CN106790141A - New road traffic resource management information system based on cloud computing - Google Patents
New road traffic resource management information system based on cloud computing Download PDFInfo
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- CN106790141A CN106790141A CN201611235328.7A CN201611235328A CN106790141A CN 106790141 A CN106790141 A CN 106790141A CN 201611235328 A CN201611235328 A CN 201611235328A CN 106790141 A CN106790141 A CN 106790141A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/30—Network architectures or network communication protocols for network security for supporting lawful interception, monitoring or retaining of communications or communication related information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Abstract
The present invention relates to traffic management technology field,Specifically a kind of new road traffic resource management information system based on cloud computing,It is characterized in that being provided with Cloud Server,Remote-control platform,Database,More than two monitor node terminals,Wherein remote-control platform and database are connected with Cloud Server respectively,The remote-control platform is connected in more than two monitor node terminals,The Cloud Server is provided with the distribution for computing resource in Control management system and will calculate management of computing module of the data forwarding to each monitor node terminal by network,Network management unit and data reduction processing module for every configuration in access to communication networks control system connection network is of the invention compared with prior art,The existing software and hardware resources of transportation industry can be integrated so as to form resource pool,Realize dynamically distributes and the release of resource,Improve resource utilization,Simultaneously by the monitoring to malicious access and treatment in time,Ensure the safe handling of whole system.
Description
Technical field：
The present invention relates to traffic management technology field, specifically a kind of new road traffic resource based on cloud computing
Management information system.
Background technology：
With information-based fast development, cloud computing is more and more concerned, either internet manufacturer and operator, also
It is communication manufacturer and basic network operator, greatly concern is all shown to cloud computing.Under cloud computing scene, substantial amounts of use
Family information all concentrates on cloud computing provider, and compared with traditional Internet service, its information is more concentrated, information assets is worth more
Attack that is high, facing also can be more.The security solution of cloud computing needs the differentiation demand for security according to different business, carries
For security solution.And the security solution traditionally formulated for single business, it is impossible to adapt to cloud computing platform high
The shared characteristic of degree, accordingly, it would be desirable to cloud computing is innovated safely in system-level architecture, it is full to adapt to the new features of platform
The personalized secure demand of all business on sufficient platform.The prospect of cloud computing is unquestionable, but in actually used process
In inevitably face some extreme conditions.For example：Mobile terminal cannot be linked into network, the meeting that unstable networks are caused
Words terminate suddenly and cause the loss of user data and information, network condition difference residing for user and cause jam brighter
Aobvious, hacker kidnaps session attack cloud center etc..
How therein, thing is lain in from substantial amounts of, incomplete, noisy, fuzzy, random extracting data
First the process of ignorant but potentially useful sometimes information is referred to as data mining, it is therefore apparent that big data during data mining
The key of technology.Network redundancy deleting technique is subject to the extensive of academia and industrial quarters as a kind of new Web compression technology
Concern, its major function is to recognize the data repeatedly transmitted in network, greatly reduces transmitted data on network amount, improves Netowrk tape
Utilization rate wide, so as to improve application performance and save operation cost.
Still realized using the serial mode on single machine node during existing big data system processes data, its data processing amount
And the degree of load of algorithm depends on the performance of single execution node, and because big data processing system often will be to mass data
Processed, the existing serial mechanism of single machine node there will naturally be the problem that efficiency is low, operand is low.
The content of the invention：
The present invention is for shortcoming and defect present in prior art, it is proposed that a kind of new road based on cloud computing is handed over
Logical resource management information system.
The present invention can be reached by following measures：
A kind of new road traffic resource management information system based on cloud computing, it is characterised in that be provided with Cloud Server,
Remote-control platform, database, more than two monitor node terminals, wherein remote-control platform and database take with cloud respectively
Business device is connected, and the remote-control platform is connected in more than two monitor node terminals, and the Cloud Server is provided with for controlling
In management system processed the distribution of computing resource and by network will calculate data forwarding to each monitor node terminal computer tube
At reason module, the network management unit configured for items in access to communication networks control system connection network and data reduction
Reason module.
Data reduction module of the present invention carries out following treatment to data：In the byte sequence of data content to be calculated
Determine length of window；Determine the window number of parallel computation and redirect interval；It is each according to counted window fingerprint value parallel computation
The fingerprint value of window, wherein the calculation of the window fingerprint value is：RF(α1、α2、α3……αβ)=(α1pβ+α2pβ‐1+…+
αβ‐1p+αβ)modM；Wherein α1、α2、α3……αβIt is the byte sequence in data content to be calculated, RF (α1、α2、α3……αβ) table
Show the fingerprint value of the byte sequence that length of window is β, p and M is optional constant；Counted window fingerprint value has been simultaneously for the basis
The fingerprint value that row calculates each window is calculated by following formula：RF(αi+1、αi+2、αi+3……αi+β)=(RF (αi、αi+1、αi+2……
αi+β‐1)‐αi×pβ)×p+αi+βmodM；Wherein αi+1、αi+2、αi+3……αi+βIt is the byte sequence in data content to be calculated,
RF(αi、αi+1、αi+2……αi+β‐1) representing that length of window is the fingerprint value of the byte sequence of β, p and M is optional constant；Mark
The window's position that window fingerprint value meets predetermined deblocking boundary condition is deblocking border, wherein, window fingerprint value
Meet predetermined deblocking condition, then the right margin position of current sliding window mouthful is labeled as the border of deblocking；
Calculate the hashed value of deblocking, and the hashed value of flag data piecemeal it is equal with the deblocking hashed value for having stored for superfluous
Remaining data block.
Heretofore described window fingerprint value is calculated by Rabin's fingerprint function；It is described to redirect at intervals of the parallel computation
The integral multiple of window number；It is described to redirect the integral multiple that interval is not the window number of the parallel computation；It is described to redirect weight in interval
The folded window fingerprint value for calculating is used to verify；The window of the parallel computation be located at it is same redirect interval in；The parallel computation
Window positioned at difference redirect interval in；Substituting data of the mark as block with hashed value and reference information is carried out
The storage of the data block.
Remote-control platform of the present invention is provided with data reception module, data processing module and data outputting module, institute
Stating data processing module includes road condition discrimination module, and the road condition discrimination module divides mould automatically including road subsection
Block, road traffic parameter real-time reception module, road traffic state real-time identification module and identification result output module,
The automatic division module of road subsection and road traffic parameter in the present invention in road condition discrimination module connect in real time
Receive input of the output end of module with road traffic state real-time identification module to be connected, road traffic state real-time identification
The output end of module is connected with identification result output module.
The automatic division module of road subsection of the present invention is used to for a road to be divided into two subsegments U1 and U2 automatically, its length
Degree is expressed as dU1 and dU2, dU1 and the division of dU2 depends on that parameter includes entire road lengthFront signal light split t,
Highway layout saturation factor s,Represent that road limitation speed, a are the control parameters related to road overall length, b is to limit speed with road
Related control parameter is spent, is specifically divided according to equation below：
Road traffic state real-time identification module of the present invention completes traffic behavior real-time identification by following steps：It is right
Each road subsection sets up evaluation object single factor test collection Ui；Evaluation collection F is set up for each road subsectioni；Set up from single factor test collection
UiTo evaluation collection FiThe mapping of a fuzzy relation, single factor test evaluation matrix R is derived by Cartesian product corresponding relationi；The first order
Fuzzy Synthetic Evaluation, selection segmentation Gaussian Blur mathematical synthesis function is carried out comprehensive and is made normalized；Two grades obscure
Comprehensive Assessment；Fuzzy analysis judgement is carried out to two grades of result of determination, the result that urban road state is distinguished is drawn.
The present invention compared with prior art, can integrate the existing software and hardware resources of transportation industry so as to form resource pool,
Dynamically distributes and the release of resource are realized, resource utilization is improved, is that each traffic subsystem is carried using the versatility of cloud service
For support, while by the monitoring to malicious access and treatment in time, it is ensured that the safe handling of whole system.
Brief description of the drawings：
Accompanying drawing 1 is structured flowchart of the invention.
Accompanying drawing 2 is the structured flowchart at management and control center in the present invention.
Reference：Cloud Server 1, remote-control platform 2, database 3, monitor node terminal 4, management of computing module 5,
Network management unit 6, data reception module 7, data processing module 8, data outputting module 9, data reduction processing module 10.
Specific embodiment：
The present invention is further illustrated below in conjunction with the accompanying drawings.
As shown in drawings, the present invention proposes the new road traffic resource management information system based on cloud computing, and it is special
Levy is to be provided with Cloud Server 1, remote-control platform 2, database 3, more than two monitor node terminals 4, its medium-long range pipe
Control platform 2 and database 3 are connected with Cloud Server 1 respectively, and the remote-control platform 2 is in more than two monitor node terminals
4 connections, the Cloud Server 1 is provided with the distribution for computing resource in Control management system and will calculate data by network and turns
It is sent to the management of computing module 5 of each monitor node terminal, matches somebody with somebody for items in access to communication networks control system connection network
The network management unit 6 and data reduction processing module 10 put.
Data reduction module of the present invention carries out following treatment to data：In the byte sequence of data content to be calculated
Determine length of window；Determine the window number of parallel computation and redirect interval；It is each according to counted window fingerprint value parallel computation
The fingerprint value of window, wherein the calculation of the window fingerprint value is：RF(α1、α2、α3……αβ)=(α1pβ+α2pβ‐1+…+
αβ‐1p+αβ)modM；Wherein α1、α2、α3……αβIt is the byte sequence in data content to be calculated, RF (α1、α2、α3……αβ) table
Show the fingerprint value of the byte sequence that length of window is β, p and M is optional constant；Counted window fingerprint value has been simultaneously for the basis
The fingerprint value that row calculates each window is calculated by following formula：RF(αi+1、αi+2、αi+3……αi+β)=(RF (αi、αi+1、αi+2……
αi+β‐1)‐αi×pβ)×p+αi+βmodM；Wherein αi+1、αi+2、αi+3……αi+βIt is the byte sequence in data content to be calculated,
RF(αi、αi+1、αi+2……αi+β‐1) representing that length of window is the fingerprint value of the byte sequence of β, p and M is optional constant；Mark
The window's position that window fingerprint value meets predetermined deblocking boundary condition is deblocking border, wherein, window fingerprint value
Meet predetermined deblocking condition, then the right margin position of current sliding window mouthful is labeled as the border of deblocking；
Calculate the hashed value of deblocking, and the hashed value of flag data piecemeal it is equal with the deblocking hashed value for having stored for superfluous
Remaining data block.
Heretofore described window fingerprint value is calculated by Rabin's fingerprint function；It is described to redirect at intervals of the parallel computation
The integral multiple of window number；It is described to redirect the integral multiple that interval is not the window number of the parallel computation；It is described to redirect weight in interval
The folded window fingerprint value for calculating is used to verify；The window of the parallel computation be located at it is same redirect interval in；The parallel computation
Window positioned at difference redirect interval in；Substituting data of the mark as block with hashed value and reference information is carried out
The storage of the data block.
Remote-control platform 2 of the present invention is provided with data reception module 7, data processing module 8 and data outputting module
9, the data processing module 8 includes road condition discrimination module, and the road condition discrimination module includes that road subsection is automatic
Division module, road traffic parameter real-time reception module, road traffic state real-time identification module and identification result output mould
Block,
The automatic division module of road subsection and road traffic parameter in the present invention in road condition discrimination module connect in real time
Receive input of the output end of module with road traffic state real-time identification module to be connected, road traffic state real-time identification
The output end of module is connected with identification result output module.
The automatic division module of road subsection of the present invention is used to for a road to be divided into two subsegments U1 and U2 automatically, its length
Degree is expressed as dU1 and dU2, dU1 and the division of dU2 depends on that parameter includes entire road lengthFront signal light split t,
Highway layout saturation factor s,Represent that road limitation speed, a are the control parameters related to road overall length, b is to limit speed with road
Related control parameter is spent, is specifically divided according to equation below：
Road traffic state real-time identification module of the present invention completes traffic behavior real-time identification by following steps：It is right
Each road subsection sets up evaluation object single factor test collection Ui；Evaluation collection F is set up for each road subsectioni；Set up from single factor test collection
UiTo evaluation collection FiThe mapping of a fuzzy relation, single factor test evaluation matrix R is derived by Cartesian product corresponding relationi；The first order
Fuzzy Synthetic Evaluation, selection segmentation Gaussian Blur mathematical synthesis function is carried out comprehensive and is made normalized；Two grades obscure
Comprehensive Assessment；Fuzzy analysis judgement is carried out to two grades of result of determination, the result that urban road state is distinguished is drawn.
The present invention compared with prior art, can integrate the existing software and hardware resources of transportation industry so as to form resource pool,
Dynamically distributes and the release of resource are realized, resource utilization is improved, is that each traffic subsystem is carried using the versatility of cloud service
For support, while by the monitoring to malicious access and treatment in time, it is ensured that the safe handling of whole system.
Claims (7)
1. a kind of new road traffic resource management information system based on cloud computing, it is characterised in that be provided with Cloud Server, remote
Journey control platform, database, more than two monitor node terminals, wherein remote-control platform and database respectively with cloud service
Device is connected, and the remote-control platform is connected in more than two monitor node terminals, and the Cloud Server is provided with for controlling
In management system the distribution of computing resource and by network will calculate data forwarding to each monitor node terminal management of computing
Module, the network management unit for every configuration in access to communication networks control system connection network and data reduction treatment
Module.
2. a kind of new road traffic resource management information system based on cloud computing according to claim 1, its feature
It is that the data reduction module carries out following treatment to data：Determine that window is long in the byte sequence of data content to be calculated
Degree；Determine the window number of parallel computation and redirect interval；According to the fingerprint of counted each window of window fingerprint value parallel computation
Value, wherein the calculation of the window fingerprint value is：RF(α1、α2、α3……αβ)=(α1pβ+α2pβ‐1+…+αβ‐1p+αβ)
modM；Wherein α1、α2、α3……αβIt is the byte sequence in data content to be calculated, RF (α1、α2、α3……αβ) represent that window is long
The fingerprint value of the byte sequence for β is spent, p and M is optional constant；Counted window fingerprint value parallel computation is each for the basis
The fingerprint value of window is calculated by following formula：RF(αi+1、αi+2、αi+3……αi+β)=(RF (αi、αi+1、αi+2……αi+β‐1)‐αi×pβ)
×p+αi+βmodM；Wherein αi+1、αi+2、αi+3……αi+βIt is the byte sequence in data content to be calculated, RF (αi、αi+1、
αi+2……αi+β‐1) representing that length of window is the fingerprint value of the byte sequence of β, p and M is optional constant；Mark window fingerprint value
Meet the window's position of predetermined deblocking boundary condition for deblocking border, wherein, window fingerprint value meets predetermined
Deblocking condition, then the right margin position of current sliding window mouthful is labeled as the border of deblocking；Calculate data point
The hashed value of block, and the hashed value of flag data piecemeal it is equal with the deblocking hashed value for having stored be redundant data block.
3. a kind of new road traffic resource management information system based on cloud computing according to claim 1, its feature
It is that the window fingerprint value is calculated by Rabin's fingerprint function；The integer for redirecting the window number at intervals of the parallel computation
Times；It is described to redirect the integral multiple that interval is not the window number of the parallel computation；The window for redirecting overlapping calculation in interval
Fingerprint value is used to verify；The window of the parallel computation be located at it is same redirect interval in；The window of the parallel computation is located at not
Redirect together in being spaced；Substituting data of the mark as block with hashed value and reference information carries out the data block
Storage.
4. a kind of new road traffic resource management information system based on cloud computing according to claim 1, its feature
It is that the remote-control platform is provided with data reception module, data processing module and data outputting module, the data processing
Module includes road condition discrimination module, and the road condition discrimination module includes that the automatic division module of road subsection, road are handed over
Logical parameter real-time reception module, road traffic state real-time identification module and identification result output module.
5. a kind of new road traffic resource management information system based on cloud computing according to claim 1, its feature
It is the output of the automatic division module of road subsection and road traffic parameter real-time reception module in road condition discrimination module
The input with road traffic state real-time identification module is held to be connected, the output end of road traffic state real-time identification module
It is connected with identification result output module.
6. a kind of new road traffic resource management information system based on cloud computing according to claim 1, its feature
It is that the automatic division module of road subsection is used to for a road to be divided into two subsegments U1 and U2 automatically, its length is expressed as
The division of dU1 and dU2, dU1 and dU2 depends on that parameter includes entire road lengthFront signal light split t, highway layout
Saturation factor s,Represent that road limitation speed, a are the control parameters related to road overall length, b is to limit velocity correlation with road
Control parameter, specifically divides according to equation below：
7. a kind of new road traffic resource management information system based on cloud computing according to claim 1, its feature
It is that the road traffic state real-time identification module completes traffic behavior real-time identification by following steps：To each road way
Duan Jianli evaluation object single factor test collection Ui；Evaluation collection F is set up for each road subsectioni；Set up from single factor test collection UiCollect to evaluation
FiThe mapping of a fuzzy relation, single factor test evaluation matrix R is derived by Cartesian product corresponding relationi；First order fuzzy synthesis are commented
Fixed, selection segmentation Gaussian Blur mathematical synthesis function is carried out comprehensive and is made normalized；Two-stage Fuzzy Comprehensive Evaluation；It is right
Two grades of result of determination carry out fuzzy analysis judgement, draw the result that urban road state is distinguished.
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| CN101778741A (en) * | 2007-07-24 | 2010-07-14 | 日产自动车株式会社 | Drive assistance system and method for vehicle and vehicle equipped with the system |
| CN102402858A (en) * | 2011-10-25 | 2012-04-04 | 深圳市华盈泰科技有限公司 | Vehicle electronic identity recognition information network system |
| CN102708688A (en) * | 2012-06-08 | 2012-10-03 | 四川川大智胜软件股份有限公司 | Secondary fuzzy comprehensive discrimination-based urban road condition recognition method |
| CN103078709A (en) * | 2013-01-05 | 2013-05-01 | 中国科学院深圳先进技术研究院 | Data redundancy identifying method |
-
2016
- 2016-12-28 CN CN201611235328.7A patent/CN106790141A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101778741A (en) * | 2007-07-24 | 2010-07-14 | 日产自动车株式会社 | Drive assistance system and method for vehicle and vehicle equipped with the system |
| CN102402858A (en) * | 2011-10-25 | 2012-04-04 | 深圳市华盈泰科技有限公司 | Vehicle electronic identity recognition information network system |
| CN102708688A (en) * | 2012-06-08 | 2012-10-03 | 四川川大智胜软件股份有限公司 | Secondary fuzzy comprehensive discrimination-based urban road condition recognition method |
| CN103078709A (en) * | 2013-01-05 | 2013-05-01 | 中国科学院深圳先进技术研究院 | Data redundancy identifying method |
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Application publication date: 20170531 |