CN114422442B - Multidimensional dynamic grouping current limiting method, device, equipment and storage medium - Google Patents
Multidimensional dynamic grouping current limiting method, device, equipment and storage medium Download PDFInfo
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Abstract
The present specification relates to a flow control technology applicable to a distributed system in a financial field or other fields, and provides a multidimensional dynamic packet flow limiting method, a device, equipment and a storage medium, wherein the method comprises: confirming whether the service request amount at the current transaction moment is abnormal or not; when the service request amount at the current transaction moment is abnormal, acquiring the current entropy uncertainty proportion of the application; and carrying out service-level current limiting, service group-level current limiting or application-level current limiting according to the entropy uncertainty proportion and the service request quantity. The embodiment of the specification can improve the operation stability of the application system.
Description
Technical Field
The present disclosure relates to flow control technologies applicable to distributed systems in financial or other fields, and in particular, to a multidimensional dynamic packet flow limiting method, apparatus, device, and storage medium.
Background
The service gateway is used as the only entrance of external access of the distributed network, plays an important role in the distributed overall architecture, is used for providing service calling capability in the form of HTTP for applications and Automatic Private IP (APIP) which are not integrated with the distributed service framework, realizing the RESTful (Representational State Transfer) format external automatic exposure of the HTTP protocol, shielding internal remote procedure call (Remote Procedure Call, RPC) and supporting service access among the applications. However, as the service request amount borne by the gateway is continuously increased, the systematic protection capability of the node is always a weak link, and the single current limitation cannot meet the requirement of high concurrent service scenes, so that the stable operation of an application system is easily affected.
Disclosure of Invention
An object of an embodiment of the present disclosure is to provide a method, an apparatus, a device, and a storage medium for multi-dimensional dynamic packet current limiting, so as to improve the operation stability of an application system.
To achieve the above object, in one aspect, an embodiment of the present disclosure provides a multi-dimensional dynamic packet current limiting method, including:
confirming whether the service request amount at the current transaction moment is abnormal or not;
when the service request amount at the current transaction moment is abnormal, acquiring the current entropy uncertainty proportion of the application;
and carrying out service-level current limiting, service group-level current limiting or application-level current limiting according to the entropy uncertainty proportion and the service request quantity.
In the multidimensional dynamic packet throttling method of the embodiment of the present disclosure, the confirming whether the service request amount at the current transaction time is abnormal includes:
for each service single service request quantity at the current transaction moment, judging whether the single service request quantity is positioned in a corresponding preset first confidence interval [ m ] i -3δ i ,m i +3δ i ]An inner part; wherein m is i For the i-th service, the request amount average value delta in a specified history period i The variance of the request amount in a specified history period for the ith service;
and when the single service request quantity is not positioned in the corresponding preset first confidence interval, confirming that the single service request quantity is abnormal.
In the multidimensional dynamic packet throttling method of the embodiment of the present disclosure, the confirming whether the service request amount at the current transaction time is abnormal includes:
for the group request quantity of each service group at the current transaction time, judging whether the group request quantity is positioned in a corresponding preset second confidence interval [ m ] j -3δ j ,m j +3δ j ]An inner part; wherein m is j Average, delta, of requests for j-th service group in specified history period j The variance of the request quantity in a specified history period for the j-th service group;
and when the group request quantity is not in the second confidence interval corresponding to the preset, confirming that the group request quantity is abnormal.
In the multidimensional dynamic packet throttling method of the embodiment of the present disclosure, the confirming whether the service request amount at the current transaction time is abnormal includes:
judging whether the application request quantity is positioned in a preset third confidence interval [ m-3 delta, m+3 delta ] or not according to the application request quantity at the current transaction moment; wherein m is the average value of the request amount applied in the appointed historical period, and delta is the variance of the request amount applied in the appointed historical period;
and when the application request quantity is not located in the third confidence interval, confirming that the application request quantity is abnormal.
In the multidimensional dynamic packet current limiting method of the embodiment of the present disclosure, the obtaining the current entropy uncertainty proportion of the application includes:
according to the formulaDetermining the current entropy uncertainty proportion of the application;
where t is the current entropy uncertainty proportion of the application, n is the number of services in the application, p' (x) is the distribution of congestion in x groups, x is the number of service groups under the application, y is the number of abnormal services in the application, p (y|x) is the probability of occurrence of abnormality in y services in case of abnormality in x groups, and p i The gateway congestion event probability of the maximum entropy is satisfied for the ith service.
In the multidimensional dynamic packet throttling method of the embodiment of the present disclosure, the performing service-level throttling, service group-level throttling or application-level throttling according to the entropy uncertainty ratio and the service request amount includes:
and triggering the single-service request quantity of the abnormality to carry out service-level flow limiting when the entropy uncertainty proportion is smaller than a first threshold value and the group request quantity of the service group to which the abnormality belongs does not reach the group request quantity threshold value.
In the multidimensional dynamic packet throttling method of the embodiment of the present disclosure, the performing service-level throttling, service group-level throttling or application-level throttling according to the entropy uncertainty ratio and the service request amount includes:
and triggering to carry out service group level current limiting on the service group when the entropy uncertainty proportion is larger than a first threshold and smaller than or equal to a second threshold and the group request quantity of the service group to which the abnormality belongs reaches a group request quantity threshold.
In the multidimensional dynamic packet throttling method of the embodiment of the present disclosure, the performing service-level throttling, service group-level throttling or application-level throttling according to the entropy uncertainty ratio and the service request amount includes:
triggering application-level throttling of the application when the entropy uncertainty ratio is greater than a second threshold and the application request amount of the application reaches an application request amount threshold.
In the multidimensional dynamic grouping current limiting method of the embodiment of the present disclosure, the value range of the first threshold is 5% -15%.
In the multidimensional dynamic grouping current limiting method of the embodiment of the present disclosure, the value range of the second threshold is 45% -55%.
In another aspect, embodiments of the present disclosure further provide a multidimensional dynamic packet current limiting device, including:
the abnormality judging module is used for confirming whether the service request quantity at the current transaction moment is abnormal or not;
the proportion determining module is used for acquiring the current entropy uncertainty proportion of the application when the service request quantity at the current transaction moment is abnormal;
and the multidimensional flow limiting module is used for carrying out service-level flow limiting or service group-level flow limiting or application-level flow limiting according to the entropy uncertainty proportion and the service request quantity.
In another aspect, embodiments of the present disclosure further provide a computer device including a memory, a processor, and a computer program stored on the memory, which when executed by the processor, performs the instructions of the above method.
In another aspect, embodiments of the present disclosure also provide a computer storage medium having stored thereon a computer program which, when executed by a processor of a computer device, performs instructions of the above method.
As can be seen from the technical solutions provided in the embodiments of the present disclosure, when the service request amount at the current transaction time is abnormal, service-level current limiting, service group-level current limiting, or application-level current limiting may be performed according to the entropy uncertainty ratio and the service request amount. Because the entropy uncertainty proportion can be used for representing the congestion probability of the judged object, when multidimensional multi-flow limiting is carried out according to the entropy uncertainty proportion and the service request quantity, the method not only can support high-concurrency service transaction, but also can reduce or avoid service gateway congestion, thereby improving the running stability of an application system and reducing the operation and maintenance pressure of operation and maintenance personnel.
Drawings
In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some of the embodiments described in the present description, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
FIG. 1 illustrates a schematic diagram of an application system in some embodiments of the present description;
FIG. 2 illustrates a group partitioning schematic applied in some embodiments of the present description;
FIG. 3 illustrates a flow chart of a multi-dimensional dynamic packet throttling method in some embodiments of the present description;
FIG. 4 is a flow chart illustrating a multi-dimensional dynamic packet throttling method in further embodiments of the present disclosure;
FIG. 5 illustrates a block diagram of an apparatus in some embodiments of the present description;
fig. 6 illustrates a block diagram of a computer device in some embodiments of the present description.
[ reference numerals description ]
10. A client;
20. a service gateway;
30. a server;
51. an abnormality judgment module;
52. a proportion determining module;
53. a multidimensional current limiting module;
602. a computer device;
604. a processor;
606. a memory;
608. a driving mechanism;
610. an input/output interface;
612. an input device;
614. an output device;
616. a presentation device;
618. a graphical user interface;
620. a network interface;
622. a communication link;
624. a communication bus.
Detailed Description
In order to make the technical solutions in the present specification better understood by those skilled in the art, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are intended to be within the scope of the present disclosure.
The embodiment of the specification relates to a flow control technology at a service gateway side, and can be applied to business scenes such as finance, electronic commerce and the like. The service gateway serves as a node for forwarding transactions and accommodates various service interfaces exposed by the application system. When a certain service abnormality or transaction amount is suddenly increased under an application system, the current limitation of the service gateway can be limited to a service dimension, but under one application, a plurality of service groups can exist, and each service group has a plurality of services. Therefore, in order to prevent or reduce service gateway congestion, there is a need for improved traffic control at the service gateway side.
Referring to fig. 1, an embodiment of the present specification provides an application system that may include a client 10, a service gateway 20, and a server 30. The client 10 may initiate a service request and forward to the server 30 for processing via the service gateway 20, and the service gateway 20 may be configured to: judging whether the service request amount at the current transaction moment is abnormal or not; when the service request amount at the current transaction moment is abnormal, acquiring the current entropy uncertainty proportion of the server 30; and carrying out service-level current limiting, service group-level current limiting or application-level current limiting according to the entropy uncertainty proportion and the service request quantity. In the embodiment of the specification, the entropy uncertainty proportion can be used for representing the probability of layering transaction congestion of the judged object, namely the entropy uncertainty proportion can be also called layering transaction congestion rate, so that when multidimensional multi-current limiting is carried out according to the entropy uncertainty proportion and the service request quantity, high concurrent service transaction can be supported, service gateway congestion can be relieved or avoided, the running stability of an application system is improved, and the operation and maintenance pressure of operation and maintenance personnel is reduced.
In some embodiments, the client 10 may be a self-service terminal device, a mobile terminal (i.e., a smart phone), a display, a desktop computer, a tablet computer, a notebook computer, a digital assistant, a smart wearable device, or the like. Wherein, intelligent wearable equipment can include intelligent bracelet, intelligent wrist-watch, intelligent glasses or intelligent helmet etc.. Of course, the client 10 is not limited to the electronic device with a certain entity, and may be software running in the electronic device. The service gateway 20 is a gateway device having routing forwarding and filtering functions. The filter function may include, for example, current limiting, rights checking, monitoring, and the like. The server 30 may be an electronic device with computing and network interaction functions; software running in the electronic device that provides business logic for data processing and network interactions may also be used. Based on the forwarding process of the service gateway 20, the server 30 may interact with the client 10.
Referring to fig. 2, a service may refer to a sub-divided service (e.g., services 11 to mn shown in fig. 2) formed according to a service split (e.g., a longitudinal split according to a service domain and then a transverse split according to a common shared dimension). Correspondingly, a service group may refer to a group of multiple services (e.g., service group 1-service group m shown in fig. 2). An application may provide multiple service classes (or service functions), each service class being a service group (e.g., m service groups shown in fig. 2 may form m service classes).
For example, in an exemplary embodiment, taking xx online banking (an application) as an example, it is assumed that the application has six service categories of registration service, deposit service, loan service, financial service, and life payment service, where each service category can be servitively split into multiple services. For example, taking a deposit business as an example, it may be divided into a demand deposit service, a three-month regular deposit service, a six-month regular deposit service, a one-year deposit service, a three-year deposit service, a five-year deposit service, and the like. Thus, six service categories may correspond to six service groups (i.e., a registration service group, a loan service group, a transfer service group, a financial service group, and a life payment service group).
The embodiment of the present disclosure further provides a multi-dimensional dynamic packet current limiting method, which may be applied to the service gateway side, as shown in fig. 3, and in some embodiments, the multi-dimensional dynamic packet current limiting method may include the following steps:
s301, confirming whether the service request quantity at the current transaction moment is abnormal.
In conjunction with fig. 4, the service gateway may count the service request amount in real time (i.e., count the service request amount at the current transaction time in real time) when performing route forwarding of the service request (e.g., the http request in fig. 4). Wherein, the service request volume can comprise the service request volume under each statistical dimension; for example, a service request amount of each service at the current transaction time (hereinafter referred to as a single service request amount), a service request amount of each service group at the current transaction time (hereinafter referred to as a group request amount), and a service request amount of the entire application at the current transaction time (hereinafter referred to as an application request amount).
In order to realize multidimensional flow control, whether the service request amount in each dimension is abnormal or not needs to be judged; therefore, when judging whether or not the traffic request amount in each dimension is abnormal in a preset threshold range manner, the threshold range in each dimension may be set in advance.
For example, taking a threshold range of the service request amount of a single service as an example, considering that the continuous random variable obeys normal distribution of parameters as mean and variance, a confidence interval [ m ] can be preset for the threshold range under each service i -3δ i ,m i +3δ i ]The degree of deviation of each operating state variable from the operating expectation is quantitatively described with relative accuracy. Wherein m is i For the i-th service, the request amount average value delta in a specified history period i The variance of the request amount over a specified history period for the ith service. The specified history period may be set according to actual needs, for example, taking the current transaction time as T day as an example, and the specified history period may be selected as the previous week (T-7 days).
Accordingly, the determining whether the service request amount at the current transaction time is abnormal may be: for each service single service request quantity at the current transaction moment, judging whether the single service request quantity is positioned in a corresponding preset first confidence interval [ m ] i -3δ i ,m i +3δ i ]And (3) inner part. When the single service request amount of the ith service at the current transaction time is greater than m i +3δ i The single service request quantity of the ith service at the current transaction moment is shown to be beyond the processing capacity (or throughput) of the ith service, so that the single service request quantity of the ith service at the current transaction moment can be judged to be in an abnormal scene, and the current limiting control can be triggered; otherwise, it may be determined that the single service request amount of the ith service at the current transaction time is in a normal scenario, so that normal service data forwarding (e.g., service request may be forwarded downstream) may be performed without triggering the flow restriction control.
Those skilled in the art will appreciate that the threshold ranges for other statistical dimensions may also be set based on similar confidence intervals, although in this case the meaning of the corresponding symbol parameters will be different.
Similarly, for the group request quantity of each service group at the current transaction time, judging whether the group request quantity is positioned in a corresponding preset second confidence interval [ m ] j -3δ j ,m j +3δ j ]An inner part; wherein m is j Average, delta, of requests for j-th service group in specified history period j The variance of the request quantity in a specified history period for the j-th service group; when the group request amount is greater than m j +3δ j When the group request quantity of the j-th service group is beyond the processing capacity (or throughput) of the j-th service group, the abnormality of the group request quantity can be judged, and the current limit control can be triggered; otherwise, normal traffic data forwarding may be performed without triggering the flow limit control.
Similarly, for the application request quantity at the current transaction moment, judging whether the application request quantity is positioned in a preset third confidence interval [ m-3 delta, m+3 delta ]; wherein m is the average value of the request amount applied in the appointed historical period, and delta is the variance of the request amount applied in the appointed historical period; when the application request amount is greater than m+3δ, it is indicated that the application request amount of the entire application has exceeded the processing capacity (or throughput) of the entire application, and therefore it can be determined that the application request amount is abnormal, so that the current limit control can be triggered; otherwise, normal traffic data forwarding may be performed without triggering the flow limit control.
S302, when the service request quantity at the current transaction moment is abnormal, acquiring the current entropy uncertainty proportion of the application.
The current entropy uncertainty ratio of an application refers to the ratio of the current entropy value of the application to the maximum entropy value of the application. The current entropy value applied refers to the entropy value applied at the current transaction moment. The entropy value of the application characterizes the probability of the uncertainty of the application (in the embodiment of the specification, the uncertainty is positively correlated with the hierarchical transaction congestion rate, the greater the probability of the uncertainty of the application is, the greater the probability of the hierarchical transaction congestion occurs, and when the entropy value of the application reaches the maximum entropy, the probability of the application being in the uncertainty is the maximum, namely the application is regarded as the hierarchical transaction congestion. Thus, the greater the proportion of entropy uncertainty at the current transaction time, the greater the likelihood of congestion at the current transaction time.
In some embodiments, obtaining the current entropy uncertainty proportion of the application may include:
according to the formulaDetermining the current entropy uncertainty proportion of the application;
where t is the current entropy uncertainty proportion of the application, n is the number of services in the application, p' (x) is the distribution of congestion in x groups, x is the number of service groups under the application, y is the number of abnormal services in the application, p (y|x) is the probability of occurrence of abnormality in y services in case of abnormality in x groups, and p i The gateway congestion event probability of the maximum entropy is satisfied for the ith service.
S303, service-level flow restriction, service group-level flow restriction or application-level flow restriction is carried out according to the entropy uncertainty proportion and the service request quantity.
In some embodiments, the performing service-level throttling, service group-level throttling or application-level throttling according to the entropy uncertainty proportion and the service request amount may specifically include:
(one) service level throttling
And triggering the single-service request quantity of the abnormality to carry out service-level flow limiting when the entropy uncertainty proportion is smaller than a first threshold value and the group request quantity of the service group to which the abnormality belongs does not reach the group request quantity threshold value. The first threshold and the group request amount threshold can be reasonably set according to actual needs. In some embodiments, the first threshold may take any value between 5% and 15% as desired. Preferably, the first threshold may be 10%.
For example, in an exemplary embodiment, if an application F-TEST, the application associates groups m, services n under each group; at the current transaction moment, if the single service request quantity is abnormal under the kth group, and the request quantity of the kth group does not reach the group request quantity threshold; if the entropy uncertainty ratio is smaller than 10%, the possibility that the k group is congested due to the single service request quantity abnormality which occurs at present is smaller, and in order to ensure the normal operation of the k group, service-level current limiting can be performed on the single service request quantity with the single service request quantity abnormality under the k group. In addition, when there are x services having single service request quantity abnormality in n services in the kth group, service level flow restriction can be performed on the x services respectively. Obviously, the x services at this time are less in proportion to the n services under the kth group; otherwise, the corresponding entropy uncertainty is not less than 10%.
(II) group level current limiting
And triggering to carry out service group level current limiting on the service group when the entropy uncertainty proportion is larger than a first threshold and smaller than or equal to a second threshold and the group request quantity of the service group to which the abnormality belongs reaches a group request quantity threshold. The first threshold and the group request amount threshold can be reasonably set according to actual needs. In some embodiments, the second threshold may take any value between 45% and 55% as desired. Preferably, the second threshold may be 50%. For example, in an exemplary embodiment, the first threshold may be 10% and the second threshold may be 50%. If a certain application F-TEST is applied, the application is associated with m groups, and each group is provided with n services; at the current transaction moment, if the single service request quantity is abnormal under the kth group, and the kth group request quantity reaches a group request quantity threshold; if the entropy uncertainty ratio is greater than 10% and less than 50%, the current single service request quantity abnormality has a larger influence on congestion of the kth group, and in order to avoid the occurrence of integral congestion of the kth group, service group level current limiting on the kth group, namely current limiting on the whole kth group, can be triggered.
(III) application level current limiting
Triggering application-level throttling of the application when the entropy uncertainty ratio is greater than a second threshold and the application request amount of the application reaches an application request amount threshold.
For example, in an exemplary embodiment, if an application F-TEST is applied, at the current transaction time, if the application request amount of the application F-TEST reaches the application request amount threshold and the entropy uncertainty ratio at this time is greater than 50%, it indicates that most groups under the application F-TEST are congested, and in order to prevent the whole application F-TEST from being unable to provide services (even being down) due to overall congestion, application-level current limiting may be triggered on the application F-TEST, that is, current limiting is performed on the whole application F-TEST.
Therefore, the embodiment of the specification comprehensively judges according to the entropy uncertainty proportion and the service request quantity, adaptively performs the current limiting of the corresponding dimension, not only can ensure the stable operation of the gateway, but also can realize the current limiting self-protection of different dimensions for the abnormality implementation of different layers.
In the above embodiment of the present disclosure, the throttling may be to reject the subsequent transaction request at the front end, and directly return the transaction failure to the transaction request, so as to ensure the operation stability of the service gateway and the application.
In other embodiments, in the multi-dimensional dynamic grouping current limiting method, the real-time processing pressure of each service and each group under the application can be dynamically monitored, and when the real-time processing pressure is confirmed to be normal, the current limiting of the corresponding level can be timely canceled, so that the service processing efficiency is improved, and the service processing delay is reduced.
Corresponding to the multi-dimensional dynamic grouping current limiting method, the embodiment of the specification also provides a multi-dimensional dynamic grouping current limiting device. Referring to fig. 5, the multi-dimensional dynamic grouping current limiting apparatus may include an abnormality determination module 51, a proportion determination module 52, and a multi-dimensional current limiting module 53. Wherein:
the abnormality determination module 51 may be configured to determine whether the service request amount at the current transaction time is abnormal;
the proportion determining module 52 may be configured to obtain a current entropy uncertainty proportion of the application when the traffic request amount at the current transaction time is abnormal;
the multidimensional throttling module 53 may be configured to perform service-level throttling, service group-level throttling, or application-level throttling according to the entropy uncertainty ratio and the traffic request.
In the embodiment of the present disclosure, the multidimensional dynamic packet current limiting device may perform service-level current limiting, service group-level current limiting, or application-level current limiting according to the entropy uncertainty ratio and the service request amount when the service request amount at the current transaction time is abnormal. Because the entropy uncertainty proportion can be used for representing the congestion probability of the judged object, when multidimensional multi-flow limiting is carried out according to the entropy uncertainty proportion and the service request quantity, the method not only can support high-concurrency service transaction, but also can reduce or avoid service gateway congestion, thereby improving the running stability of an application system and reducing the operation and maintenance pressure of operation and maintenance personnel.
In some embodiments of the multidimensional dynamic packet flow restrictor, the determining whether the traffic request at the current transaction time is abnormal includes:
for each service single service request quantity at the current transaction moment, judging whether the single service request quantity is positioned in a corresponding preset first confidence interval [ m ] i -3δ i ,m i +3δ i ]An inner part; wherein m is i For the i-th service, the request amount average value delta in a specified history period i The variance of the request amount in a specified history period for the ith service;
and when the single service request quantity is not positioned in the corresponding preset first confidence interval, confirming that the single service request quantity is abnormal.
In some embodiments of the multidimensional dynamic packet flow restrictor, the determining whether the traffic request at the current transaction time is abnormal includes:
for the group request quantity of each service group at the current transaction time, judging whether the group request quantity is positioned in a corresponding preset second confidence interval [ m ] j -3δ j ,m j +3δ j ]An inner part; wherein m is j Average, delta, of requests for j-th service group in specified history period j The variance of the request quantity in a specified history period for the j-th service group;
and when the group request quantity is not in the second confidence interval corresponding to the preset, confirming that the group request quantity is abnormal.
In some embodiments of the multidimensional dynamic packet flow restrictor, the determining whether the traffic request at the current transaction time is abnormal includes:
judging whether the application request quantity is positioned in a preset third confidence interval [ m-3 delta, m+3 delta ] or not according to the application request quantity at the current transaction moment; wherein m is the average value of the request amount applied in the appointed historical period, and delta is the variance of the request amount applied in the appointed historical period;
and when the application request quantity is not located in the third confidence interval, confirming that the application request quantity is abnormal.
In some embodiments of the multidimensional dynamic packet current limiting apparatus, the obtaining the current entropy uncertainty ratio of the application includes:
according to the formulaDetermining the current entropy uncertainty proportion of the application;
where t is the current entropy uncertainty proportion of the application, n is the number of services in the application, p' (x) is the distribution of congestion in x groups, x is the number of service groups under the application, y is the number of abnormal services in the application, p (y|x) is the probability of occurrence of abnormality in y services in case of abnormality in x groups, and p i The gateway congestion event probability of the maximum entropy is satisfied for the ith service.
In some embodiments of the multi-dimensional dynamic packet throttling device, the performing service-level throttling, service group-level throttling, or application-level throttling according to the entropy uncertainty ratio and the traffic request amount comprises:
and triggering the single-service request quantity of the abnormality to carry out service-level flow limiting when the entropy uncertainty proportion is smaller than a first threshold value and the group request quantity of the service group to which the abnormality belongs does not reach the group request quantity threshold value.
In some embodiments of the multi-dimensional dynamic packet throttling device, the performing service-level throttling, service group-level throttling, or application-level throttling according to the entropy uncertainty ratio and the traffic request amount comprises:
and triggering to carry out service group level current limiting on the service group when the entropy uncertainty proportion is larger than a first threshold and smaller than or equal to a second threshold and the group request quantity of the service group to which the abnormality belongs reaches a group request quantity threshold.
In some embodiments of the multi-dimensional dynamic packet throttling device, the performing service-level throttling, service group-level throttling, or application-level throttling according to the entropy uncertainty ratio and the traffic request amount comprises:
triggering application-level throttling of the application when the entropy uncertainty ratio is greater than a second threshold and the application request amount of the application reaches an application request amount threshold.
In some embodiments of the multidimensional dynamic grouping current limiting device, the value range of the first threshold is 5% -15%.
In some embodiments of the multidimensional dynamic grouping current limiting device, the value range of the second threshold is 45% -55%.
For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when implemented in the present specification.
While the process flows described above include a plurality of operations occurring in a particular order, it should be apparent that the processes may include more or fewer operations, which may be performed sequentially or in parallel (e.g., using a parallel processor or a multi-threaded environment).
Embodiments of the present description also provide a computer device. As shown in fig. 6, in some embodiments of the present description, the computer device 602 may include one or more processors 604, such as one or more Central Processing Units (CPUs) or Graphics Processors (GPUs), each of which may implement one or more hardware threads. The computer device 602 may also include any memory 606 for storing any kind of information such as code, settings, data, etc., and in a particular embodiment, a computer program on the memory 606 and executable on the processor 604, which when executed by the processor 604, may perform the instructions of the multidimensional dynamic packet throttling method described in any of the embodiments above. For example, and without limitation, memory 606 may include any one or more of the following combinations: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any memory may store information using any technique. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent fixed or removable components of computer device 602. In one case, when the processor 604 executes associated instructions stored in any memory or combination of memories, the computer device 602 can perform any of the operations of the associated instructions. The computer device 602 also includes one or more drive mechanisms 608, such as a hard disk drive mechanism, an optical disk drive mechanism, and the like, for interacting with any memory.
The computer device 602 may also include an input/output interface 610 (I/O) for receiving various inputs (via an input device 612) and for providing various outputs (via an output device 614). One particular output mechanism may include a presentation device 616 and an associated graphical user interface 618 (GUI). In other embodiments, input/output interface 610 (I/O), input device 612, and output device 614 may not be included, but merely as a computer device in a network. The computer device 602 may also include one or more network interfaces 620 for exchanging data with other devices via one or more communication links 622. One or more communication buses 624 couple the above-described components together.
The communication link 622 may be implemented in any manner, for example, through a local area network, a wide area network (e.g., the internet), a point-to-point connection, etc., or any combination thereof. Communication link 622 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to some embodiments of the specification. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processor to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processor, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processor to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processor to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computer device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computer device. Computer readable media, as defined in the specification, does not include transitory computer readable media (transmission media), such as modulated data signals and carrier waves.
It will be appreciated by those skilled in the art that embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the present specification embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present description embodiments may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The present embodiments may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The embodiments of the specification may also be practiced in distributed computing environments where tasks are performed by remote processors that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
It should also be understood that, in the embodiments of the present specification, the term "and/or" is merely one association relationship describing the association object, meaning that three relationships may exist. For example, a and/or B may represent: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the embodiments of the present specification. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (9)
1. A multi-dimensional dynamic packet current limiting method, comprising:
confirming whether the service request amount at the current transaction moment is abnormal or not;
when the service request amount at the current transaction moment is abnormal, acquiring the current entropy uncertainty proportion of the application;
service-level throttling, service group-level throttling or application-level throttling is performed according to the entropy uncertainty proportion and the service request quantity;
the obtaining the current entropy uncertainty proportion of the application comprises the following steps:
according to the formulaDetermining the current entropy uncertainty proportion of the application;
where t is the current entropy uncertainty proportion of the application, n is the number of services in the application, p' (x) is the distribution of congestion in x groups, x is the number of service groups under the application, y is the number of abnormal services in the application, p (y|x) is the probability of occurrence of abnormality in y services in case of abnormality in x groups, and p i Gateway congestion event probability satisfying maximum entropy for the ith service;
the performing service-level throttling, service group-level throttling or application-level throttling according to the entropy uncertainty proportion and the service request quantity comprises the following steps:
when the entropy uncertainty proportion is smaller than a first threshold value and the group request quantity of the service group to which the abnormality belongs does not reach the group request quantity threshold value, triggering to carry out service-level current limiting on the abnormal single-service request quantity;
triggering to carry out service group level current limiting on the service group when the entropy uncertainty proportion is larger than a first threshold and smaller than or equal to a second threshold and the group request quantity of the service group to which the abnormality belongs reaches a group request quantity threshold;
triggering application-level throttling of the application when the entropy uncertainty ratio is greater than a second threshold and the application request amount of the application reaches an application request amount threshold.
2. The multi-dimensional dynamic packet throttling method of claim 1, wherein said confirming whether the traffic request amount at the current transaction time is abnormal comprises:
for each service single service request quantity at the current transaction moment, judging whether the single service request quantity is positioned in a corresponding preset first confidence interval [ m ] i -3δ i ,m i +3δ i ]An inner part; wherein m is i For the i-th service, the request amount average value delta in a specified history period i Is the firsti requests variance of services in a specified history period;
and when the single service request quantity is not positioned in the corresponding preset first confidence interval, confirming that the single service request quantity is abnormal.
3. The multi-dimensional dynamic packet throttling method of claim 1, wherein said confirming whether the traffic request amount at the current transaction time is abnormal comprises:
for the group request quantity of each service group at the current transaction time, judging whether the group request quantity is positioned in a corresponding preset second confidence interval [ m ] j -3δ j ,m j +3δ j ]An inner part; wherein m is j Average, delta, of requests for j-th service group in specified history period j The variance of the request quantity in a specified history period for the j-th service group;
and when the group request quantity is not in the second confidence interval corresponding to the preset, confirming that the group request quantity is abnormal.
4. The multi-dimensional dynamic packet throttling method of claim 1, wherein said confirming whether the traffic request amount at the current transaction time is abnormal comprises:
judging whether the application request quantity is positioned in a preset third confidence interval [ m-3 delta, m+3 delta ] or not according to the application request quantity at the current transaction moment; wherein m is the average value of the request amount applied in the appointed historical period, and delta is the variance of the request amount applied in the appointed historical period;
and when the application request quantity is not located in the third confidence interval, confirming that the application request quantity is abnormal.
5. The method of claim 1, wherein the first threshold has a value ranging from 5% to 15%.
6. The method of claim 1, wherein the second threshold has a value ranging from 45% to 55%.
7. A multi-dimensional dynamic packet current limiting device, comprising:
the abnormality judging module is used for confirming whether the service request quantity at the current transaction moment is abnormal or not;
the proportion determining module is used for acquiring the current entropy uncertainty proportion of the application when the service request quantity at the current transaction moment is abnormal, and specifically comprises the following steps: according to the formulaDetermining the current entropy uncertainty proportion of the application; where t is the current entropy uncertainty proportion of the application, n is the number of services in the application, p' (x) is the distribution of congestion in x groups, x is the number of service groups under the application, y is the number of abnormal services in the application, p (y|x) is the probability of occurrence of abnormality in y services in case of abnormality in x groups, and p i Gateway congestion event probability satisfying maximum entropy for the ith service;
the multidimensional flow limiting module is used for carrying out service level flow limiting, service group level flow limiting or application level flow limiting according to the entropy uncertainty proportion and the service request quantity, and specifically comprises the following steps: when the entropy uncertainty proportion is smaller than a first threshold value and the group request quantity of the service group to which the abnormality belongs does not reach the group request quantity threshold value, triggering to carry out service-level current limiting on the abnormal single-service request quantity; triggering to carry out service group level current limiting on the service group when the entropy uncertainty proportion is larger than a first threshold and smaller than or equal to a second threshold and the group request quantity of the service group to which the abnormality belongs reaches a group request quantity threshold; triggering application-level throttling of the application when the entropy uncertainty ratio is greater than a second threshold and the application request amount of the application reaches an application request amount threshold.
8. A computer device comprising a memory, a processor, and a computer program stored on the memory, characterized in that the computer program, when being executed by the processor, performs the instructions of the method according to any of claims 1-6.
9. A computer storage medium having stored thereon a computer program, which, when executed by a processor of a computer device, performs the instructions of the method according to any of claims 1-6.
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| CN114513470A (en) * | 2020-10-23 | 2022-05-17 | 中国移动通信集团河北有限公司 | Network flow control method, device, equipment and computer readable storage medium |
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| CN114513470A (en) * | 2020-10-23 | 2022-05-17 | 中国移动通信集团河北有限公司 | Network flow control method, device, equipment and computer readable storage medium |
| CN112769633A (en) * | 2020-12-07 | 2021-05-07 | 深信服科技股份有限公司 | Proxy traffic detection method and device, electronic equipment and readable storage medium |
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