CN107070740A - A kind of efficient PAAS platform monitoring methods and system - Google Patents
A kind of efficient PAAS platform monitoring methods and system Download PDFInfo
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- CN107070740A CN107070740A CN201710143426.6A CN201710143426A CN107070740A CN 107070740 A CN107070740 A CN 107070740A CN 201710143426 A CN201710143426 A CN 201710143426A CN 107070740 A CN107070740 A CN 107070740A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L65/00—Network arrangements, protocols or services for supporting real-time applications in data packet communication
- H04L65/40—Support for services or applications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
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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
- H04L67/50—Network services
- H04L67/535—Tracking the activity of the user
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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
- H04L67/50—Network services
- H04L67/56—Provisioning of proxy services
- H04L67/568—Storing data temporarily at an intermediate stage, e.g. caching
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Abstract
The present invention relates to big data and field of cloud calculation, a kind of efficient PAAS platform monitoring methods are disclosed, are comprised the following steps：On the host that intelligent Agent Systems are deployed in PAAS platforms；Intelligent Agent Systems carry out data acquisition to monitored object；Compression Strategies are used to be transmitted in the form of data block to data；Receive data block and carry out decompression.A kind of efficient PAAS platform monitorings system is also disclosed, including：Deployment module, acquisition module, transport module and processing module.The present invention by the method and system can accurate feedback platform running status in real time, reduce occupancy of the monitoring data to Internet resources, add the availability of system.
Description
Technical field
The present invention relates to big data and field of cloud calculation, more particularly to a kind of efficient PAAS platform monitoring methods and it is
System.
Background technology
Cloud computing technology make use of virtualization technology that the resources such as calculating, storage, network are carried out into pond, will by internet
Shared software and hardware is supplied to user in the way of servicing, and cloud computing technology possesses virtualization technology, parallel computing, grid
A series of advantages of calculating, distributed computing technology and lucidification disposal technology, and PAAS platforms are used as one kind of cloud computing to take
Service type, is supplied to software development user, as very popular in recent years on demand using software deployment, O＆M as one kind service
Research direction；In PAAS platforms, system service and all kinds of customizing services are required for platform to be monitored at any time, monitoring
Object complexity is various, and data volume is huge；In order to efficiently monitor PAAS platforms, it is ensured that the normal operation of service is, it is necessary to one
Stable, efficient and expansible monitor supervision platform.
The significant challenge of current PAAS platform monitoring systems faces has：The resource monitoring of cloud computing platform, can
Reliability, availability and the high efficiency of cloud platform are constantly weighed and assessed, is the pith for constituting cloud computing platform, therefore
Efficiently, the acquisition abnormity of reliable platform status information is important；The service type that PAAS platforms are provided is complicated various and can not be pre-
Know, monitored object is not quite similar with the change of service how efficiently all kinds of services are carried out with effective monitoring, and
Do not influence original PAAS platforms most important；The service that PAAS platforms are provided has stronger autgmentability and flexibility, monitoring
The data volume of collection is huge, and needs the information redundancy field of transmission excessive in the data of collection, for communications-intensive
For PAAS platforms, Internet resources are extremely precious, and monitoring system takes the substantial amounts of network bandwidth for a long time, can not only influence to put down
Platform collapse can be also caused can not externally to provide service under platform others service effectively operation, serious conditions.Therefore, how efficiently
Ground monitoring PAAS platforms are technical problems urgently to be resolved hurrily at present.
The content of the invention
The present invention is supervised for the weak point that current needs and prior art develop there is provided a kind of efficient PAAS platforms
Method and system are controlled, accurate feedback platform running status, adds the availability of system in real time.
In order to make it easy to understand, making explanation explained below to the part noun occurred in the present invention：
PAAS：English full name is Platform-as-a-Service, and platform is service；Operation and exploitation ring application service
Border, as a kind of business model for servicing and providing, is also that there is provided the exploitation of application program and running environment for a kind of cloud service.
Agent：Referring to reside in can continue under a certain environment, independently play a role, and meet reactive, social and main
The computational entity of the features such as dynamic property.
Intelligent Agent Systems：The system that this abstract, key concept is set up based on Agent, can realize calculating
The dynamic of entity, concurrency and intelligent.
Adler-32 algorithms：It is a kind of checksum algorithm that Mark Adler are proposed, with more preferable execution efficiency.It is lower
Can not detect the probability made mistake.
MD5：English full name is Message-Digest Algorithm 5, Message-Digest Algorithm 5, for ensuring information
Transmission is complete consistent.It is one of widely used hash algorithm of computer, main flow programming language generally has MD5 and realized, by number
It is another fixed-length value according to computing, is the basic principle of hash algorithm.
To achieve these goals, the present invention uses following technical scheme：
The invention provides a kind of efficient PAAS platform monitoring methods, comprise the following steps：
On the host that intelligent Agent Systems are deployed in PAAS platforms；
Intelligent Agent Systems carry out data acquisition to monitored object；
Compression Strategies are used to be transmitted in the form of data block to data；
Receive data block and carry out decompression.
Preferably, after intelligent Agent Systems are deployed on the host of PAAS platforms, in addition to：According to difference
Monitored object, be respectively that it sets up data buffering queue, and set between the acquiescence monitoring period of intelligent Agent Systems and sampling
Every atomic time, default sample cycles of intelligent Agent Systems is equal with acquiescence monitoring period.
Preferably, described intelligent Agent Systems carry out data acquisition to monitored object, including：Intelligent Agent Systems are adopted
With the sampling period of acquiescence, the different running state informations of collection host and service, by the information collected storage to correspondence
Data buffering queue in.
Preferably, after intelligent Agent Systems carry out data acquisition to monitored object, in addition to：
Calculate the standard deviation δ of data in data buffering queue：
Wherein, XiFor the data state info of i-th of the monitored object collected, n refers to the sum of monitored object；
The upper limit for defining the data deviation of i-th of monitored object is Li, the upper limit L of criterion difference δ and deviationiSize, if δ
＜ Li, then the sampling period is increased；If δ >=Li, then the sampling period is reduced.
Preferably, the described increase sampling period includes：Calculate the sampling period T after increaseu：
Tu=T+taf(δ,Li)
Wherein, T refers to the default sample cycle of intelligent Agent Systems；taRefer to the atomic time in sampling interval；f(δ,Li) be
Refer to the standard deviation δ and threshold value L of dataiRespective function relation；
The described reduction sampling period includes：Calculate the sampling period T after reducingd：
Td=Max (T/2, ta)
Wherein, Max (T/2, ta) refer to take T/2 and taMaximum in the two.
Preferably, it is described to use Compression Strategies to be transmitted in the form of data block to data, including：
The data block size K (i) of each monitored object transmitted between computational intelligence Agent systems and cloud platform：
Wherein, TiRefer to sampling period of the intelligent Agent Systems to i-th of monitored object；SiRefer to the shape of i-th of monitored object
The particle size of state change；λ refers to factor of influence；SdRefer to the default size of data block；
According to the data block size of the monitored object of determination, it is serialized, one group is constituted by m of the size for K (i) bytes
The sequence of individual data block composition：
Wherein,Refer to different size of data block；
Obtain the index after the serializing of corresponding data block, the complete information of each index corresponding data block；
Local node safeguards a serialized data block transmitted：
Wherein,Refer to the different size of data block transmitted；
Adler32 value of the index sequence for data block after k to l serializing is drawn as check code by the use of Adler32 algorithms, and is compared
More whether transmission data block is identical with the check code of non-transmission data block, if so, obtaining another group of verification using MD5 algorithms
Code, compares transmission data block whether identical with the check code of non-transmission data block；If it is not, sending this serialized data to platform
The data of block and the index in initial data；
Whether transmission data block is identical with the check code of non-transmission data block for described utilization MD5 algorithm comparisons, including：Utilize
MD5 algorithms show that MD5 value of the index sequence for data block after k to l serializing, as another group of check code, has transmitted data
Whether block is identical with the check code of non-transmission data block, if so, the index of transmission serialized data block；If it is not, transmission serializing
The complete information of data block.
Preferably, described reception data block and decompression is carried out, including：PAAS platforms receive intelligent Agent system
The serialized data block of system transmission, takes out the data block of correspondence monitored object, by using index from local data information bank
And its data block carries out decompression and obtains complete data block information.
Present invention also offers a kind of efficient PAAS platform monitorings based on a kind of efficient PAAS platform monitoring methods
System, including：
Deployment module, the host for intelligent Agent Systems to be deployed in PAAS platforms；
Acquisition module, data acquisition is carried out for intelligent Agent Systems to monitored object；
Transport module, for using Compression Strategies to be transmitted in the form of data block to data；
Processing module, for receiving data block and carrying out decompression.
Preferably, in addition to：
Setup module, for according to different monitored object, being respectively that it sets up data buffering queue, and sets intelligent Agent
The acquiescence monitoring period and the atomic time in sampling interval of system, default sample cycle and the acquiescence of intelligent Agent Systems are monitored
Time is equal；
The upper limit L of judge module, the standard deviation δ for calculating data in buffered data queue, criterion difference δ and deviationi's
Size.
Preferably, the transport module includes：
Computing module, for the data block size of each monitored object transmitted between computational intelligence Agent systems and cloud platform；
Block, for the data block size of the monitored object according to determination, is serialized to it；
First comparison module, for drawing Adler32 of the index sequence for data block after k to l serializing using Adler32 algorithms
Value is as check code, and whether compare transmission data block identical with the check code of non-transmission data block；
Second comparison module, for using MD5 algorithm comparisons transmission data block and non-transmission data block check code whether phase
Together.
Beneficial effects of the present invention：
1. the present invention is by the running state information of monitored object, Mobile state adjustment is entered to data collection cycle, redundancy is reduced
Collection, transmission and the storage of data, save substantial amounts of network, calculating, storage resource；
2. the data collection cycle of the present invention realizes the adjustment to data collection cycle by the running status of monitored object, then leads to
Regulation of the adjustment realization of collection period to monitored object state is crossed, closed-loop control is used, it is calculated independent of experience
Set, can correctly reflect the real-time running state of system；
3. the data transfer based on data compression strategy of the present invention, greatly reduces the transmission of redundant data, the strategy exists
On the basis of the stability of guarantee system, the utilization rate of the network bandwidth is greatly improved so that the performance of cloud platform and experience
Degree is improved.
Brief description of the drawings
Fig. 1 is a kind of one of schematic flow sheet of efficient PAAS platform monitoring methods of the present invention.
Fig. 2 is a kind of one of structural representation of efficient PAAS platform monitorings system of the present invention.
Fig. 3 is the two of a kind of schematic flow sheet of efficient PAAS platform monitoring methods of the present invention.
Fig. 4 is the two of a kind of structural representation of efficient PAAS platform monitorings system of the present invention.
Embodiment
With reference to the accompanying drawings and examples, the embodiment to the present invention is described in further detail：
Embodiment one：As shown in figure 1, a kind of efficient PAAS platform monitoring methods of the present invention, comprise the following steps：
Step S101：On the host that intelligent Agent Systems are deployed in PAAS platforms；
Step S102：Intelligent Agent Systems carry out data acquisition to monitored object；
Step S103：Compression Strategies are used to be transmitted in the form of data block to data；
Step S104：Receive data block and carry out decompression.
Embodiment two：As shown in Fig. 2 a kind of efficient PAAS platform monitorings system of the present invention, including：
Deployment module 201, acquisition module 202, transport module 203 and processing module 204；Deployment module 201 is sequentially connected collection
Module 202, transport module 203 and processing module 204.
Deployment module 201, the host for intelligent Agent Systems to be deployed in PAAS platforms；Acquisition module 202,
Data acquisition is carried out to monitored object for intelligent Agent Systems；Transport module 203, for using Compression Strategies with data block
Form data are transmitted；Processing module 204, for receiving data block and carrying out decompression.
Embodiment three：As shown in figure 3, another efficient PAAS platform monitoring methods of the present invention, including：
Step S301：On the host that intelligent Agent Systems are deployed in PAAS platforms；
Step S302：It is respectively that it sets up data buffering queue, and intelligent Agent Systems are set according to different monitored object
The acquiescence monitoring period and atomic time in sampling interval, default sample cycle and the acquiescence monitoring period of intelligent Agent Systems
It is equal；
Step S303：Intelligent Agent Systems gather host and the different running statuses letter of service using the sampling period of acquiescence
Breath, by the information collected storage into corresponding data buffering queue；
Step S304：Calculate the standard deviation δ of data in data buffering queue：
Wherein, XiFor the data state info of i-th of the monitored object collected, n refers to the sum of monitored object；
The upper limit for defining the data deviation of i-th of monitored object is Li, the upper limit L of criterion difference δ and deviationiSize, if δ
＜ Li, then the sampling period is increased；If δ >=Li, then the sampling period is reduced.
Preferably, the described increase sampling period includes：Calculate the sampling period T after increaseu：
Tu=T+taf(δ,Li)
Wherein, T refers to the default sample cycle of intelligent Agent Systems；taRefer to the atomic time in sampling interval；f(δ,Li) be
Refer to the standard deviation δ and threshold value L of dataiRespective function relation；
The described reduction sampling period includes：Calculate the sampling period T after reducingd：
Td=Max (T/2, ta)
Wherein, Max (T/2, ta) refer to take T/2 and taMaximum in the two.
Step S305：The data block size K of each monitored object transmitted between computational intelligence Agent systems and cloud platform
(i)：
Wherein, TiRefer to sampling period of the intelligent Agent Systems to i-th of monitored object；SiRefer to the shape of i-th of monitored object
The particle size of state change；λ refers to factor of influence；SdRefer to the default size of data block；
According to the data block size of the monitored object of determination, it is serialized, one group is constituted by m of the size for K (i) bytes
The sequence of individual data block composition：
Wherein,Refer to different size of data block；
Obtain the index after the serializing of corresponding data block, the complete information of each index corresponding data block；
Local node safeguards a serialized data block transmitted：
Wherein,Refer to the different size of data block transmitted；
Step S307：Show that index sequence is used as school for the Adler32 values of data block after k to l serializing by the use of Adler32 algorithms
Test code, and whether compare transmission data block identical with the check code of non-transmission data block, if so, being obtained separately using MD5 algorithms
One group of check code, compares transmission data block whether identical with the check code of non-transmission data block；If it is not, sending this sequence to platform
The data of rowization data block and the index in initial data；
Step S308：Show that index sequence is used as another group of verification for the MD5 values of data block after k to l serializing by the use of MD5 algorithms
Code, compares whether transmission data block is identical with the check code of non-transmission data block, if so, the rope of transmission serialized data block
Draw；If it is not, the complete information of transmission serialized data block；
Step S309：PAAS platforms receive the serialized data block of intelligent Agent Systems transmission, are taken from local data information bank
Go out the data block of correspondence monitored object, carrying out decompression by using index and its data block obtains complete data block information.
Example IV：As shown in figure 4, another efficient PAAS platform monitorings system of the present invention, including：
Computing module 405 in deployment module 401, setup module 402, acquisition module 403, judge module 404, transport module,
The first comparison module 407 in block 406, transport module in transport module, the second comparison module in transport module
408 and processing module 409；Deployment module 401 is sequentially connected setup module 402, acquisition module 403, judge module 404, transmission
The block 406 in computing module 405, transport module in module, the first comparison module 407 in transport module, transmission
The second comparison module 408 and processing module 409 in module.
Deployment module 401, the host for intelligent Agent Systems to be deployed in PAAS platforms；Setup module 402,
For according to different monitored object, being respectively that it sets up data buffering queue, and the acquiescence of intelligent Agent Systems is set to monitor
Time and the atomic time in sampling interval, the default sample cycle of intelligent Agent Systems are equal with acquiescence monitoring period；Gather mould
Block 403, for sampling period of the intelligent Agent Systems using acquiescence, the different running state informations of collection host and service,
By the information collected storage into corresponding data buffering queue；Judge module 404, for calculating number in buffered data queue
According to standard deviation δ, the upper limit L of criterion difference δ and deviationiSize；Computing module 405 in transport module, for calculating
The data block size of each monitored object transmitted between intelligent Agent Systems and cloud platform；Block in transport module
406, for the data block size of the monitored object according to determination, it is serialized；First in transport module compares mould
Block 407, for showing that index sequence is used as verification for the Adler32 values of data block after k to l serializing by the use of Adler32 algorithms
Code, and whether compare transmission data block identical with the check code of non-transmission data block；The second comparison module in transport module
408, for drawing MD5 value of the index sequence for data block after k to l serializing as another group of check code by the use of MD5 algorithms, than
More whether transmission data block is identical with the check code of non-transmission data block；Processing module 409, intelligence is received for PAAS platforms
The serialized data block of Agent systems transmission, takes out the data block of correspondence monitored object, by making from local data information bank
Index of reference and its data block carry out decompression and obtain complete data block information.
Illustrated above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, under the premise without departing from the principles of the invention, some improvements and modifications can also be made, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (10)
1. a kind of efficient PAAS platform monitoring methods, it is characterised in that comprise the following steps：
On the host that intelligent Agent Systems are deployed in PAAS platforms；
Intelligent Agent Systems carry out data acquisition to monitored object；
Compression Strategies are used to be transmitted in the form of data block to data；
Receive data block and carry out decompression.
2. a kind of efficient PAAS platform monitoring methods according to claim 1, it is characterised in that by intelligent Agent
After system deployment is on the host of PAAS platforms, in addition to：According to different monitored object, respectively it is set up data and delayed
Queue is rushed, and the acquiescence monitoring period and the atomic time in sampling interval of intelligent Agent Systems are set, intelligent Agent Systems
The default sample cycle is equal with acquiescence monitoring period.
3. a kind of efficient PAAS platform monitoring methods according to claim 1, it is characterised in that described intelligence
Agent systems carry out data acquisition to monitored object, including：Intelligent Agent Systems gather host using the sampling period of acquiescence
Machine and the different running state informations of service, by the information collected storage into corresponding data buffering queue.
4. a kind of efficient PAAS platform monitoring methods according to claim 1, it is characterised in that in intelligent Agent system
System is carried out to monitored object after data acquisition, in addition to：
Calculate the standard deviation δ of data in data buffering queue：
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Wherein, XiFor the data state info of i-th of the monitored object collected, n refers to the sum of monitored object；
The upper limit for defining the data deviation of i-th of monitored object is Li, the upper limit L of criterion difference δ and deviationiSize, if δ
＜ Li, then the sampling period is increased；If δ >=Li, then the sampling period is reduced.
5. a kind of efficient PAAS platform monitoring methods according to claim 4, it is characterised in that described increase sampling
Cycle includes：Calculate the sampling period T after increaseu：
Tu=T+taf(δ,Li)
Wherein, T refers to the default sample cycle of intelligent Agent Systems；taRefer to the atomic time in sampling interval；f(δ,Li) refer to
The standard deviation δ and threshold value L of dataiRespective function relation；
The described reduction sampling period includes：Calculate the sampling period T after reducingd：
Td=Max (T/2, ta)
Wherein, Max (T/2, ta) refer to take T/2 and taMaximum in the two.
6. a kind of efficient PAAS platform monitoring methods according to claim 1, it is characterised in that described uses compression
Strategy is transmitted in the form of data block to data, including：
The data block size K (i) of each monitored object transmitted between computational intelligence Agent systems and cloud platform：
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The particle size of state change；λ refers to factor of influence；SdRefer to the default size of data block；
According to the data block size of the monitored object of determination, it is serialized, one group is constituted by m of the size for K (i) bytes
The sequence of individual data block composition：
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Obtain the index after the serializing of corresponding data block, the complete information of each index corresponding data block；
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Wherein,Refer to the different size of data block transmitted；
Adler32 value of the index sequence for data block after k to l serializing is drawn as check code by the use of Adler32 algorithms, and is compared
More whether transmission data block is identical with the check code of non-transmission data block, if so, obtaining another group of verification using MD5 algorithms
Code, compares transmission data block whether identical with the check code of non-transmission data block；If it is not, sending this serialized data to platform
The data of block and the index in initial data；
Whether transmission data block is identical with the check code of non-transmission data block for described utilization MD5 algorithm comparisons, including：Utilize
MD5 algorithms show that MD5 value of the index sequence for data block after k to l serializing, as another group of check code, has transmitted data
Whether block is identical with the check code of non-transmission data block, if so, the index of transmission serialized data block；If it is not, transmission serializing
The complete information of data block.
7. a kind of efficient PAAS platform monitoring methods according to claim 1, it is characterised in that described reception data
Block simultaneously carries out decompression, including：PAAS platforms receive the serialized data block of intelligent Agent Systems transmission, from local number
According to the data block that corresponding monitored object is taken out in information bank, decompression is carried out by using index and its data block and obtained completely
Data block information.
8. a kind of efficient PAAS platforms based on a kind of any described efficient PAAS platform monitoring methods of claim 1-7
Monitoring system, it is characterised in that including：
Deployment module, the host for intelligent Agent Systems to be deployed in PAAS platforms；
Acquisition module, data acquisition is carried out for intelligent Agent Systems to monitored object；
Transport module, for using Compression Strategies to be transmitted in the form of data block to data；
Processing module, for receiving data block and carrying out decompression.
9. a kind of efficient PAAS platform monitorings system according to claim 8, it is characterised in that also include：
Setup module, for according to different monitored object, being respectively that it sets up data buffering queue, and sets intelligent Agent
The acquiescence monitoring period and the atomic time in sampling interval of system, default sample cycle and the acquiescence of intelligent Agent Systems are monitored
Time is equal；
The upper limit L of judge module, the standard deviation δ for calculating data in buffered data queue, criterion difference δ and deviationiIt is big
It is small.
10. a kind of efficient PAAS platform monitorings system according to claim 8, it is characterised in that the transport module
Including：
Computing module, for the data block size of each monitored object transmitted between computational intelligence Agent systems and cloud platform；
Block, for the data block size of the monitored object according to determination, is serialized to it；
First comparison module, for drawing Adler32 of the index sequence for data block after k to l serializing using Adler32 algorithms
Value is as check code, and whether compare transmission data block identical with the check code of non-transmission data block；
Second comparison module, for using MD5 algorithm comparisons transmission data block and non-transmission data block check code whether phase
Together.
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