CN109558789A - A kind of biological characteristic system for rapidly identifying based on distributed computing - Google Patents
A kind of biological characteristic system for rapidly identifying based on distributed computing Download PDFInfo
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/70—Multimodal biometrics, e.g. combining information from different biometric modalities
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Abstract
The present invention includes a kind of biological characteristic system for rapidly identifying based on distributed computing, comprising: client, registration and identification for sending biological characteristic by message queue are requested；Message queue, for creating message queue, to message queue publication and monitoring information；Cluster management system, for being safeguarded and being dispatched to node listing；Registration service end receives the registration request from client, and sends registering result to client by message queue；It identifies server-side, receives the bio-identification request from client, and recognition result is sent to client by message queue；Biometric sample library, for storing the biometric sample of multiple format.The invention has the benefit that for the biological attribute data sample database of magnanimity to be split into small biometric sample collection, parallel search is carried out to the sample that biometric sample is concentrated by the living things feature recognition service node of distributed type assemblies, to greatly shorten the response time of living things feature recognition.
Description
Technical field
The present invention relates to a kind of biological characteristic system for rapidly identifying based on distributed computing, belongs to computer digital animation
Field.
Background technique
Big data era, internet platform need to handle a large amount of service request, as double 11 periods in 2016, Ali
Alipay created the records of 120,000 payments of processing in one second, the behind of this record, distributed computing plays extremely
Important role is likely to the so big trading volume of processing exactly because there is distributed computing.
What is meant by distributed computing? distributed computing is a kind of calculation method, and it is opposite that centralization, which calculates,.With calculating
The development of technology, some applications are needed very huge computing capability that could complete, if calculated using centralization, need to expend
Considerable time completes.The application decomposition at many small parts, is distributed to multiple stage computers progress by distributed computing
Processing.The overall calculation time can be saved in this way, greatly improve computational efficiency.In addition, some calculating tasks, need to form collection
Group, dynamically distributes the computing resource in cluster,, can during double 11 to meet the needs of business, such as Alipay
With root it was predicted that distributing enough computing resources for payment system, so that extensive transaction instantaneous during meeting double 11 is asked
It asks.
The core and essence of distributed computing are the distribution and scheduling of calculating task, i.e., how to arrive distribution of computation tasks
Suitable computing resource gets on, and calculated result is quickly returned to computation requests person.The challenge of distributed computing is lain also in
This.
Distributed computing has very high technical threshold, therefore distributed computation ability is in fact by Large-Scale Interconnected net
Platform is monopolized, small internet platform, has no ability to exploitation distributed computing system, it is flat to also result in these small internets
Platform cannot technically make big innovation, and computing resource cannot be extended according to the demand of business, limit further hair
Exhibition.
With the development of technology, especially deep learning/artificial intelligence technology development, the standard of the living things feature recognition of people
True rate (such as face, iris, fingerprint) is higher and higher, and correspondingly, more and more scenes will use biological identification technology
To solve the identification and identification of user.The identity traditional compared to password etc. identifies means, and living things feature recognition is safer,
And use is also more convenient.But living things feature recognition needs to use deep learning/artificial intelligence technology, needs largely to calculate,
When the sample size in biometric sample library reaches million/ten million or even hundred million grades, with traditional deep learning and people
Work intelligence, each identification process will take a substantial amount of time, this will limit significantly biometrics identification technology in systems in practice
Large-scale application.One big biometric sample library is divided into several small, virtual biological characteristic samples by this patent
Then this collection uses distributed computing technology, form living things feature recognition cluster, each node in cluster, be only responsible for one or
The identification of the several biometric sample collection of person, to guarantee the response time of identification.
CSV, otherwise referred to as character separation value, because separating character may not be comma, file is with plain text shape
Formula stores list data (number and text).Plain text means that this document is a character string, without necessary as binary system
Digital data interpreted like that.Csv file is made of any number of record, with the separation of certain newline between record；Every
Record is made of field, and the separator of interfield is other characters or character string, most commonly comma or tab.
The target of this patent is to design a kind of biological characteristic system for rapidly identifying based on distributed computing, allows system energy
In the biometric sample library of millions/hundred million grade, matched biological sample is rapidly found out.
Summary of the invention
In view of the deficiencies of the prior art, a kind of biological characteristic system for rapidly identifying based on distributed computing, allows system energy
In the biometric sample library of millions/hundred million grade, matched biological sample is rapidly found out.
Technical solution of the present invention includes a kind of biological characteristic system for rapidly identifying based on distributed computing, including client
End, cluster management system, message queue, identification server-side, registration service end and biometric sample library, it is characterised in that: visitor
Family end, registration and identification for sending biological characteristic by message queue are requested；Message queue, for creating message queue,
To message queue publication and monitoring information, wherein message queue includes cluster message queue, server-side message queue and client
Message queue,
Server-side message queue: user receives the computation requests from client, and by computation requests by being scheduled to meter
Operator node (such as registration service end and identification server-side).There are two types of scheduling strategy, the first formula polling schemas, by computation requests
A calculate node being scheduled in cluster；Second is broadcast, i.e., all calculating sections being scheduled to computation requests in cluster
Point；
Client message queue: calculate node sends calculated result to client message queue, and client passes through the message
Queue receives the calculated result from calculate node；
Cluster management system, for server-side node listing to be safeguarded and dispatched, wherein server-side includes identification clothes
Business end and registration service end；Registration service end, for receiving the node of biological characteristic registration service, by monitoring server-side message
Queue receives the biological characteristic registration request from client, and sends biological characteristic note to client by message queue
Volume result；It identifies server-side, for receiving the end node of living things feature recognition service, by monitoring server-side message queue, connects
The bio-identification request from client is received, and recognition result is sent to client by message queue；Biometric sample
Library, for storing the biometric sample of multiple format.
According to the biological characteristic system for rapidly identifying based on distributed computing, the client includes: registration
Request module sends biological characteristic registration request to biological characteristic registration cluster message queue；Request module is identified, to biological spy
Sign identification cluster message queue sends living things feature recognition request.
According to the biological characteristic system for rapidly identifying based on distributed computing, the registration module for execute with
Lower step: S31 is connected to the message queue of biological characteristic registration cluster by cluster management system；S32 is based on S31 to life
The message queue that object feature registers cluster sends registration request, and wherein biological characteristic registration request includes the unique user of system
Identification code, and the raw image data comprising user biological feature, wherein the corresponding multiple biological characteristics of each user identifier；
S33 is scheduled request after the cluster management system is connected to biological characteristic registration request, further by corresponding requests point
It is fitted on a biological characteristic registration service node in cluster；S34 is right after biological characteristic registration service node is connected to registration request
The initial data of user biological feature carries out living things feature recognition, and by the biological characteristic recognized and corresponding client identification
Symbol is associated, and then biological characteristic is stored into biometric sample library；S35 sends the processing result of registration request
To only client message queue.
According to the biological characteristic system for rapidly identifying based on distributed computing, the identification module is used to execute
Following steps: S41 is connected to the message queue that biological characteristic registers cluster by cluster management system；S42 is based on step S41
Identification request is sent to living things feature recognition cluster message queue, contains user biological feature in living things feature recognition request
Raw image data；S43 is scheduled request after the cluster management system is connected to biological especially identification request, thus will
The request all living things feature recognition service nodes into living things feature recognition cluster are broadcasted；S44, living things feature recognition clothes
After business node is connected to identification request, living things feature recognition is carried out to the initial data comprising user biological feature, and save with service
The sample of the corresponding biometric sample concentration of point institute is compared；S35, after finding matched sample by S44, by sample institute
Corresponding user's unique identification is sent to client message queue.
According to the biological characteristic system for rapidly identifying based on distributed computing, which is characterized in that the cluster pipe
Reason system includes: distributed management module, for carrying out Dynamic Maintenance to request and response queue, is in real-time servicing cluster
The calculate node list of service state；Distributed computing module: for when client initiates computation requests to cluster, cluster to be logical
It crosses string type and calculates the calculate node being assigned to the computation requests with parallel type in cluster.
According to the biological characteristic system for rapidly identifying based on distributed computing, the use of the distributed management module
In executing following steps: S61, calculate node states the cluster name of oneself, and to system registry itself；S62, system are receiving
It after registration request, can be inquired into cluster-list, if the cluster of same names is had existed, if it is not, can be the collection
Group establishes a request queue, and cluster-list is added in the cluster, otherwise which is added to the request of cluster automatically
Queue；S63, when calculate node goes offline and when person actively leaves, system can be actively by the calculate node from corresponding cluster
It deletes.
According to the biological characteristic system for rapidly identifying based on distributed computing, the string of the distributed computing module
Line is calculated for executing following steps: S71, client send computation requests into the request queue of cluster；S72, client
To the response queue of one client of computing cluster application, the calculated result from the queue is monitored；S73, computing cluster from
Waiting time longest computation requests are obtained in request queue, and calculate node is found out by polling algorithm, computation requests are distributed
Give the calculate node；S74, the calculate node chosen executes computation requests, and calculated result is returned by queue of receiveing the response
To client.
According to the biological characteristic system for rapidly identifying based on distributed computing, the distributed computing module and
Line is calculated for executing following steps: S81, client send computation requests into the request queue of cluster；S82, client
The calculated result from the queue is monitored in response to one client of computing cluster application；S83, computing cluster is from request
In the computation requests that are most started, and the computation requests are distributed into all calculate nodes in cluster；S84, it is all to cluster
Calculate node execute computation requests, and the calculated result of each node is returned into client by queue of receiveing the response, it is right
In the node for being focused to find out matched user in biometric sample, then calculated result is returned into client, otherwise then terminated
It calculates, result of not going back on one's word.
According to the biological characteristic system for rapidly identifying based on distributed computing, it is characterised in that: the biology
Feature samples library can be traditional file system, csv file format, structured database and unstructured database.
According to above-mentioned any biological characteristic system for rapidly identifying based on distributed computing, which is characterized in that institute
Stating biological characteristic includes but is not limited to: face, fingerprint, iris.
The invention has the benefit that the biological attribute data sample database of magnanimity can be split into small biological characteristic sample
This collection carries out parallel search to the sample that biometric sample is concentrated by the living things feature recognition service node of distributed type assemblies,
To greatly shorten the response time of living things feature recognition, the authentication techniques based on biological characteristic will be promoted each significantly
The application in field (including transaction, payment, safety etc.).
Detailed description of the invention
Fig. 1 show the overall construction drawing of embodiment according to the present invention；
Fig. 2 show the general technical architecture diagram of embodiment according to the present invention；
Fig. 3 show the flow chart for sending registration request of embodiment according to the present invention；
Fig. 4 show the flow chart for sending identification to request of embodiment according to the present invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, right in the following with reference to the drawings and specific embodiments
The present invention is described in detail.The system and method for game graph demand and design of the invention are suitable for game animation image
Exploitation.
Fig. 1 show the overall construction drawing of embodiment according to the present invention.System of the invention includes client as shown in the figure
End, cluster management system, message queue, identification server-side, registration service end and biometric sample library, it is characterised in that: visitor
Family end, registration and identification for sending biological characteristic by message queue are requested；Message queue, for creating message queue,
To message queue publication and monitoring information, wherein message queue includes cluster message queue, server-side message queue and client
Message queue；Cluster management system, for being safeguarded and being dispatched to node listing；Registration service end, for receiving and processing
The node of biological characteristic registration service receives the registration request from client, Yi Jitong by monitoring server-side message queue
It crosses message queue and sends registering result to client；It identifies server-side, for receiving the node of living things feature recognition request, passes through
Server-side message queue is monitored, receives the bio-identification request from client, and send to client by message queue
Recognition result；Biometric sample library, for storing the biometric sample of multiple format.
Fig. 2 show the general technical architecture diagram of embodiment according to the present invention.General technical framework is as shown above,
In:
(101) client includes following major function:
(a) face registration request is sent to biological characteristic registration cluster message queue；
(b) recognition of face request is sent to living things feature recognition cluster message queue.
(102) message queue includes following major function:
(a) message queue is created；
(b) it gives out information to message queue；
(c) monitoring information.
The following three classes message queue of message queue major maintenance:
(a) cluster message queue: each cluster has a unique message queue, is marked by unique cluster name
Know, client sends computation requests to cluster message queue, then sends server-side for computation requests by cluster management system
Message queue；
(b) server-side message queue: each server-side (registration service end/identification server-side) node has one uniquely to disappear
Queue is ceased, by the Unique ID of service end node.
(1023) client message queue: each client has a unique message queue, by the unique of client
ID mark.
(103) cluster management includes following major function:
(a) the server-side node listing of cluster is safeguarded；
(b) the client node list of cluster is safeguarded；
(c) computation requests are dispatched.
(104) registration service end includes following major function:
(a) the service end node registered to cluster management system registration biological characteristic cluster；
(b) by monitoring server-side message queue, the registration request from client is received；
(c) registering result is sent to client by message queue.
(105) it identifies server-side, includes following functions:
(a) to the service end node of cluster management system registration living things feature recognition cluster；
(b) by monitoring server-side message queue, the bio-identification request from client is received；
(c) recognition result is sent to client by message queue；
(d) biometric sample library, biometric sample library can store biometric sample library with arbitrary format, for example pass
The file system of system, CSV format, structured database, unstructured database etc..
(107) biometric sample collection, biometric sample collection are a subset in biometric sample library, each sample
Collection contains the biological sample of fixed quantity.
Fig. 3 show the flow chart for sending registration request of embodiment according to the present invention.Its implementing procedure is as follows:
1. being connected to the message queue of biological characteristic registration cluster by cluster management system；
2. judging to connect successfully? if successful connection, step 3 is gone to, otherwise goes to 21, if step 21 malfunctions,
Terminate whole flow process
3. the message queue transmission registration request of cluster is registered to biological characteristic by 205, in biological characteristic registration request
The unique User ID of system, and the raw image data comprising user biological feature are contained, 31 and 4 are performed simultaneously；
31. monitoring client message queue, registering result can be obtained from this queue；
4. after cluster management system is connected to biological characteristic registration request, being scheduled to the request, thus by the request point
It is fitted on a biological characteristic registration service node in cluster；
5. after biological characteristic registration service node is connected to registration request, being carried out to the initial data comprising user biological feature
Living things feature recognition, and the ID of the biological characteristic recognized and the user is associated, it is put into biometric sample library.
6. after the complete registration request of biological characteristic registration service node processing, sending client for the processing result of registration request
In the message queue at end.
Fig. 4 show the flow chart for sending identification to request of embodiment according to the present invention.
1. being connected to the message queue of biological characteristic registration cluster by cluster management system；
2. judging to connect successfully? if successful connection, step 3 is gone to, otherwise goes to 21, if 21 errors, terminate
Whole flow process；Identification request is sent to living things feature recognition cluster message queue by 205, contains use in bio-identification request
The initial data of family biological characteristic, is performed simultaneously 31 and 4；
31. monitoring client message queue, recognition result can be obtained from this queue；
4. be scheduled after cluster management system is connected to biological especially identification request to the request, thus by the request to
All living things feature recognition service nodes are broadcasted in living things feature recognition cluster；
After living things feature recognition service node is connected to identification request, the initial data comprising user biological feature is given birth to
The identification of object feature, and the sample that the biometric sample being responsible for service node is concentrated is compared.
5. if some living things feature recognition service nodes has found from sample set and matches with raw biometric
User identifier corresponding to the sample is then dealt into the message queue of client and goes by sample.
The above, only presently preferred embodiments of the present invention, the invention is not limited to above embodiment, as long as
It reaches technical effect of the invention with identical means, all should belong to protection scope of the present invention.In protection model of the invention
Its technical solution and/or embodiment can have a variety of different modifications and variations in enclosing.
Claims (10)
1. a kind of biological characteristic system for rapidly identifying based on distributed computing, including client, cluster management system, message team
Column, identification server-side, registration service end and biometric sample library, it is characterised in that:
Client, registration and identification for sending biological characteristic by message queue are requested；
Message queue, for creating message queue, to message queue publication and monitoring information, wherein message queue includes that cluster disappears
Cease queue, server-side message queue and client message queue；
Cluster management system, for server-side node listing to be safeguarded and dispatched, wherein server-side includes identification server-side
With registration service end；
Registration service end, for receiving the node of biological characteristic registration service, by monitoring server-side message queue, reception is come from
The biological characteristic registration request of client, and biological characteristic registering result is sent to client by message queue；
It identifies server-side, for receiving the end node of living things feature recognition service, by monitoring server-side message queue, receives and
It is requested from the bio-identification of client, and recognition result is sent to client by message queue；
Biometric sample library, for storing the biometric sample of multiple format.
2. the biological characteristic system for rapidly identifying according to claim 1 based on distributed computing, which is characterized in that described
Client include:
Registration request module sends biological characteristic registration request to biological characteristic registration cluster message queue；
It identifies request module, sends living things feature recognition request to living things feature recognition cluster message queue.
3. the biological characteristic system for rapidly identifying according to claim 2 based on distributed computing, which is characterized in that described
Registration module is for executing following steps:
S31 is connected to the message queue of biological characteristic registration cluster by cluster management system；
S32 sends registration request to the message queue of biological characteristic registration cluster based on S31, wherein biological characteristic registration request
Including, the unique user identification code of system, and the raw image data comprising user biological feature, wherein each user identifier
Corresponding multiple biological characteristics；
S33 is scheduled request after the cluster management system is connected to biological characteristic registration request, further asks correspondence
It asks and is assigned to a biological characteristic registration service node in cluster；
After biological characteristic registration service node is connected to registration request, it is special to carry out biology to the initial data of user biological feature by S34
Sign identification, and the biological characteristic recognized and corresponding client identifier is associated, so by biological characteristic store to
In biometric sample library；
The processing result of registration request is sent to a client message queue by S35.
4. the biological characteristic system for rapidly identifying according to claim 2 based on distributed computing, which is characterized in that described
Identification module is used to execute following steps:
S41 is connected to the message queue that biological characteristic registers cluster by cluster management system；
S42 sends identification request to living things feature recognition cluster message queue based on step S41, in living things feature recognition request
Contain the raw image data of user biological feature；
S43 is scheduled request after the cluster management system is connected to biological especially identification request, thus by the request to
All living things feature recognition service nodes are broadcasted in living things feature recognition cluster；
S44 gives birth to the initial data comprising user biological feature after living things feature recognition service node is connected to identification request
The identification of object feature, and be compared with the sample of service node institute corresponding biometric sample concentration；
User's unique identification corresponding to sample after finding matched sample by S44, is sent to client message team by S35
Column.
5. the biological characteristic system for rapidly identifying based on distributed computing according to claim 1, which is characterized in that the cluster
Management system includes:
Distributed management module is in service shape for carrying out Dynamic Maintenance to request and response queue in real-time servicing cluster
The calculate node list of state；
Distributed computing module: for when client initiates computation requests to cluster, cluster to be by string type calculating and parallel
The computation requests are assigned to the calculate node in cluster by formula.
6. the biological characteristic system for rapidly identifying according to claim 5 based on distributed computing, which is characterized in that described
Distributed management module is used to execute following steps:
S61, calculate node state the cluster name of oneself, and to system registry itself；
S62, system can inquire after receiving registration request into cluster-list, if having existed the cluster of same names, such as
Fruit does not have, then can establish a request queue for the cluster, and cluster-list is added in the cluster, otherwise automatically save the calculating
The request queue of cluster is added in point；
S63, when calculate node goes offline and when person actively leaves, system can be actively by the calculate node from corresponding cluster
It deletes.
7. the biological characteristic system for rapidly identifying according to claim 5 based on distributed computing, which is characterized in that described
The string type of distributed computing module is calculated for executing following steps:
S71, client send computation requests into the request queue of cluster；
S72, client monitor the calculated result from the queue to the response queue of one client of computing cluster application；
S73, computing cluster obtain waiting time longest computation requests from request queue, find out calculating section by polling algorithm
Computation requests are distributed to the calculate node by point；
S74, the calculate node chosen executes computation requests, and calculated result is returned to client by queue of receiveing the response.
8. the biological characteristic system for rapidly identifying according to claim 5 based on distributed computing, which is characterized in that described
The parallel type of distributed computing module is calculated for executing following steps:
S81, client send computation requests into the request queue of cluster；
The calculated result from the queue is monitored in S82, response of the client to one client of computing cluster application；
S83, computing cluster since request most computation requests, and the computation requests are distributed into all meters in cluster
Operator node；
S84, the calculate node all to cluster executes computation requests, and the calculated result of each node is passed through team of receiveing the response
Column return to client, for being focused to find out the node of matched user in biometric sample, then return to calculated result
Otherwise client then terminates to calculate, result of not going back on one's word.
9. the biological characteristic system for rapidly identifying according to claim 5 based on distributed computing, it is characterised in that:
The biometric sample library can be traditional file system, csv file format, structured database and non-structural
Change database.
10. -9 any biological characteristic system for rapidly identifying based on distributed computing, feature exist according to claim 1
In the biological characteristic includes but is not limited to:
Face, fingerprint, iris.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111130999A (en) * | 2019-12-23 | 2020-05-08 | 飞天诚信科技股份有限公司 | Method and bus adapter suitable for distributed message transmission |
| CN113792649A (en) * | 2021-09-13 | 2021-12-14 | 广州广电运通金融电子股份有限公司 | Rapid authentication method, device and medium based on finger vein biological identification technology |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101483524A (en) * | 2009-02-25 | 2009-07-15 | 李苏 | Distributed finger print recognition system for network and implementing method thereof |
| CN103118341A (en) * | 2013-01-04 | 2013-05-22 | 深圳市中兴移动通信有限公司 | Implementation method of distributed network schedule of mobile terminal and mobile terminal |
| CN103188245A (en) * | 2011-12-31 | 2013-07-03 | 上海火瀑云计算机终端科技有限公司 | Fight game server system |
| CN103379021A (en) * | 2012-04-24 | 2013-10-30 | 中兴通讯股份有限公司 | Method and system for achieving distributed message queue |
| CN103455633A (en) * | 2013-09-24 | 2013-12-18 | 浪潮齐鲁软件产业有限公司 | Method of distributed analysis for massive network detailed invoice data |
| CN103744734A (en) * | 2013-12-24 | 2014-04-23 | 中国科学院深圳先进技术研究院 | Method, device and system for task operation processing |
| CN104036557A (en) * | 2013-03-06 | 2014-09-10 | 中国科学技术大学苏州研究院 | B/S architecture based distributed face recognition attendance system and attendance checking method thereof |
| US20140330656A1 (en) * | 2011-07-18 | 2014-11-06 | Andrew H B Zhou | Mobile and wearable device payments via free cross-platform messaging service, free voice over internet protocol communication, free over-the-top content communication, and universal digital mobile and wearable device currency faces |
| CN105046303A (en) * | 2015-08-03 | 2015-11-11 | 深圳市科锐奇科技有限公司 | Distributed data interaction based biological identification method and system |
| CN105610987A (en) * | 2016-03-18 | 2016-05-25 | 车智互联（北京）科技有限公司 | Method, application and system for managing server cluster |
| CN106373288A (en) * | 2016-11-03 | 2017-02-01 | 深圳市亚略特生物识别科技有限公司 | Certificate handling self-service terminal |
| CN106484530A (en) * | 2016-09-05 | 2017-03-08 | 努比亚技术有限公司 | A kind of distributed task dispatching O＆M monitoring system and method |
| CN107666399A (en) * | 2016-07-28 | 2018-02-06 | 北京京东尚科信息技术有限公司 | A kind of method and apparatus of monitoring data |
| CN107770271A (en) * | 2017-10-20 | 2018-03-06 | 南方电网科学研究院有限责任公司 | Clustered machine people's cloud control method, device and system |
| CN108536532A (en) * | 2018-04-23 | 2018-09-14 | 中国农业银行股份有限公司 | A kind of batch tasks processing method and system |
-
2018
- 2018-10-09 CN CN201811172035.8A patent/CN109558789A/en active Pending
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101483524A (en) * | 2009-02-25 | 2009-07-15 | 李苏 | Distributed finger print recognition system for network and implementing method thereof |
| US20140330656A1 (en) * | 2011-07-18 | 2014-11-06 | Andrew H B Zhou | Mobile and wearable device payments via free cross-platform messaging service, free voice over internet protocol communication, free over-the-top content communication, and universal digital mobile and wearable device currency faces |
| US20140349692A1 (en) * | 2011-07-18 | 2014-11-27 | Andrew H B Zhou | Systems and methods for messaging, calling, digital multimedia capture and payment transactions |
| CN103188245A (en) * | 2011-12-31 | 2013-07-03 | 上海火瀑云计算机终端科技有限公司 | Fight game server system |
| CN103379021A (en) * | 2012-04-24 | 2013-10-30 | 中兴通讯股份有限公司 | Method and system for achieving distributed message queue |
| CN103118341A (en) * | 2013-01-04 | 2013-05-22 | 深圳市中兴移动通信有限公司 | Implementation method of distributed network schedule of mobile terminal and mobile terminal |
| CN104036557A (en) * | 2013-03-06 | 2014-09-10 | 中国科学技术大学苏州研究院 | B/S architecture based distributed face recognition attendance system and attendance checking method thereof |
| CN103455633A (en) * | 2013-09-24 | 2013-12-18 | 浪潮齐鲁软件产业有限公司 | Method of distributed analysis for massive network detailed invoice data |
| CN103744734A (en) * | 2013-12-24 | 2014-04-23 | 中国科学院深圳先进技术研究院 | Method, device and system for task operation processing |
| CN105046303A (en) * | 2015-08-03 | 2015-11-11 | 深圳市科锐奇科技有限公司 | Distributed data interaction based biological identification method and system |
| CN105610987A (en) * | 2016-03-18 | 2016-05-25 | 车智互联（北京）科技有限公司 | Method, application and system for managing server cluster |
| CN107666399A (en) * | 2016-07-28 | 2018-02-06 | 北京京东尚科信息技术有限公司 | A kind of method and apparatus of monitoring data |
| CN106484530A (en) * | 2016-09-05 | 2017-03-08 | 努比亚技术有限公司 | A kind of distributed task dispatching O＆M monitoring system and method |
| CN106373288A (en) * | 2016-11-03 | 2017-02-01 | 深圳市亚略特生物识别科技有限公司 | Certificate handling self-service terminal |
| CN107770271A (en) * | 2017-10-20 | 2018-03-06 | 南方电网科学研究院有限责任公司 | Clustered machine people's cloud control method, device and system |
| CN108536532A (en) * | 2018-04-23 | 2018-09-14 | 中国农业银行股份有限公司 | A kind of batch tasks processing method and system |
Non-Patent Citations (2)
| Title |
|---|
| BENFANO SOEWITO 等: "Smartphone for next generation attendance system and human resources payroll system", 《2017 4TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, COMPUTER SCIENCE AND INFORMATICS (EECSI)》 * |
| 王雅哲 等: "智能云电视公共安全服务平台建设", 《中国科学:信息科学》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111130999A (en) * | 2019-12-23 | 2020-05-08 | 飞天诚信科技股份有限公司 | Method and bus adapter suitable for distributed message transmission |
| CN111130999B (en) * | 2019-12-23 | 2021-08-31 | 飞天诚信科技股份有限公司 | Method and bus adapter suitable for distributed message transmission |
| CN113792649A (en) * | 2021-09-13 | 2021-12-14 | 广州广电运通金融电子股份有限公司 | Rapid authentication method, device and medium based on finger vein biological identification technology |
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