disclosure provides a computer readable medium having stored thereon a computer program which, when executed by a processing apparatus, performs the steps of the method of the first aspect.
In a fourth aspect, the present disclosure provides an electronic device comprising:
a storage device having a computer program stored thereon;
processing means for executing the computer program in the storage means to carry out the steps of the method of the first aspect.
Through the technical scheme, the source station load balancing node can record the flow parameter information of a plurality of user requests received by the source station in a log mode. Therefore, the log information of the load balancing node of the source station is acquired, the traffic parameter information requested by each user can be acquired, and a directed acyclic graph can be generated according to the analysis of the traffic parameter information, so that traffic topological structures corresponding to a plurality of user requests are determined, and a new traffic topological generation mode is provided. In addition, the traffic parameter information for topology generation can be acquired through the source station load balancing node, multi-node data collection is not needed, the problem of data alignment caused by multi-node data collection can be avoided, and therefore the generation efficiency of the traffic topology is improved.
Additional features and advantages of the present disclosure will be set forth in the detailed description which follows.
Drawings
The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale. In the drawings:
fig. 1 is a schematic diagram illustrating an implementation scenario of a traffic topology generation method according to an exemplary embodiment of the present disclosure;
FIG. 2 is a flowchart illustrating a traffic topology generation method according to an exemplary embodiment of the present disclosure;
fig. 3 is a flowchart illustrating a traffic topology generation method according to another exemplary embodiment of the present disclosure;
FIG. 4 is a block diagram illustrating a traffic topology generation apparatus according to an exemplary embodiment of the present disclosure;
fig. 5 is a block diagram illustrating an electronic device according to an exemplary embodiment of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be understood that the various steps recited in method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units. It is further noted that references to "a", "an", and "the" modifications in the present disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
As background art, a distributed architecture in related art usually adopts disaster-tolerant architectures such as dual-active in the same city and multiple active in different places. In this case, the traffic path for user traffic into the enterprise data center becomes complex. If a traffic path fails, troubleshooting difficulties can result. Therefore, an efficient traffic topology generation method for monitoring user traffic paths is needed.
The inventor researches and discovers that a traffic topology monitoring system in the related art generally only collects and monitors link topology and state data of a network layer, and lacks data processing and analyzing capabilities of service layers such as domain names and Content Delivery Nodes (CDN). And the related art traffic topology monitoring system needs to collect data from various network nodes, and has the problem that the data is difficult to align. In view of this, the present application provides a new traffic topology generation method, so as to generate a directed acyclic graph through log information of a source station load balancing node to restore topology information of an entire traffic link.
An implementation scenario of the present disclosure is first explained. For example, an implementation scenario of the present disclosure may be a network architecture as shown in fig. 1. Referring to fig. 1, zone 1 is the data center (IDC) where the source station is located, including data center IDC1, IDC2, and IDC 3. The source station is a server for storing resources, and each network node can acquire resources from the source station for responding to a network request sent by a user. Region 2 is an optional intermediate node data center, including data centers IDC4, IDC5, IDC6, and IDC 7. The area 3 is a Content Delivery Network (CDN) (content Delivery network) and includes content Delivery nodes CDN1, CDN2, CDN3 and CDN 4. Each region communicates with each other through Internet Service Providers (ISPs), i.e., operators providing internet access services to users, which, as shown in fig. 1, may include internet service providers ISP1 through ISP 7. Each data center of area 1 is deployed with L7 load balancing (seven-tier load balancing), referred to as source station load balancing. Before the L7 load balancing of the area 1, the deployment of L4 load balancing (four-layer load balancing) or L7 load balancing, called access point load balancing, can be selected. As shown in fig. 1, the access point load balancing may be deployed in area 1 or area 2. Under the network architecture shown in fig. 1, a user request sent by a user to a source station may have four possible traffic access routes shown in fig. 1 (i) to (iv). By the traffic topology generation method provided by the disclosure, the directed acyclic graph can be generated through the log information of the source station load balancing node to restore the topology information of the whole traffic link, and the whole traffic topology from the user is obtained.
Fig. 2 is a flow topology generation method according to an exemplary embodiment of the present disclosure. The traffic topology generation method may include the steps of:
And 203, generating a directed acyclic graph according to the analyzed traffic parameter information to determine traffic topological structures corresponding to the multiple user requests.
By way of example, log information of the source station load balancing node can be acquired and stored in real time, so that a user traffic topological structure is generated in real time, and the user traffic condition can be monitored in real time conveniently. In a possible way, in order to save storage and calculation resources, a part of the log can be stored in a sampling way, and the used sampling rate value is added to the log content at the same time. That is to say, in the embodiment of the present disclosure, the log information of the source station load balancing node may also be obtained according to a preset sampling period, and the preset sampling period is added to the log information. The preset sampling period may be set according to an actual situation, which is not limited in the embodiments of the present disclosure.
It should be understood that the source station load balancing node may record the traffic parameter information of each user request received by the source station in the form of a log, that is, the log information of the source station load balancing node may include basic information of each user request. Therefore, by analyzing the traffic parameter information requested by the user, the traffic starting point, the traffic ending point and the specific traffic data requested by the user can be determined, so that the traffic topology corresponding to the user request can be restored.
In a possible manner, the traffic parameter information may include at least one type of parameter information: the method comprises the steps of domain name, request path, request parameter, request header information, data center information corresponding to a source station load balancing node and user IP information.
The domain name is the name of a computer or a group of computers on the network, which is composed of a string of names separated by points, and is used for positioning and identifying the computer during data transmission. The request path is used to access a specified resource of the source station. The request parameter is used to determine the data processing method of the source station for the specified resource. The request header information may be used to store cookie information. And the data center information corresponding to the source station load balancing node is used for representing information such as the position and the identification of the data center where the source station is located. The user IP information is used for representing the logic address corresponding to each network or each host on the Internet, and different hosts or networks correspond to different IP information.
In a possible manner, the traffic topology generation method provided by the present disclosure may be applied to a network architecture including a content delivery network CDN node, a source station load balancing node, and an access point load balancing node, where the CDN node may be configured to carry CDN information in a user request and send the CDN information to a next network node, and the access point load balancing node may be configured to carry public network IP information of the access point in the user request and send the user request to the next network node. Correspondingly, the traffic parameter information may further include CDN information and public network IP information corresponding to the access point load balancing node.
A traffic monitoring system in the related art usually collects and monitors only link topology and state data of a network layer, and lacks data processing and analyzing capabilities of service layers such as a domain name and a CDN. In the embodiment of the present disclosure, a CDN node in a network architecture may carry CDN information in a user request and send the CDN information to a next network node, and an access point load balancing node may carry public network IP information of itself in the user request and send the user request to the next network node, so that the source station load balancing node may record data of service levels such as a domain name, the CDN, and public network IP information in a log form, so that a finally restored traffic topology better conforms to an actual traffic path situation.
For example, the CDN information may be used to represent a location, an identifier, and the like of a CDN node through which the user request passes, for example, the CND information may include vendor information of the CDN node, that is, the CDN node may carry the vendor information of itself in the user request and forward the vendor information to a next network node.
In the related technology, CDN content delivery only needs to push specified content in a CDN node streaming media resource library to a lower node according to a content delivery policy defined by a service operator, and CDN information such as CDN manufacturer information of a CDN node does not need to be used, so that the CDN information such as the CDN manufacturer information is not usually carried in a network request and sent to a next network node. In the embodiment of the present disclosure, in consideration of the situation that the user traffic is large, different CDN nodes need to be used, so in order to accurately restore the user traffic path, the CDN nodes may carry CDN information in the network request and send the CDN information to the next network node. For example, referring to fig. 1, if the CDN information includes an identifier CDN1, it may be determined that the user request was sent to the origin site through CDN1 node.
In a possible manner, the CDN information may be carried in a domain name requested by the user, a request parameter, or request header information. Accordingly, by analyzing the domain name, the request parameter, or the request header information of the user request, the CDN information corresponding to the user request may be obtained.
Illustratively, the public network IP information is used to represent operator line information and geographical location information to which a user belongs when requesting to enter the source station data center, and in the embodiment of the present disclosure, the access point load balancing may carry its own public network IP information in the request and forward it to the next network node.
In the related art, the access point load balancing node usually performs load balancing on the received network request, and the public network IP information of the access point load balancing does not need to be known in the process, so that the public network IP information of the access point load balancing node is usually not carried in the user request and is sent to the next network node in the related art. In the embodiment of the present disclosure, considering that there are many access point load balancing nodes, in order to accurately restore a user traffic path, the access point load balancing node may carry public network IP information in a network request and send the network request to the next network node. For example, referring to fig. 1, if the operator is determined to be ISP1 by analyzing the public network IP information, it may be determined that the user request is transmitted to the source station through operator ISP 1.
Through the mode, the access point load balancing node can transmit public network IP information to a next-level source station load balancing node, the CDN node can carry a request header used for identifying the CDN information of the CDN node when a user request is forwarded, therefore, the source station load balancing node can record the CDN information corresponding to the user request and the public network IP information before accessing the source station in a log mode, so that a flow path corresponding to the user request can be more accurately restored, a flow topology more conforming to the actual situation is obtained, and further, a network node and a flow link with problems can be more conveniently positioned under the condition that the flow link breaks down.
In a possible manner, the traffic parameter information may further include a user-defined parameter carried in the request parameter or the request header information, and the user-defined parameter may include version information of an application program sending the user request or type information of an electronic device sending the user request.
That is to say, in the embodiment of the present disclosure, any service dimension that needs to perform traffic topology analysis, such as an Application program (App) version, a user machine type, and the like, may also be carried in the request header and the parameter. By the method, the corresponding traffic topology can be generated according to the actual service requirement, so that the service traffic analysis can be performed more conveniently.
In this way, the log information of the source station load balancing node may include at least one of the following traffic parameter information: the method comprises the steps of domain name, request path, request parameter, request header information, data center information corresponding to a source station load balancing node, user IP information, CDN information, public network IP information corresponding to an access point load balancing node, version information of an application program sending a user request, and type information of electronic equipment sending the user request. That is to say, the identification information corresponding to each network node through which the user request passes may be carried in the user request and sent to the source station, so that the traffic path corresponding to the user request may be restored by analyzing the traffic parameter information of the user request. The traffic parameter information may be analyzed by a Flink distributed processing engine, and the analyzing manner of the traffic parameter information is not limited in the embodiment of the present disclosure.
It should be understood that, by analyzing the public network IP information, the operator line information and the geographical location information to which the data center belongs when entering the data center can be obtained, and the operator dimension is added to the initial log information recorded by the source station load balancing center. The data center position corresponding to the source station can be obtained by analyzing the data center information corresponding to the source station load balancing node, and the dimension of the source station data center is added to the initial log information recorded by the source station load balancing center. The CDN information to which the user request belongs can be obtained by analyzing the domain name, the request parameter or the request header information, and CDN dimensionality is added to the initial log information recorded by the source station load balancing center. And the traffic starting point operator and the geographical position information corresponding to the user request can be obtained by analyzing the IP information of the user. Various required service dimensions such as application versions and other information can be obtained by analyzing the request header information and the request parameters, and service analysis dimensions are added to the initial log information recorded by the source station load balancing center.
After the traffic parameter information is analyzed, a directed acyclic graph can be generated according to the analyzed traffic parameter information to determine a traffic topology structure corresponding to a plurality of user requests. The directed acyclic graph can be generated in real time according to the analyzed traffic parameter information, so that traffic topological structures corresponding to the multiple user requests can be analyzed in real time. Alternatively, in order to save the computing resources, the analyzed traffic parameter information added with various pieces of dimension information may be saved, for example, the analyzed traffic parameter information added with various pieces of dimension information is saved by the clickwouse database management system, and the like. And then, under the condition of service failure, acquiring corresponding analyzed flow parameter information from the stored analyzed flow parameter information to generate a directed acyclic graph, so that the failure can be conveniently checked.
In a possible manner, generating a directed acyclic graph according to the analyzed traffic parameter information to determine a traffic topology structure corresponding to the plurality of user requests may be: and performing aggregation calculation on the analyzed flow parameter information according to target flow parameter information, wherein the target flow parameter information is at least one of the flow parameter information. And then generating a corresponding flow vector link for each aggregation calculation result. And finally, accumulating the traffic vector links with the same starting point and the same end point according to preset service indexes to obtain a directed acyclic graph so as to determine traffic topological structures corresponding to a plurality of user requests. The preset service index may be the number of user requests, the size of data volume (number of bytes) corresponding to the user requests, or the size of data volume (number of bytes) of returned response requests, and the like.
In actual service, the number of user requests received by the source station is large, so in order to monitor user traffic more efficiently and intuitively, the user requests received by the source station can be classified first, and then the user requests of the same class are aggregated into one class, that is, aggregation calculation can be performed according to target traffic parameter information. The target traffic parameter information may be any kind of parameter information in the traffic parameter information corresponding to the user request. For example, the target traffic parameter is data center information corresponding to the source station load balancing node, and then user requests with the same data center information corresponding to the source station load balancing node in the multiple user requests may be aggregated into one category.
A corresponding traffic vector link may then be generated for each aggregate computation. As previously noted, the aggregation calculation may classify the plurality of user requests received by the source station, and thus each of the aggregation calculation results may be understood as each of the user requests included in each of the classes of aggregation results.
In a possible manner, if the traffic topology generation method provided by the present disclosure is applied to a network architecture including a content delivery network CDN node, a source station load balancing node, and an access point load balancing node, for each aggregation calculation result, generating a corresponding traffic vector link may be: and determining whether the aggregation calculation result comprises CDN information or not to obtain a first judgment result, and determining whether data center information corresponding to the source station load balance in the aggregation calculation result is consistent with data center information corresponding to the access point load balance center to obtain a second judgment result. And then generating a corresponding flow vector link according to the first judgment result and the second judgment result.
For example, referring to the network architecture shown in fig. 1, a traffic topology method provided by the embodiment of the present disclosure may include the following steps:
And 305, generating a corresponding flow vector link according to the first judgment result and the second judgment result.
And step 306, accumulating the traffic vector links with the same starting point and the same end point according to a preset service index to obtain a directed acyclic graph so as to determine a traffic topological structure corresponding to a plurality of user requests.
Step 301 to step 303 are already described in detail above, and are not described herein again.
For example, in step 304, for each aggregation calculation result, that is, for each user request, the first determination result may include that the user request includes CDN information or that the user request does not include CDN information, and the second determination result may include that data center information corresponding to the source station load balancing node is consistent with data center information corresponding to the access point load balancing node or that the data center information corresponding to the source station load balancing node is inconsistent with the data center information corresponding to the access point load balancing node. In this case, four different traffic vector links can be obtained according to the first determination result and the second determination result.
For example, referring to the network architecture shown in fig. 1, if the aggregation calculation result includes CDN information and data center information corresponding to the source station load balancing node is not consistent with data center information corresponding to the access point load balancing node, it indicates that the user request passes through the CDN node, and the source station load balancing node is set in area 1 and the access point load balancing node is set in area 2. In this case, the user request sequentially passes through the CDN node, the operator node, and the access point load balancing node with the user terminal as a starting point, and finally reaches the source station load balancing node, so that a traffic vector link can be generated as follows: user-CDN node-operator-access point load balancing node-source station load balancing node.
If the aggregation calculation result includes CDN information and the data center information corresponding to the source station load balancing node is consistent with the data center information corresponding to the access point load balancing node, it indicates that the user request has passed through the CDN node, and the source station load balancing node and the access point load balancing node are both set in region 1. In this case, the user request sequentially passes through the CDN node and the operator node with the user terminal as a starting point, and finally reaches the source station load balancing node, so that a traffic vector link may be generated as follows: user-CDN node-operator-source station load balancing node.
If the aggregation calculation result does not include the CDN information and the data center information corresponding to the source station load balancing node is inconsistent with the data center information corresponding to the access point load balancing node, it indicates that the user request does not pass through the CDN node, and the source station load balancing node is set in the area 1 and the access point load balancing node is set in the area 2. In this case, the user request sequentially passes through the operator node and the access point load balancing node with the user terminal as a starting point, and finally reaches the source station load balancing node, so that a traffic vector link can be generated as follows: user-operator-access point load balancing node-source station load balancing node.
If the aggregation calculation result does not include CDN information and the data center information corresponding to the source station load balancing node is consistent with the data center information corresponding to the access point load balancing node, it indicates that the user request does not pass through the CDN node, and the source station load balancing node and the access point load balancing node are both set in region 1. In this case, the user request starts from the user terminal, passes through the operator node, and finally reaches the source station load balancing node, so that the traffic vector link may be generated as follows: user-operator-source station load balancing node.
By the method, the traffic vector links corresponding to each user request can be obtained, and then the traffic vector links with the same starting point and the same end point can be accumulated according to the preset service index to obtain the directed acyclic graph so as to determine the traffic topological structure corresponding to the plurality of user requests. The starting point of the traffic vector link corresponds to a user terminal which initiates a user request, and the end point of the traffic vector link corresponds to a source station load balancing node which finally responds to the user request and provides resources. For example, if the preset service index is the size of data volume (number of bytes) requested by a user, and the traffic vector link is a user-operator-source station load balancing node, the traffic vector links with the same data volume and the same user terminal (that is, the same starting point) and the same source station load balancing node (that is, the same destination) in the user request may be accumulated to obtain a directed acyclic graph, so as to determine a traffic topology corresponding to multiple user requests.
It should be understood that the directed acyclic graph refers to a loop-free directed graph, in which a node starts from the directed acyclic graph and cannot return to the node through a plurality of edges, which conforms to the characteristic that user traffic reaches a source station data center from a user terminal. In addition, the flow topology is generated through the embodiment of the disclosure, the flow proportion and specific numerical value of the public network access flow of the specific service among each source station data center, different operator lines and different CDNs can be determined, and fault diagnosis and flow scheduling are facilitated.
Based on the same inventive concept, the embodiment of the disclosure further provides a traffic topology generation device. The traffic topology generating device may be a part or all of an electronic device through software, hardware or a combination of both. Referring to fig. 4, the traffic topology generating apparatus 400 includes:
an obtaining module 401, configured to obtain log information of a source station load balancing node, where the source station load balancing node is deployed in a data center where a source station is located, and the log information includes traffic parameter information of multiple user requests received by the source station;
an analysis module 402, configured to analyze the traffic parameter information included in the log information;
a generating module 403, configured to generate a directed acyclic graph according to the analyzed traffic parameter information, so as to determine a traffic topology structure corresponding to the multiple user requests.
Optionally, the generating module 403 is configured to:
performing aggregation calculation on the analyzed flow parameter information according to target flow parameter information, wherein the target flow parameter information is at least one of the flow parameter information;
generating a corresponding flow vector link for each aggregation calculation result;
and accumulating the traffic vector links with the same starting point and the same end point according to a preset service index to obtain the directed acyclic graph so as to determine a traffic topological structure corresponding to the plurality of user requests.
Optionally, the apparatus 400 is applied to a network architecture including a content delivery network CDN node, the source station load balancing node, and an access point load balancing node, where the access point load balancing node is a network node before accessing the source station load balancing node, and the generating module 403 is configured to:
determining whether the aggregation calculation result comprises CDN information or not to obtain a first judgment result aiming at each aggregation calculation result, and determining whether data center information corresponding to the source station load balance in the aggregation calculation result is consistent with data center information corresponding to the access point load balance center or not to obtain a second judgment result;
and generating a corresponding flow vector link according to the first judgment result and the second judgment result.
Optionally, the traffic parameter information includes at least one of the following types of parameter information: the system comprises a domain name, a request path, request parameters, request header information, data center information corresponding to the source station load balancing node and user IP information.
Optionally, the apparatus 400 is applied to a network architecture including a content delivery network CDN node, the source station load balancing node, and an access point load balancing node, where the CDN node is configured to carry CDN information in a user request and send the CDN information to a next network node, and the access point load balancing node is configured to carry public network IP information of the access point in the user request and send the user request to the next network node;
the traffic parameter information further includes the CDN information and public network IP information corresponding to the access point load balancing node.
Optionally, the traffic parameter information further includes a user-defined parameter carried in the request parameter or the request header information, where the user-defined parameter includes version information of an application program that sends the user request or type information of an electronic device that sends the user request.
Optionally, the obtaining module 401 is configured to:
and acquiring log information of the source station load balancing node according to a preset sampling period, and adding the preset sampling period to the log information.
With regard to the apparatus in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be described in detail here.
Based on the same inventive concept, the disclosed embodiments further provide a computer readable medium, on which a computer program is stored, and the computer program, when executed by a processing device, implements the steps of any of the traffic topology generation methods described above.
Based on the same inventive concept, an embodiment of the present disclosure further provides an electronic device, including:
a storage device having a computer program stored thereon;
processing means for executing the computer program in the storage means to implement the steps of any of the traffic topology generation methods described above.
Referring now to FIG. 5, shown is a schematic diagram of an electronic device 500 suitable for use in implementing embodiments of the present disclosure. The terminal device in the embodiments of the present disclosure may include, but is not limited to, a mobile terminal such as a mobile phone, a notebook computer, a digital broadcast receiver, a PDA (personal digital assistant), a PAD (tablet computer), a PMP (portable multimedia player), a vehicle terminal (e.g., a car navigation terminal), and the like, and a stationary terminal such as a digital TV, a desktop computer, and the like. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 5, electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may be alternatively implemented or provided.
In particular, the processes described above with reference to the flow diagrams may be implemented as computer software programs, according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a non-transitory computer readable medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program performs the above-described functions defined in the methods of the embodiments of the present disclosure when executed by the processing device 501.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the communication may be performed using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring log information of a source station load balancing node, wherein the source station load balancing node is deployed in a data center where a source station is located, and the log information comprises flow parameter information of a plurality of user requests received by the source station; analyzing the flow parameter information included in the log information; and generating a directed acyclic graph according to the analyzed traffic parameter information so as to determine traffic topological structures corresponding to the multiple user requests.
Computer program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including but not limited to an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present disclosure may be implemented by software or hardware. Wherein the name of a module in some cases does not constitute a limitation on the module itself.
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
In accordance with one or more embodiments of the present disclosure, an example provides a traffic topology generation method, the method including:
acquiring log information of a source station load balancing node, wherein the source station load balancing node is deployed in a data center where a source station is located, and the log information comprises flow parameter information of a plurality of user requests received by the source station;
analyzing the flow parameter information included in the log information;
and generating a directed acyclic graph according to the analyzed traffic parameter information so as to determine traffic topological structures corresponding to the multiple user requests.
According to one or more embodiments of the present disclosure, example two provides the method of example one, wherein the generating a directed acyclic graph according to the analyzed traffic parameter information to determine a traffic topology corresponding to the multiple user requests includes:
performing aggregation calculation on the analyzed flow parameter information according to target flow parameter information, wherein the target flow parameter information is at least one of the flow parameter information;
generating a corresponding flow vector link aiming at each aggregation calculation result;
and accumulating the traffic vector links with the same starting point and the same end point according to preset service indexes to obtain the directed acyclic graph so as to determine traffic topological structures corresponding to the user requests.
According to one or more embodiments of the present disclosure, example three provides the method of example two, where the method is applied to a network architecture including a content delivery network CDN node, the source station load balancing node, and an access point load balancing node, where the access point load balancing node is a network node before accessing the source station load balancing node, and the generating a corresponding traffic vector link for each aggregated calculation result includes:
determining whether the aggregation calculation result comprises CDN information or not to obtain a first judgment result aiming at each aggregation calculation result, and determining whether data center information corresponding to the source station load balance in the aggregation calculation result is consistent with data center information corresponding to the access point load balance center or not to obtain a second judgment result;
and generating a corresponding flow vector link according to the first judgment result and the second judgment result.
Example four provides the method of any of examples one to three, wherein the traffic parameter information includes at least one of the following types of parameter information: the system comprises a domain name, a request path, request parameters, request header information, data center information corresponding to the source station load balancing node and user IP information.
According to one or more embodiments of the present disclosure, example five provides the method of example four, where the method is applied to a network architecture including a content delivery network CDN node, the source station load balancing node, and an access point load balancing node, where the CDN node is configured to carry CDN information in a user request and send the CDN information to a next network node, and the access point load balancing node is configured to carry public network IP information of the access point itself in the user request and send the user request to the next network node;
the traffic parameter information further includes the CDN information and public network IP information corresponding to the access point load balancing node.
In accordance with one or more embodiments of the present disclosure, example six provides the method of example four, wherein the traffic parameter information further includes a user-defined parameter carried in the request parameter or the request header information, and the user-defined parameter includes version information of an application program sending the user request or type information of an electronic device sending the user request.
Example seven provides the method of any one of examples one to three, wherein the obtaining log information of the source station load balancing node includes:
and acquiring log information of the source station load balancing node according to a preset sampling period, and adding the preset sampling period to the log information.
In accordance with one or more embodiments of the present disclosure, example eight provides an apparatus for traffic topology generation, the apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring log information of a source station load balancing node, the source station load balancing node is deployed in a data center where a source station is located, and the log information comprises flow parameter information of a plurality of user requests received by the source station;
the analysis module is used for analyzing the flow parameter information included in the log information;
and the generating module is used for generating a directed acyclic graph according to the analyzed traffic parameter information so as to determine traffic topological structures corresponding to the multiple user requests.
Example nine provides the apparatus of example eight, wherein the generation module is to:
performing aggregation calculation on the analyzed flow parameter information according to target flow parameter information, wherein the target flow parameter information is at least one of the flow parameter information;
generating a corresponding flow vector link for each aggregation calculation result;
and accumulating the traffic vector links with the same starting point and the same end point according to a preset service index to obtain the directed acyclic graph so as to determine a traffic topological structure corresponding to the plurality of user requests.
In accordance with one or more embodiments of the present disclosure, example ten provides the apparatus of example nine, where the apparatus is applied to a network architecture including a content delivery network CDN node, the source station load balancing node, and an access point load balancing node, where the access point load balancing node is a network node before accessing the source station load balancing node, and the generating module is configured to:
determining whether the aggregation calculation result comprises CDN information or not to obtain a first judgment result aiming at each aggregation calculation result, and determining whether data center information corresponding to the source station load balance in the aggregation calculation result is consistent with data center information corresponding to the access point load balance center or not to obtain a second judgment result;
and generating a corresponding flow vector link according to the first judgment result and the second judgment result.
In accordance with one or more embodiments of the present disclosure, example eleven provides the apparatus of any one of example eight to example ten, wherein the traffic parameter information includes at least one type of parameter information of: the system comprises a domain name, a request path, request parameters, request header information, data center information corresponding to the source station load balancing node and user IP information.
According to one or more embodiments of the present disclosure, an example twelfth provides the apparatus of the example eleventh, where the apparatus is applied to a network architecture that includes a content delivery network CDN node, the source station load balancing node, and an access point load balancing node, the CDN node is configured to carry CDN information in a user request and send the CDN information to a next network node, and the access point load balancing node is configured to carry own public network IP information in a user request and send the user request to the next network node;
the traffic parameter information further includes the CDN information and public network IP information corresponding to the access point load balancing node.
In accordance with one or more embodiments of the present disclosure, example thirteen provides the apparatus of example eleven, wherein the traffic parameter information further includes a user-defined parameter carried in the request parameter or the request header information, and the user-defined parameter includes version information of an application program that sent the user request or type information of an electronic device that sent the user request.
In accordance with one or more embodiments of the present disclosure, example fourteen provides the apparatus of any one of examples eight to ten, wherein the obtaining means is to:
and acquiring log information of the source station load balancing node according to a preset sampling period, and adding the preset sampling period to the log information.
Example fifteen provides, in accordance with one or more embodiments of the present disclosure, a computer-readable medium having stored thereon a computer program that, when executed by a processing device, implements the steps of the method of any of examples one to seven.
Example sixteen provides an electronic device, in accordance with one or more embodiments of the present disclosure, comprising:
a storage device having a computer program stored thereon;
processing means for executing the computer program in the storage means to implement the steps of the method of any of examples one to seven.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the disclosure herein is not limited to the particular combination of features described above, but also encompasses other combinations of features described above or equivalents thereof without departing from the spirit of the disclosure. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Further, while operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limitations on the scope of the disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims. With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
Claims (10)
1. A traffic topology generation method, characterized in that the method comprises:
acquiring log information of a source station load balancing node, wherein the source station load balancing node is deployed in a data center where a source station is located, and the log information comprises flow parameter information of a plurality of user requests received by the source station;
analyzing the flow parameter information included in the log information;
and generating a directed acyclic graph according to the analyzed traffic parameter information so as to determine a traffic topological structure corresponding to the plurality of user requests.
2. The method according to claim 1, wherein the generating a directed acyclic graph according to the parsed traffic parameter information to determine a traffic topology corresponding to the plurality of user requests comprises:
performing aggregation calculation on the analyzed flow parameter information according to target flow parameter information, wherein the target flow parameter information is at least one of the flow parameter information;
generating a corresponding flow vector link for each aggregation calculation result;
and accumulating the traffic vector links with the same starting point and the same end point according to preset service indexes to obtain the directed acyclic graph so as to determine traffic topological structures corresponding to the user requests.
3. The method according to claim 2, wherein the method is applied to a network architecture including a Content Delivery Network (CDN) node, the source station load balancing node, and an access point load balancing node, where the access point load balancing node is a network node before accessing the source station load balancing node, and the generating a corresponding traffic vector link for each aggregated calculation result includes:
determining whether the aggregation calculation result comprises CDN information or not to obtain a first judgment result aiming at each aggregation calculation result, and determining whether data center information corresponding to the source station load balance in the aggregation calculation result is consistent with data center information corresponding to the access point load balance center or not to obtain a second judgment result;
and generating a corresponding flow vector link according to the first judgment result and the second judgment result.
4. A method according to any of claims 1-3, characterized in that said traffic parameter information comprises at least one type of parameter information of: the system comprises a domain name, a request path, request parameters, request header information, data center information corresponding to the source station load balancing node and user IP information.
5. The method according to claim 4, wherein the method is applied to a network architecture including a Content Delivery Network (CDN) node, the source station load balancing node and an access point load balancing node, the CDN node is used for carrying CDN information in a user request and sending the CDN information to a next network node, and the access point load balancing node is used for carrying public network IP information of the access point load balancing node in the user request and sending the user request to the next network node;
the traffic parameter information further includes the CDN information and public network IP information corresponding to the access point load balancing node.
6. The method of claim 4, wherein the traffic parameter information further comprises a user-defined parameter carried in the request parameter or request header information, and wherein the user-defined parameter comprises version information of an application program sending the user request or type information of an electronic device sending the user request.
7. The method according to any one of claims 1 to 3, wherein the obtaining the log information of the source station load balancing node comprises:
and acquiring log information of the source station load balancing node according to a preset sampling period, and adding the preset sampling period to the log information.
8. An apparatus for traffic topology generation, the apparatus comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring log information of a source station load balancing node, the source station load balancing node is deployed in a data center where a source station is located, and the log information comprises flow parameter information of a plurality of user requests received by the source station;
the analysis module is used for analyzing the flow parameter information included in the log information;
and the generating module is used for generating a directed acyclic graph according to the analyzed traffic parameter information so as to determine traffic topological structures corresponding to the multiple user requests.
9. A computer-readable medium, on which a computer program is stored, characterized in that the program, when being executed by processing means, carries out the steps of the method of any one of claims 1 to 7.
10. An electronic device, comprising:
a storage device having a computer program stored thereon;
processing means for executing the computer program in the storage means to carry out the steps of the method according to any one of claims 1 to 7.
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