CN104618693A - Cloud computing based online processing task management method and system for monitoring video - Google Patents
Cloud computing based online processing task management method and system for monitoring video Download PDFInfo
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Abstract
The invention discloses a cloud computing based online processing task management system for monitoring video. The system is respectively connected with a client and a front end camera and comprises an intelligent video analyzing algorithm management module, a cloud resource management module, a cloud computing physical resource model and a virtual intelligent video analyzing server. The invention further discloses a cloud computing based online processing task management method for monitoring video. According to the method and system, a group of interconnected server groups in a data center is unified to be managed by the cloud computing technology, and the server groups coordinate to provide a user the intelligent monitoring video online processing task management service; the system is high in telescopic performance; the intelligent video analyzing algorithm can be dynamically configured as requirement, thus the management is convenient, and the cost is greatly reduced; in addition, the video processing task provided by the user can be reasonably dispatched to enable balanced load of the computing groups, and therefore, the resource utilization rate is increased, and efficient cloud computing service is provided to the user.
Description
Technical field
The application relates to intelligent video monitoring and field of cloud calculation, be specifically related to the online Processing tasks management system of on-line intelligence monitor video, cloud resource management system, cloud resource regulating method, particularly relate to the online Processing tasks management method of a kind of monitor video based on cloud computing and system.
Background technology
Along with the develop rapidly of computer technology, network technology and multimedia technology, video monitoring system develops into IP-based network video monitor and control system from traditional analog video supervisory control system.The continuous acceleration of adjoint China's modernization construction level and economic development, the construction of large scale community public security network video monitor and control system is risen to the strategic height making " safe city " by each city one after another, and this just proposes requirement to building technical standard unification, network interconnection intercommunication, the city-level of information resources share or provincial monitor network.
The scale of video monitoring system sharply expands, but do not have enough manpowers to monitor, be difficult to ensure multizone, for a long time monitoring in real time, be difficult to process magnanimity real-time video information in time, therefore time in the urgent need to possessing network implementation, the supervisory control system of intelligent video analysis is extracted key video sequence information, carries out early warning to abnormal monitoring scene event.On the other hand, traditional centralized monitoring video processing service device can not adapt to the demand of HD video to network traffics, has had a strong impact on the operating efficiency of on-line intelligence monitor video treatment system.In addition, in traditional intelligent video monitoring system, intelligent video analysis algorithm is integrated in the embedded chip of video analytics server or camera usually, provides the parser of fixed type, and user cannot customized task according to demand.When user needs to use new video analysis algorithm, system upgrade or extended capability, need buy video analytics server in addition or change camera, cost is very high, is not easy to system management.Make Single-Server obtain stronger computing capability to be realized by the mode increasing processor number and other member velocity, but the restriction of the aspect such as Computer Architecture and dominant frequency can be subject to, also can run into that high-performance server is expensive, poor expandability and fundamentally cannot solve Single Point of Faliure and the problem such as server resource is not enough.
The current demand end of above each side is got up, and needs a kind of efficient, flexible, stable, low cost, the convenient magnanimity monitor video data processing scheme managed.
Summary of the invention
This application provides the online Processing tasks management method of a kind of monitor video based on cloud computing and system, efficient, flexible, stable, low cost, the convenient magnanimity monitor video data processing managed can be realized.
The embodiment of the present application provides the online Processing tasks management system of a kind of monitor video based on cloud computing, the online Processing tasks management system of described monitor video connects client and front-end camera respectively, and the online Processing tasks management system of this monitor video comprises: intelligent video analysis algorithm management module, cloud resource management module, cloud computing physical resource module and Virtual Intelligent video analytics server;
Described intelligent video analysis algorithm management module is used for the video analytic tasks of administrative client, the relevant information of preservation and managing virtual intelligent video analysis server, monitor the running status of Virtual Intelligent video analytics server, in virtual computing server deploy, start Virtual Intelligent video analytics server; Send resource bid to cloud computing physical resource module and cancel request;
Described cloud resource management module for dynamically creating Virtual Intelligent video analytics server, delete, check operation as required in cloud computing physical resource module;
Cloud computing physical resource module is used for deployment server virtualized environment, possesses the cloud computing physical resource of generating virtual intelligent video analysis server;
Virtual Intelligent video analytics server, be created on cloud computing physical resource that cloud computing physical resource module provides, each Virtual Intelligent video analytics server comprises one or more video analysis algorithms, for receiving and the video flowing of CCTV camera transmission of decoding, be responsible for carrying out online analysis to monitoring video flow, then the result of video analysis sent to client.
The embodiment of the present application additionally provides the online Processing tasks management method of a kind of monitor video based on cloud computing, comprises the steps:
In the task requests stage: client sends monitor video online Processing tasks request Q={C to intelligent video analysis algorithm management module, then J, T} wait for the task deployment result of intelligent video analysis algorithm management module; Wherein, C={c1, c2 ..., cn} is camera set, J={j1, j2 ..., j3} is video analysis algorithm set, and T=[t1, t2] is task execution time section;
The task deployment stage: after intelligent video analysis algorithm management module receives task requests Q, judge: if there is no to meet the Virtual Intelligent video analytics server of task requests Q in current cloud computing physical resource module, the virtual computing server meeting the configuration of task requests Q resource requirement is then dynamically generated by cloud resource management module, then required intelligent video analysis algorithm application mirror image is deployed to virtual computing server, thus generate the Virtual Intelligent video analytics server meeting mission requirements, start Virtual Intelligent video analytics server and perform video analytic tasks, and Virtual Intelligent video analytics server relevant information is returned to client, if there is the Virtual Intelligent video analytics server that can meet task requests Q in current cloud computing physical resource module, then dispatch Virtual Intelligent video analytics server adaptively according to the loading condition of Virtual Intelligent video analytics server cluster, start Virtual Intelligent video analytics server and perform video analytic tasks, and corresponding Virtual Intelligent video analytics server cluster information is returned to client,
The processing stage of task: after client receives the Virtual Intelligent video analytics server information that intelligent video analysis algorithm management module returns, can monitor and receive the video analysis result that Virtual Intelligent video analytics server returns.Virtual Intelligent video analytics server obtains and decoding standard monitoring video flow from front-end camera, calls the video analysis algorithm of J demand, carries out on-line analysis, and analysis result is returned to client to video flowing.
As can be seen from the above technical solutions, adopt cloud computing technology that the server cluster interconnected in one group of data center is carried out unified management, collaborate provides intelligent monitoring video online Processing tasks management service for user, system is made to have good retractility, can dynamic-configuration intelligent video analysis algorithm as required, be convenient to management, also greatly reduce cost.In addition, the application's scheme can carry out rational management to the video processing duties that user submits to, makes computing cluster load balancing, improves resource utilization, provide efficient cloud computing service to user.
Accompanying drawing explanation
Fig. 1 is the online Processing tasks of the monitor video based on the cloud computing management system structure chart that the embodiment of the present application provides.
Fig. 2 is the operating process schematic diagram of the IVAM scheduling intelligent video analysis task that the embodiment of the present application provides;
The IVAM that Fig. 3 provides for the embodiment of the present application dispatches in intelligent video analysis task, the concrete handling process schematic diagram in task requests stage;
The IVAM that Fig. 4 provides for the embodiment of the present application dispatches in intelligent video analysis task, the concrete handling process schematic diagram in task deployment stage;
Fig. 5 is for step 404 in flow process shown in Fig. 4 is to the concrete processing procedure schematic diagram of step 405;
The concrete processing procedure schematic diagram that Fig. 6 is step 403 in flow process shown in Fig. 4;
The IVAM that Fig. 7 provides for the embodiment of the present application dispatches in intelligent video analysis task, the concrete handling process schematic diagram processing stage of task;
The IVAM that Fig. 8 provides for the embodiment of the present application dispatches in intelligent video analysis task, task ending phase when the time period T cut-off required in task Q, then its service interaction schematic flow sheet;
The IVAM that Fig. 9 provides for the embodiment of the present application dispatches in intelligent video analysis task, task ending phase when CS to IVAM send cancel VIVU ask time, then its service interaction schematic flow sheet.
Embodiment
The object of the application is to provide the online Processing tasks management method of a kind of monitor video based on cloud computing and system, make full use of distributed structure/architecture design and the expandability of cloud computing, and support extensive monitor video on-line analysis function, by setting up intelligent video analysis algorithm management functional module (IVAM) and cloud video analysis cluster (CVAC), form the call capability as required of intelligent video analysis algorithm, meet the flexible and varied intellectual analysis demand of client, thus the dynamic expanding of monitoring scale can be realized, possesses more perfect function, obtain the systematic function of more high efficient and reliable, there is higher cost performance simultaneously.Its fundamental design idea is: carry out unified management and scheduling based on the physical compute server cluster of cloud computing technology to data center, when there being the online Processing tasks request of monitor video, according to the resource situation of required by task with the loading condition of current server cluster dynamically generates, configuration virtual video analysis computational resource, provide video analysis service as required to user.
Cloud computing is a kind of emerging computation schema, is the one of distributed computing technology, mainly by a large amount of computational resource unified management of connecting with network and scheduling, forms a computational resource pond to user's on-demand service.User obtains resource requirement and service by network in the mode as required, easily expanded, and the computer in network, server externally provide service jointly, and make it transparence.
For making the know-why of technical scheme, feature and technique effect clearly, below in conjunction with specific embodiment, technical scheme is described in detail.
As shown in Figure 1, this system comprises the structure of the online Processing tasks of the monitor video based on cloud computing management system (hereinafter referred to as system) that the embodiment of the present application provides: intelligent video analysis algorithm management module (IVAM) 102, cloud resource management module (CRMU) 103, cloud computing physical resource module (CPR) 104 and Virtual Intelligent video analytics server (VIVU) 105.In addition, during this system worked well, also need and client (CS) 101) and front-end camera (PU) 106 possess and be connected.Various piece in Fig. 1 is described as follows:
Client (CS) 101: nonsystematic nucleus module, being made up of one or more computer is the requestor of the online Processing tasks of monitor video, is also the recipient of video analysis result.Intelligent video analysis task can be submitted to the online Processing tasks management system of monitor video, obtain intellectual analysis result data from VIVU 105, usually can store and show video analysis result.When no longer needing to analyze monitor video, also intelligent video analysis task can be cancelled to the online Processing tasks management system of monitor video.
Intelligent video analysis algorithm management module (IVAM) 102: belong to system core functional module, be made up of a server, it is the request response inlet module of the online Processing tasks management system of monitor video, be supplied to the system access mode of CS 101, there is provided two kinds of system access modes: one is present with the form of Web page, user can pass through the online Processing tasks management system of management of webpage monitor video; Two is make CS 101 can the service that provides of the online Processing tasks management system of usage monitoring video in the mode of Web service interface.The interface that CS 101 is exposed by service carries out task customization and submission.When CS 101 no longer needs VIVU 105, computational resource can be initiated to IVAM 102 and cancel request.
According to another embodiment of the application, intelligent video analysis algorithm management module (IVAM) 102 comprises following functional unit further:
Intelligent video analysis algorithm management unit: for storing multiple intelligent video analysis algorithm mirror image, user can add video analysis algorithm mirror image, delete, the bookkeeping such as to search;
Intelligent video analysis role management unit: for managing the video analytic tasks of CS, comprise monitor and response task requests, preservation and management role information, control task implementation etc.;
VIVU administrative unit: the relevant information preserving and manage VIVU, monitors the running status of VIVU, in addition, can send the application of virtual computing server resource to CRMU and cancel request, and can at virtual computing server deploy, startup VIVU;
System task scheduling unit: for the running status according to current VIVU cluster, adaptively intelligent video analysis task scheduling is carried out video analysis to corresponding VIVU;
Authentication management unit: for managing the identity information of CS, the identity of CS is verified, and can the behavior of control CS.
Cloud resource management module (CRMU) 103: belong to system core functional module, be made up of a server, it is the request response inlet module of cloud computing basic resource, be responsible for the CPR 104 at integral data center, the isomerism of shielding infrastructure resources and dynamic, for system provides easily flexible, friendly, transparent data center's infrastructure management service.
According to another embodiment of the application, described cloud resource management module 103 comprises following functional unit:
Cloud Host Administration unit: bookkeepings such as dynamically can creating Virtual Intelligent video analytics server Virtual Intelligent video analytics server as required, delete, check, support the mainstream operation systems such as Windows, Linux, BSD, can remote activation, close, restart, log in Virtual Intelligent video analytics server Virtual Intelligent video analytics server, and thermophoresis can be carried out to Virtual Intelligent video analytics server Virtual Intelligent video analytics server;
Mirror image administrative unit: can create, delete and inquire about image file, realizes the rapid configuration of software environment and the rapid deployment of business;
Cloud Host Status monitoring unit: the running status of Monitoring Data center cloud main frame in real time, collects, preserves and the state values such as the CPU of graphical representation cloud main frame, internal memory, hard disk and network I/O;
Authentication management unit: the identity information of leading subscriber, can verify the identity of user, and can control the behavior of user.
Cloud computing physical resource module (CPR) 104: data center's physical compute server cluster, carries out unified management by CRMU, deploys server virtualization environment, can generating virtual calculation server thereon.
Virtual Intelligent video analytics server (VIVU) 105: belong to system core functional module, after applying for virtual computing server resource by IVAM 102 to CRMU 103, the virtual computing server that physical resource CPR 104 creates, then IVAM 102 is deployed to video analysis algorithm application mirror image on the virtual computing server of establishment, thus generates VIVU 105.Each VIVU 105 comprises one or more video analysis algorithms, can receive and the video flowing of CCTV camera PU 106 transmission of decoding, be responsible for carrying out online analysis to monitoring video flow, then the result of video analysis is sent to CS 101.Meanwhile, VIVU 105 periodically reports oneself running status, comprises CPU, internal memory, hard disk and network I/O state value.
Front-end camera (PU) 106: be made up of multiple web camera, is arranged in guarded region, is responsible for acquisition monitoring video flowing, encodes to video flowing, and monitor video can be flowed through IP network and transmit.
When client 101 front end CCTV camera video flowing carries out analyzing of task, intelligent video analysis algorithm management module (IVAM) 102 applies for virtual resource according to the resource requirement situation of video analytic tasks to cloud video analysis cluster (CVAC), and generate corresponding Virtual Intelligent video analytics server (VIVU), Virtual Intelligent video analytics server receives the video data sent by front end CCTV camera, system can according to the difference between each task, determine the key factor of influential system performance, according to the occupation condition of video analytic tasks feature and each Virtual Intelligent video analytics server, determine the server node distributing to each task, make Virtual Intelligent video analytics server cluster load balance, resource utilization is high, improve system task execution efficiency, simultaneously can unified management intelligent video analysis server efficiently, effectively meet consumers' demand.
The online Processing tasks of the monitor video based on the cloud computing management method that the application provides as shown in Figure 2, comprises following operative step:
Step 201: task requests stage: CS sends monitor video online Processing tasks request Q to IVAM, then waits for the task deployment result of IVAM.
Step 202: task deployment stage: after IVAM receives task requests Q, judge: if there is no to meet the VIVU of task requests Q in current C PR, the virtual computing server meeting the configuration of task requests Q resource requirement is then dynamically generated by CRMU, then required intelligent video analysis algorithm application mirror image is deployed to virtual computing server, thus generate the VIVU meeting mission requirements, start VIVU and perform video analytic tasks, and VIVU relevant information is returned to CS; If have the VIVU that can meet task requests Q in current C PR, then dispatch VIVU adaptively according to the loading condition of VIVU cluster, start VIVU and perform video analytic tasks, and corresponding VIVU cluster information is returned to CS.
When IVAM sends computational resource application to CRMU, CRMU, according to the loading condition of present physical basic resource CPR, CPR generates the virtual computing server of respective resources configuration, and the relevant information of virtual computing server is returned to IVAM.Cancel request when IVAM sends computational resource to CRMU, CRMU deletes corresponding virtual computing server on CPR.
After step 203: the processing stage of task: CS receives the VIVU information that returns of IVAM, can monitor and receive the video analysis result that VIVU returns.VIVU obtains and decoding standard monitoring video flow from PU, calls the video analysis algorithm of J demand, carries out on-line analysis, and analysis result is returned to CS to video flowing.
Step 204: task ending phase: at the end of task, when the time period T namely required in task Q ends, IVAM stops the video analysis work of VIVU; Or when CS to IVAM send cancel VIVU request time, IVAM sends computational resource to CRMU and cancels request, then CRMU shared by corresponding VIVU computational resource regain.
Wherein, the concrete processing procedure in task requests stage as shown in Figure 3, comprises the steps:
Step 301:CS signs in IVAM, and IVAM carries out authentication to CS;
Step 302:CS sends monitor video online Processing tasks request Q={C to IVAM, J, T} (wherein C={c1, c2,, cn} is camera set, J={j1, j2,, j3} is video analysis algorithm set, T=[t1, t2] be task execution time section), then wait for the task deployment result of IVAM.
As shown in Figure 4, this stage comprises following maneuvering sequence to the handling process in task deployment stage:
Step 401:IVAM receives task requests Q.
Step 402: judge whether to exist the VIVU cluster meeting task requests Q, if so, performs step 403, otherwise performs step 404.
Step 403: according to VIVU cluster load dispatch VIVU, then performs step 406.
Step 404: apply for virtual machine to CRMU.
Step 405: Deployment Algorithm generates VIVU on a virtual machine.
Step 406: start VIVU cluster and perform video analytic tasks.
Step 407: VIVU cluster information is returned to CS.
If do not have the VIVU that can meet task requests Q in current C PR, then its service interaction idiographic flow (step 404 in corresponding diagram 4 is to step 405) as shown in Figure 5, comprises the steps:
Step 501:IVAM signs in CRMU, and the identity of CRMU to IVAM is verified;
Step 502:IVAM sends the request of generating virtual machines to CRMU, dynamically generates the virtual computing server meeting the configuration of task requests Q resource requirement;
Step 503::CRMU is according to the loading condition of present physical basic resource CPR, the physical server set subCPR in dispatching algorithm selection CPR is filtered based on BFilter, virtual machine image is issued on the subCPR of selection, subCPR generates the virtual computing server cluster of respective resources configuration;
BFilter filters dispatching algorithm: the disposal ability arranging each virtual computing server is identical, and minimum energy parallel processing Nk video analytic tasks, therefore need to create Ncpr=Nc*Nj/Nk virtual server (wherein Nc is the number of camera in C, and Nj is the number of task in J).For each virtual computing server of establishment, first obtain the physical server virtual computation environmental state in all CPR, then (such as needs 4G internal memory is filtered out to the physical server not meeting Q resource requirement, directly filter out less than 4G internal memory), then remaining to all filtrations physical server carries out weights scoring, and (such as free memory is larger, mark higher), finally extract the highest some main frames (being defaulted as 5) of scoring, Stochastic choice one alternatively virtual computing server from these some physical servers.
Step 504:CRMU returns to IVAM the information of virtual computing server cluster;
Step 505:IVAM is deployed to the intelligent video analysis algorithm application mirror image required by Q on virtual computing server cluster, thus generates the VIVU cluster meeting mission requirements;
Step 506:VIVU cluster reports IVAM the running status of oneself (comprise and whether normally running, performing video analytic tasks situation, the state values such as CPU, internal memory, hard disk, network I/O);
Step 507:IVAM sends task execution command Q1={C to VIVU cluster, J}, starts VIVU and performs video analytic tasks;
Step 508:IVAM returns the information of VIVU cluster to CS.
If have the VIVU that can meet task requests Q in current C PR, then its service interaction flow process (step 403 in corresponding diagram 4) is as shown in Figure 6:
Step 601:VIVU cluster periodically reports IVAM the running status of oneself (comprise and whether normally running, performing video analytic tasks situation, the state values such as CPU, internal memory, hard disk, network I/O);
Step 602:IVAM, according to the loading condition of VIVU cluster, dispatches VIVU adaptively based on BScheduler algorithm, sends task execution command Qk to VIVU cluster, starts VIVU and performs video analytic tasks;
BScheduler dispatching algorithm: each video analytic tasks j that in traversal C, each camera ci is corresponding, if current VIVU can process j, then task j is distributed to current VIVU, if current VIVU can not Processing tasks j, then from VIVU cluster, select the next one there is no occupied VIVU.Finally obtain the task execution command Qk (wherein Qk contains the set of tasks that each VIVU should process) of VIVU cluster.
Step 603:IVAM returns the information of VIVU cluster to CS.
In the processing stage of task, after CS receives the VIVU cluster information that returns of IVAM, can monitor and receive the video analysis result that VIVU cluster returns, its concrete service interaction flow process as shown in Figure 7, comprises the steps:
Step 701:VIVU cluster receives the task execution command Q1={C that IVAM sends, and after J}, gathers C send camera connection request to PU;
Step 702:VIVU obtains and decoding standard monitoring video flow from camera, calls the video analysis algorithm that algorithm set J requires, carries out on-line analysis to video flowing;
Step 703:VIVU returns to CS video analysis result.
Task ending phase, when the time period T required in task Q ends, then its service interaction flow process as shown in Figure 8, comprises the steps:
Step 801:IVAM sends to VIVU and stops video analytic tasks order S=<Q1> (Q1={C, J});
The PU that step 802:VIVU specifies in camera set C sends and stops video stream order, then PU stops sending video flowing to VIVU, and VIVU stops video analytic tasks Q1;
Step 803:IVAM notifies that CS video analytic tasks Q arrives deadline, has stopped video analysis work.
Task ending phase, when CS to IVAM send cancel VIVU request time, then its service interaction flow process as shown in Figure 9, comprises the steps:
Step 901:CS sends to IVAM and cancels VIVU request command P=<Q> (Q={C, J, T});
Step 902:IVAM sends to VIVU and stops video analytic tasks order S=<Q1> (Q1={C, J});
The PU that step 903:VIVU specifies in camera set C sends and stops video stream order, then PU stops sending video flowing to VIVU, and VIVU stops video analytic tasks Q1;
Step 904:IVAM sends computational resource to CRMU and cancels request, and application to set aside performs the virtual computing server cluster of Q task;
Step 905:CRMU regains the computational resource shared by the VIVU of the Q that executes the task.
The foregoing is only the preferred embodiment of the application; not in order to limit the protection range of the application; within all spirit in technical scheme and principle, any amendment made, equivalent replacements, improvement etc., all should be included within scope that the application protects.
Claims (10)
1. the online Processing tasks of the monitor video based on a cloud computing management system, it is characterized in that, the online Processing tasks management system of described monitor video connects client and front-end camera respectively, and the online Processing tasks management system of this monitor video comprises: intelligent video analysis algorithm management module, cloud resource management module, cloud computing physical resource module and Virtual Intelligent video analytics server;
Described intelligent video analysis algorithm management module is used for the video analytic tasks of administrative client, the relevant information of preservation and managing virtual intelligent video analysis server, monitor the running status of Virtual Intelligent video analytics server, in virtual computing server deploy, start Virtual Intelligent video analytics server; Send resource bid to cloud computing physical resource module and cancel request;
Described cloud resource management module for dynamically creating Virtual Intelligent video analytics server, delete, check operation as required in cloud computing physical resource module;
Cloud computing physical resource module is used for deployment server virtualized environment, possesses the cloud computing physical resource of generating virtual intelligent video analysis server;
Virtual Intelligent video analytics server, be created on cloud computing physical resource that cloud computing physical resource module provides, each Virtual Intelligent video analytics server comprises one or more video analysis algorithms, for receiving and the video flowing of CCTV camera transmission of decoding, be responsible for carrying out online analysis to monitoring video flow, then the result of video analysis sent to client.
2. the online Processing tasks management system of monitor video according to claim 1, is characterized in that, described intelligent video analysis algorithm management module comprises following functional unit:
Intelligent video analysis algorithm management unit, for storing multiple intelligent video analysis algorithm mirror image, client carries out bookkeeping to video analysis algorithm mirror image; Described bookkeeping at least comprises interpolation, deletes and search;
Intelligent video analysis role management unit, for the video analytic tasks of administrative client, comprise monitor and response task requests, preservation and management role information, control task implementation;
Virtual Intelligent video analytics server administrative unit, for preserving the relevant information with managing virtual intelligent video analysis server, monitors the running status of Virtual Intelligent video analytics server; Also for sending the application of virtual computing server resource to cloud resource management module and cancelling request, and in virtual computing server deploy, startup Virtual Intelligent video analytics server;
System task scheduling unit, for the running status according to current virtual intelligent video analysis server cluster, carries out video analysis intelligent video analysis task scheduling to corresponding Virtual Intelligent video analytics server adaptively.
3. the online Processing tasks management system of monitor video according to claim 1, is characterized in that, described cloud resource management module comprises:
Cloud Host Administration unit, for dynamically carrying out bookkeeping to Virtual Intelligent video analytics server Virtual Intelligent video analytics server as required, remote activation, close, restart, log in Virtual Intelligent video analytics server Virtual Intelligent video analytics server, and thermophoresis can be carried out to Virtual Intelligent video analytics server Virtual Intelligent video analytics server; Described bookkeeping at least comprises establishment, deletes and check;
Mirror image administrative unit, for can creating, delete and inquiring about image file, realizes the rapid configuration of software environment and the rapid deployment of business;
Cloud Host Status monitoring unit, for monitoring the running status of the cloud main frame of cloud computing physical resource module in real time, collecting, preserving and the state value of graphical representation cloud main frame.
4. based on the online Processing tasks management method of monitor video of cloud computing, it is characterized in that, the method realizes based on the online Processing tasks management system of the monitor video as described in any one of claims 1 to 3, comprises the steps:
In the task requests stage: client sends monitor video online Processing tasks request Q={C to intelligent video analysis algorithm management module, then J, T} wait for the task deployment result of intelligent video analysis algorithm management module; Wherein, C={c1, c2 ..., cn} is camera set, J={j1, j2 ..., j3} is video analysis algorithm set, and T=[t1, t2] is task execution time section;
The task deployment stage: after intelligent video analysis algorithm management module receives task requests Q, judge: if there is no to meet the Virtual Intelligent video analytics server of task requests Q in current cloud computing physical resource module, the virtual computing server meeting the configuration of task requests Q resource requirement is then dynamically generated by cloud resource management module, then required intelligent video analysis algorithm application mirror image is deployed to virtual computing server, thus generate the Virtual Intelligent video analytics server meeting mission requirements, start Virtual Intelligent video analytics server and perform video analytic tasks, and Virtual Intelligent video analytics server relevant information is returned to client, if there is the Virtual Intelligent video analytics server that can meet task requests Q in current cloud computing physical resource module, then dispatch Virtual Intelligent video analytics server adaptively according to the loading condition of Virtual Intelligent video analytics server cluster, start Virtual Intelligent video analytics server and perform video analytic tasks, and corresponding Virtual Intelligent video analytics server cluster information is returned to client,
The processing stage of task: after client receives the Virtual Intelligent video analytics server information that intelligent video analysis algorithm management module returns, can monitor and receive the video analysis result that Virtual Intelligent video analytics server returns.Virtual Intelligent video analytics server obtains and decoding standard monitoring video flow from front-end camera, calls the video analysis algorithm of J demand, carries out on-line analysis, and analysis result is returned to client to video flowing.
5. method according to claim 4, it is characterized in that, the task deployment stage comprises further: after intelligent video analysis algorithm management module sends computational resource application to cloud resource management module, cloud resource management module is according to the loading condition of current cloud computing physical resource module, cloud computing physical resource module generates the virtual computing server of respective resources configuration, and the relevant information of virtual computing server is returned to intelligent video analysis algorithm management module.
6. method according to claim 5, it is characterized in that, if there is no the Virtual Intelligent video analytics server that can meet task requests Q in the current cloud computing physical resource module described in the task deployment stage, the virtual computing server meeting the configuration of task requests Q resource requirement is then dynamically generated by cloud resource management module, then required intelligent video analysis algorithm application mirror image is deployed to virtual computing server, thus generate the Virtual Intelligent video analytics server meeting mission requirements, start Virtual Intelligent video analytics server and perform video analytic tasks, and Virtual Intelligent video analytics server relevant information is returned to client comprise:
Step 501: intelligent video analysis algorithm management module signs in cloud resource management module, the identity of cloud resource management module to intelligent video analysis algorithm management module is verified;
Step 502: intelligent video analysis algorithm management module sends the request of generating virtual machines to cloud resource management module, dynamically generates the virtual computing server meeting the configuration of task requests Q resource requirement;
Step 503: cloud resource management module is according to the loading condition of present physical basic resource cloud computing physical resource module, the physical server set in cloud computing physical resource module is selected based on the first dispatching algorithm, virtual machine image is issued in the physical server set of selection, physical server set generates the virtual computing server cluster of respective resources configuration;
Step 504: cloud resource management module returns to intelligent video analysis algorithm management module the information of virtual computing server cluster;
Step 505: intelligent video analysis algorithm management module is deployed to the intelligent video analysis algorithm application mirror image required by Q on virtual computing server cluster, thus generate the Virtual Intelligent video analytics server cluster meeting mission requirements;
Step 506: Virtual Intelligent video analytics server cluster reports intelligent video analysis algorithm management module the running status of oneself;
Step 507: intelligent video analysis algorithm management module sends task execution command Q1={C to Virtual Intelligent video analytics server cluster, J}, starts Virtual Intelligent video analytics server and performs video analytic tasks;
Step 508: intelligent video analysis algorithm management module returns the information of Virtual Intelligent video analytics server cluster to client.
7. method according to claim 6, it is characterized in that, described first dispatching algorithm comprises: the disposal ability arranging each virtual computing server is identical, and minimum energy parallel processing Nk video analytic tasks, therefore need to create N cloud computing physical resource module=Nc*Nj/Nk virtual server, wherein Nc is the number of camera in C, and Nj is the number of task in J;
For each virtual computing server of establishment, first obtain the physical server virtual computation environmental state in all cloud computing physical resource modules, then the physical server not meeting Q resource requirement is filtered out; Then remaining to all filtrations physical server carries out weights scoring, finally extracts the highest some main frames of scoring, Stochastic choice one alternatively virtual computing server from these some physical servers.
8. method according to claim 4, it is characterized in that, if there is the Virtual Intelligent video analytics server that can meet task requests Q in the current cloud computing physical resource module described in step deployment phase, then dispatch Virtual Intelligent video analytics server adaptively according to the loading condition of Virtual Intelligent video analytics server cluster, start Virtual Intelligent video analytics server and perform video analytic tasks, and corresponding Virtual Intelligent video analytics server cluster information is returned to client comprise:
Step 601: Virtual Intelligent video analytics server cluster periodically reports intelligent video analysis algorithm management module the running status of oneself;
Step 602: intelligent video analysis algorithm management module is according to the loading condition of Virtual Intelligent video analytics server cluster, Virtual Intelligent video analytics server is dispatched adaptively based on the second dispatching algorithm, send task execution command Qk to Virtual Intelligent video analytics server cluster, start Virtual Intelligent video analytics server and perform video analytic tasks;
Step 603: intelligent video analysis algorithm management module returns the information of Virtual Intelligent video analytics server cluster to client.
9. method according to claim 8, it is characterized in that, described second dispatching algorithm comprises: each video analytic tasks j that in traversal C, each camera ci is corresponding, if current virtual intelligent video analysis server can process j, then task j is distributed to current virtual intelligent video analysis server, if current virtual intelligent video analysis server can not Processing tasks j, then from Virtual Intelligent video analytics server cluster, the next one is selected not have occupied Virtual Intelligent video analytics server; Finally obtain the task execution command Qk of Virtual Intelligent video analytics server cluster; Wherein Qk contains the set of tasks that each Virtual Intelligent video analytics server should process.
10. the method according to any one of claim 4 to 9, is characterized in that, comprises further after the processing stage of described task:
First kind task ending phase: at the end of task, when the time period T namely required in task Q ends, intelligent video analysis algorithm management module stops the video analysis work of Virtual Intelligent video analytics server;
Or,
Equations of The Second Kind task ending phase: or when client to intelligent video analysis algorithm management module send cancel the request of Virtual Intelligent video analytics server time, intelligent video analysis algorithm management module sends computational resource to cloud resource management module and cancels request, and then cloud resource management module regains the computational resource shared by respective virtual intelligent video analysis server.
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