CN113297275A - Enterprise-level concurrent authentication control method based on multi-level cache - Google Patents
Enterprise-level concurrent authentication control method based on multi-level cache Download PDFInfo
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- CN113297275A CN113297275A CN202110664473.1A CN202110664473A CN113297275A CN 113297275 A CN113297275 A CN 113297275A CN 202110664473 A CN202110664473 A CN 202110664473A CN 113297275 A CN113297275 A CN 113297275A
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
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- G06F16/24578—Query processing with adaptation to user needs using ranking
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Abstract
The invention relates to an enterprise-level concurrent authentication control method based on multi-level cache, which specifically comprises the following steps: s1, acquiring request information of the user side and sending the request information to the server side; s2, the server side reads the required cache data from the multi-level cache according to the request information and the sequence of the priority from high to low; s3, the server side calculates the authentication result of the request information by the authentication server according to the cache data, and sends the authentication result back to the user side; and S4, the user side obtains the authority response according to the authentication result and feeds back the response result to the server side. Compared with the prior art, the method has the advantages of ensuring the stability of system authentication in a high-concurrency environment, enabling the authentication result of the server to be more efficient and accurate, being suitable for service authentication in a full range, avoiding the situation that the authentication service is unavailable and the like.
Description
Technical Field
The invention relates to the technical field of internet education, in particular to an enterprise-level concurrent authentication control method based on multi-level cache.
Background
The rapid development of computer technology and network technology is changing our life, work and study ways at a very fast speed, and has important influence on the current major traditional industries. In the on-line education of the education institution at present, the online watching of live broadcast, recorded broadcast video, examination and the like through a computer and a network technology is a common phenomenon. But in the face of high concurrent access and authentication of hundreds of millions of students, whether higher quality and better stability can be realized or not determines the user experience and the system quality of the enterprise internet educational administration products.
However, with the need for such a more efficient learning experience, system services at an enterprise level are often confronted with the dilemma that high-concurrency services are not available. If multiple live broadcasts are started at the same time, the service authentication condition of each live broadcast in various dimensions is complicated, including whether a student has the right to enter a live broadcast room, which live broadcast room to enter, and which operation right to have the live broadcast room. This will place a great stability pressure on the entire enterprise system if the query authentication of the real-time very long link is performed. Not only is the time consumed huge, but also the concurrent throughput is greatly discounted, and the whole online live broadcast system is put into paralysis and downtime under the overwhelming pressure.
Therefore, the high efficiency, stability, usability, accuracy and real-time performance of the authentication method or system become core technical problems to be solved at present.
Disclosure of Invention
The invention aims to overcome the defects of poor system authentication stability and accuracy in a high concurrency environment in the prior art and provide an enterprise-level concurrency authentication control method based on multi-level cache.
The purpose of the invention can be realized by the following technical scheme:
an enterprise-level concurrent authentication control method based on multi-level cache specifically comprises the following steps:
s1, acquiring request information of the user side and sending the request information to the server side;
s2, the server side reads the required cache data from the multi-level cache according to the priority from high to low according to the request information;
s3, the server side calculates the authentication result of the request information by the authentication server according to the cache data, and sends the authentication result back to the user side;
and S4, the user side obtains the authority response according to the authentication result and feeds back the response result to the server side.
The request information of the user side in step S1 includes user information, device information, and authorized request address information.
The multi-level cache in step S2 includes a memory cache of the server, a Redis distributed cache, and a database server cache.
Further, the multi-level cache is the data in the memory cache, the Redis distributed cache, the database server cache and the database of the server according to the sequence that the priority is sorted from high to low.
Further, the cache data of the Redis distributed cache includes service scene attribute information corresponding to the request information.
The types of the permission response in the step S4 include the permission to enter the next operation and the permission to operate the page.
The step S4 further includes retaining the corresponding cache data in the authentication result at the user end for the user end to use for preliminary authentication.
The step S2 further includes the step that the server inputs the request information of the client into the machine learning model for training, generates a training task, and analyzes the training task to obtain training task parameters.
Further, the server side performs integration analysis on the request information before inputting the request information of the user side into the machine learning model.
Further, the step S3 includes inputting the authentication result into a machine learning model for training.
Further, the step S4 further includes inputting the response result fed back by the user end into the machine learning model for training, accelerating the training speed of the machine learning model, and circularly learning the authentication path of the user end in a multidimensional manner to relate to the weight coupling degree of the service.
And the server side sequentially processes and updates the training results of the machine learning model to a multi-level cache for the next authentication.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention stores the information required by the user side through the multi-level cache, calculates the authentication result of the request information by the authentication server by calling the cache data when needed, improves the stability of system authentication in a high concurrency environment, simultaneously flexibly matches more accurate weighting weight and path through the multi-level cache data, and leads the authentication result of the server side to be more efficient and accurate.
2. The server side trains authentication models under various service scenes according to the request information of the user side through various machine learning models to obtain richer and more comprehensive user dimension authentication portraits.
3. The invention supports the service authentication requirement under the internet online education, is suitable for the service authentication in the whole range, has rich authentication dimension and authentication mode, and supports the service authentication under the complex scene without the passing of the weight.
4. The server side of the invention adopts various fault-tolerant mechanisms, cache service, message queues and other modes, avoids the situation that the authentication service is unavailable, and realizes a stable and highly available system.
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FIG. 1 is a schematic flow chart of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Examples
As shown in fig. 1, a multi-level cache-based enterprise-level concurrent authentication control method can provide a stable, efficient and accurate enterprise-level authentication method or system under the condition of ten million-level flow, and specifically includes the following steps:
s1, acquiring request information of the user side and sending the request information to the server side;
s2, the server side reads the required cache data from the multi-level cache according to the request information and the sequence of the priority from high to low;
s3, the server side calculates the authentication result of the request information by the authentication server according to the cache data, and sends the authentication result back to the user side;
and S4, the user side obtains the authority response according to the authentication result and feeds back the response result to the server side.
The request information of the user side in step S1 includes user information, device information, and authorized request address information.
In this embodiment, in step S1, the user end integrates the cached data into useful data according to the user end, and then performs a simple authentication judgment, and sends the request information to the server end.
In this embodiment, an instant messaging link is used between the user side and the server side, so that user experience is improved.
In step S2, the multi-level cache includes a memory cache of the server, a Redis distributed cache, and a database server cache.
The multi-level cache is used for storing data in a memory cache, a Redis distributed cache, a database server cache and a database of a server side according to the sequence of the priority levels sorted from high to low.
The cache data of the Redis distributed cache comprises service scene attribute information corresponding to the request information.
In this embodiment, authentication information is first obtained from a memory cache of the server, whether the cache is hit is judged, if not, a machine learning result is continuously obtained from the Redis distributed cache, whether the cache is hit is judged, if not, permission information is obtained from a cache of the database server, if not, cache data is finally obtained from the database, and if the cache is hit, the server calculates an authentication result of the request information by the authentication server according to the cache data.
In this embodiment, if the server needs distributed computation, the server sends a message to the message queue.
The types of the permission response in step S4 include the permission to enter the next operation and the permission of the operable page.
Step S4 further includes retaining the corresponding cache data in the authentication result at the user end for the user end to use for preliminary authentication.
Step S2 further includes the server inputting the request information of the client to the machine learning model for training, generating a training task, and analyzing the training task to obtain training task parameters.
In the embodiment, the server performs scene-based training in subsequent training, so that the accuracy of the model is improved, and the recognition scene of the model is better.
Before the request information of the user side is input into the machine learning model, the server side carries out integration analysis on the request information.
Step S3 further includes inputting the authentication result into the machine learning model for training.
Step S4 further includes inputting the response result fed back by the user end to the machine learning model for training, accelerating the training speed of the machine learning model, and circulating the authentication path of the multidimensional learning user end to relate to the weight coupling degree of the service, thereby forming model training of closed-loop machine learning and obtaining a more accurate training authentication model.
And the server side sequentially processes and updates the training results of the machine learning model to a multi-level cache for the next authentication.
When the method is implemented specifically, the server side transmits the message in real time through the first-in first-out queue, the priority queue and the instant communication technology according to the information input by the user side. And the authentication model is trained more intelligently and comprehensively through a knowledge map and a machine learning algorithm, and the stability, the accuracy and the real-time performance of service are improved through step-by-step caching, so that the learning satisfaction and the experience of a user are improved.
In addition, it should be noted that the specific embodiments described in the present specification may have different names, and the above descriptions in the present specification are only illustrations of the structures of the present invention. All equivalent or simple changes in the structure, characteristics and principles of the invention are included in the protection scope of the invention. Various modifications or additions may be made to the described embodiments or methods may be similarly employed by those skilled in the art without departing from the scope of the invention as defined in the appending claims.
Claims (10)
1. An enterprise-level concurrent authentication control method based on multi-level cache is characterized by comprising the following steps:
s1, acquiring request information of the user side and sending the request information to the server side;
s2, the server side reads the required cache data from the multi-level cache according to the priority from high to low according to the request information;
s3, the server side calculates the authentication result of the request information by the authentication server according to the cache data, and sends the authentication result back to the user side;
and S4, the user side obtains the authority response according to the authentication result and feeds back the response result to the server side.
2. The method as claimed in claim 1, wherein the request information of the user terminal in step S1 includes user information, device information and authorized request address information.
3. The method for controlling enterprise-level concurrent authentication based on multi-level cache according to claim 1, wherein the multi-level cache in step S2 includes a memory cache of a server, a Redis distributed cache, and a database server cache.
4. The method according to claim 3, wherein the multi-level caches are the memory cache of the server, the Redis distributed cache, the database server cache and the data in the database in an order of priority ranking from high to low.
5. The method according to claim 3, wherein the cache data of the Redis distributed cache includes service scenario attribute information corresponding to the request information.
6. The method for controlling enterprise-level concurrent authentication based on multi-level cache of claim 1, wherein the types of permission responses in step S4 include a permission to enter a next operation and a permission to operate a page.
7. The method for controlling enterprise-level concurrent authentication based on multi-level cache according to claim 1, wherein step S4 further comprises retaining the corresponding cache data in the authentication result at the user end.
8. The method for enterprise-level-based concurrency authentication control based on multi-level cache according to claim 1, wherein the step S2 further comprises the steps of inputting request information of a user terminal into a machine learning model by the server for training, generating a training task, and analyzing the training task to obtain training task parameters.
9. The method for controlling enterprise-level concurrency authentication based on multi-level cache of claim 8, wherein said step S3 further comprises inputting the authentication result into a machine learning model for training.
10. The method for controlling enterprise-level concurrency authentication based on multi-level cache of claim 8, wherein said step S4 further comprises inputting the response result fed back from the user end to the machine learning model for training.
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Cited By (1)
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| CN114912082A (en) * | 2021-12-15 | 2022-08-16 | 许磊 | General computing task collaboration system |
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Application publication date: 20210824 |