CN109271395A - Extensive real time data for comprehensive monitoring system updates delivery system and method - Google Patents
Extensive real time data for comprehensive monitoring system updates delivery system and method Download PDFInfo
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Abstract
Delivery system is updated the invention discloses a kind of extensive real time data for comprehensive monitoring system and method, this method are as follows: publishing policy being updated according to static state and real-time dynamic effects factor generates dynamic and updates publishing policy；The update and publication of publishing policy control real time data point data are updated according to above-mentioned dynamic, and will be updated and be issued result data and feed back in real-time dynamic effects factor storehouse；Above-mentioned update and publication result data are stored；Corresponding result data is sent to corresponding issuing interface according to subscription, query information.The present invention meets the requirement of large-scale data online updating publication for the various working condition requirement designs of track traffic synthetic monitoring system.
Description
Technical Field
The invention belongs to the technical field of online updating and publishing of large-scale real-time data of a rail transit comprehensive monitoring system, and particularly relates to a system and a method for updating and publishing the large-scale real-time data based on dynamic feedback of a strategy in the rail transit comprehensive monitoring system.
Background
The rail transit integrated monitoring system is a large-scale rail transit automatic system, and each electromechanical equipment system of rail transit which needs to be integrated or interconnected comprises a signal system (ATS), a power monitoring system (PSCADA), an environment and equipment monitoring system (BAS), an automatic ticket selling and checking system (AFC), a video monitoring system (CCTV), a broadcasting system (PA), a Passenger Information System (PIS), a fire fighting system (FAS), an Access Control System (ACS), a screen door system (PSD), a flood gate system (FG), an automatic time synchronization system (CLK), a communication centralized alarm system (TEL/ALM) and the like. The main functions of the rail transit comprehensive monitoring include a real-time centralized monitoring function of electromechanical equipment and a coordination linkage function among all systems. On one hand, the basic functions of real-time centralized monitoring and control of broadcasting information, clock information and the like of power equipment, fire alarm information and equipment thereof, station environment control equipment, interval environment control equipment, environmental parameters, shielded door equipment, flood gate prevention equipment, escalator equipment, lighting equipment, access control equipment, automatic ticket selling and checking equipment, broadcasting and closed-circuit television equipment and a passenger information display system can be realized through the comprehensive monitoring system; on the other hand, through the comprehensive monitoring system, high-level functions such as coordination and interaction among related system equipment under the night non-operation condition, the day normal operation condition, the emergency condition and the important equipment failure condition can be realized.
The main monitoring quantity of the integrated monitoring system comprises digital quantity input (DI), digital quantity output (DO), analog quantity input (AI), analog quantity output (AO) and the like, monitoring mainly aims at DI and AI points, and control mainly aims at DO and AO points; by integrating the estimation of the conditions of a plurality of actual lines, a typical rail transit integrated monitoring system of a subway line needs to meet 50 ten thousand equipment points, wherein 30 thousand digital quantity points and 20 thousand analog quantity points can meet the project requirements. The core of the comprehensive monitoring system is a real-time database, the performance of the real-time database can meet the performance requirement of the system under normal working conditions, under certain extreme conditions, a large number of events can occur in a short time, namely the phenomenon of 'avalanche' of the system, hundreds of thousands of point-like state change data are instantly accumulated in the database, the load of the database is increased by 6-10 times under the condition of 'avalanche' calculation, so that the database cannot be immediately processed, and even a server is down.
Disclosure of Invention
In view of the above disadvantages of the prior art, an object of the present invention is to provide a system and a method for updating and publishing large-scale real-time data of a comprehensive monitoring system, so as to solve the problem that when abnormal conditions occur in the rail transit comprehensive monitoring system in the prior art, input DI and AI are increased in a large scale, and a system processing channel is blocked, so that the system processing performance is greatly reduced.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
the invention relates to a large-scale real-time data updating and releasing system for an integrated monitoring system, which comprises:
the subscription inquiry module is used for receiving subscription and inquiry request information and outputting subscription and inquiry result information;
the real-time dynamic influence factor library is used for storing real-time dynamic influence factors;
the strategy synthesis module is used for generating a dynamic update release strategy according to the static update release strategy and the real-time dynamic influence factors;
the preprocessing module is used for preprocessing the data point data according to the dynamic update release strategy;
the strategy execution module is used for controlling the updating and the publishing of the preprocessed data point data according to the dynamic updating and publishing strategy;
and the data storage module is used for storing the result data which is updated and released in real time and sending the result data to the real-time dynamic influence factor library.
Preferably, the subscription and query module receives the subscription and query request information, and outputs corresponding result data in a manner of a query and information publishing interface after obtaining the subscription and query result data in the data storage module; and feeding back the received subscription and query request information to the real-time dynamic influence factor library.
Preferably, the dynamic update publishing policy specifically includes: if the data point is subscribed at present, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the subscription times and real-time dynamic influence factors except the subscription times; if the data point is inquired for many times in the latest period of time, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the inquiry times and real-time dynamic influence factors except the inquiry times; if the data point has a latest subscription or inquiry, updating the data point cannot be rejected or abandoned, and the priority is determined according to the latest subscription or inquiry time and real-time dynamic influence factors except the latest subscription time and the latest inquiry time; determining a special data point according to the characteristics of the data point and the data association relation, wherein the updating of the special data point must not be rejected or abandoned and is preferentially updated; adjusting the priority of the data points according to the updating result, the updating times and the updating time interval of the data points; and determining the current working condition according to the updating condition of the special points and the total concurrent updating data volume in a short time, and when the characteristic data updating occurs and the short-time concurrent updating data meets the requirement of the abnormal working condition, processing according to the strategy of the abnormal working condition.
Preferably, the preprocessing module preprocesses the data point data according to a dynamic update distribution strategy, namely refusing data point data update and directly abandoning the data point data, and feeds back result information to the real-time dynamic influence factor library.
Preferably, the policy execution module performs multithreading processing on the preprocessed data point data according to a dynamic update issuing policy, updates and stores real-time data point data to the data storage module, and then issues information, that is, rejects, abandons or directly issues the data point data.
The invention discloses a large-scale real-time data updating and publishing method for a comprehensive monitoring system, which comprises the following steps of:
1) generating a dynamic update release strategy according to the static update release strategy and the real-time dynamic influence factors;
2) controlling the updating and the publishing of the real-time data point data according to the dynamic updating and publishing strategy, and feeding back the updating and publishing result data to a real-time dynamic influence factor library;
3) storing the updated and released result data;
4) updating the subscription and query information to real-time dynamic influence factors;
5) directly returning the query result to the query interface;
6) and finishing the information issuing state of the result data in the step 3) according to the dynamic updating issuing strategy.
Preferably, the static update publishing policy in step 1) includes: rejecting data point data updating, directly abandoning data point data, processing data point data at low priority, processing data point data at normal processing, processing data point data at high priority and processing data point data at abnormal working condition.
Preferably, the real-time dynamic influence factors in the step 1) are classified into four categories, one category is according to query and subscription conditions, and the category comprises data point subscription times, data point latest subscription time, query times within a certain time of data points, and data point latest query time; one is according to the preconditioning situation, including the total concurrent update quantity of short time, number of times of updating and data point recently updated in certain time; one is data processing situation, including data processing result, latest processing time; one is based on real-time result data storage, including data priority, data association relation, data last used time, data latest change time, and data update release result record in a certain time.
The updating condition considers the influence of data updating results such as the data updating times and the latest data updating time in a certain time on the subsequent data point data updating and publishing, the data updating times in the certain time are few or the data which is not updated recently, and the priority of the subsequent data is relatively improved along with the time.
The association relation considers factors such as the number of times that the special data points and the data are associated and quoted, and the updating and the publishing of the special data points must be processed firstly and must not be rejected or abandoned.
Preferably, the dynamically updating the release policy in step 1) specifically includes: if the data point is subscribed at present, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the subscription times and real-time dynamic influence factors except the subscription times; if the data point is inquired for many times in the latest period of time, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the inquiry times and real-time dynamic influence factors except the inquiry times; if the data point has a latest subscription or inquiry, updating the data point cannot be rejected or abandoned, and the priority is determined according to the latest subscription or inquiry time and real-time dynamic influence factors except the latest subscription time and the latest inquiry time; determining a special data point according to the characteristics of the data point and the data association relation, wherein the updating of the special data point must not be rejected or abandoned and is preferentially updated; adjusting the priority of the data points according to the updating result, the updating times and the updating time interval of the data points; and determining the current working condition according to the updating condition of the special points and the total concurrent updating data volume in a short time, and when the characteristic data updating occurs and the short-time concurrent updating data meets the requirement of the abnormal working condition, processing according to the strategy of the abnormal working condition.
Preferably, the step 2) specifically comprises: preprocessing data point data according to a dynamic update issuing strategy, namely rejecting data point data update and directly giving up data point data, and feeding back result information to a real-time dynamic influence factor library; and multithreading is carried out on the preprocessed data, the data of the real-time data point is updated and stored, then the information is issued, namely the data point data is refused, abandoned or directly issued, and the updated result information is fed back to the real-time dynamic influence factor library.
Preferably, the completion information issuing state in step 6) specifically includes: rejecting issuing, giving up issuing, issuing with low priority, issuing normally and issuing with high priority, and issuing information under abnormal working condition.
The invention has the beneficial effects that:
the method of the invention is specially designed for various working conditions (including normal working conditions, avalanche working conditions, blocking working conditions, fault working conditions and disaster working conditions) of the rail transit comprehensive monitoring system, meets the requirement of large-scale data online updating and releasing, and has the following characteristics:
1. the processing performance is high, the capacity of real-time data is more than 100 ten thousand points, the concurrent updating of the real-time data is more than 30 ten thousand points/second, the concurrent query of the real-time data is more than 10 ten thousand points/second, and the concurrent release of the real-time data is more than 10 ten thousand points/second;
2. the network flow is low, the updating interface is separated from the releasing interface, and the updating interface adopts a proprietary packaging format, so that the network flow is reduced; the updating data adopts a real-time data compression method, so that the network flow is reduced, and the network flow is reduced by 60%;
3. the response is rapid, the change and refresh time of important data is less than 200 milliseconds, the response time of important data is less than 800 milliseconds, the change and refresh time of data is less than 1 second, and the issuing time of a control command is less than 1 second;
4. the stability is high, and a dynamic updating and releasing strategy is adopted under an abnormal working condition to prevent the system from going down.
Drawings
FIG. 1 is a schematic block diagram of the system of the present invention;
FIG. 2 is a schematic diagram of a method of the present invention;
FIG. 3 is a graph of real-time dynamic impact factors of the present invention.
Detailed Description
In order to facilitate understanding of those skilled in the art, the present invention will be further described with reference to the following examples and drawings, which are not intended to limit the present invention.
Referring to fig. 1, a large-scale real-time data update distribution system for an integrated monitoring system according to the present invention includes:
the subscription inquiry module is used for receiving subscription and inquiry request information and outputting corresponding result data in a release interface mode; the publishing interface adopts a mode of combining inquiry and subscription, and the inquiry mode is that the value of a data point is actively obtained in a one-by-one mode when the client needs the data point; the subscription publishing (i.e. information publishing) mode is that the client subscribes to the value of the data point, and when the value of the data point changes, the server directly pushes the data to the client without active query of the client every time. And the subscription inquiry module feeds back the subscription and inquiry request information to the real-time dynamic influence factor library.
Referring to fig. 3, the real-time dynamic influence factor library is used for storing real-time dynamic influence factors; the real-time dynamic influence factors are divided into four types, one type is according to inquiry and subscription conditions, including data point subscription times, data point latest subscription time, inquiry times of data points within a certain time and data point latest inquiry time; one is according to the preconditioning situation, including the total concurrent update quantity of short time, number of times of updating and data point recently updated in certain time; one is data processing situation, including data processing result, latest processing time; one is based on real-time result data storage, including data priority, data association relation, data last used time, data latest change time, and data update release result record in a certain time.
The strategy synthesis module is used for generating a dynamic update release strategy according to the static update release strategy and the real-time dynamic influence factors; the static update issue strategy is automatically generated through system static strategy configuration information when being started, and comprises the following steps: rejecting data point data updating, directly abandoning data point data, processing data point data at low priority, processing data point data at normal processing, processing data point data at high priority and processing data point data at abnormal working condition; the dynamic update release policy comprises: if the data point is subscribed at present, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the subscription times and real-time dynamic influence factors except the subscription times; if the data point is inquired for many times in the latest period of time, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the inquiry times and real-time dynamic influence factors except the inquiry times; if the data point has a latest subscription or inquiry, updating the data point cannot be rejected or abandoned, and the priority is determined according to the latest subscription or inquiry time and real-time dynamic influence factors except the latest subscription time and the latest inquiry time; determining a special data point according to the characteristics of the data point and the data association relation, wherein the updating of the special data point must not be rejected or abandoned and is preferentially updated; adjusting the priority of the data points according to the updating result, the updating times and the updating time interval of the data points; and determining the current working condition according to the updating condition of the special points and the total concurrent updating data volume in a short time, and when the characteristic data updating occurs and the short-time concurrent updating data meets the requirement of the abnormal working condition, processing according to the strategy of the abnormal working condition.
The preprocessing module firstly caches the received data, then converts the format of the data (converts the data with different types and formats into a uniform internal data format), and then processes the data point data according to a dynamic update release strategy, namely refusing data point data update, directly abandoning the data point data, transmitting the data to the strategy execution module for processing according to the priority, and feeding back result information to the real-time dynamic influence factor library.
The strategy execution module is used for updating and releasing the preprocessed data point data according to the dynamic updating and releasing strategy; the method specifically comprises the following steps: multithreading processing is carried out on the preprocessed data, real-time data point data is updated and stored, then information is issued, and updated result information is fed back to a real-time dynamic influence factor library;
the strategy execution module is connected with an updating interface, the updating interface is separated from the inquiry and subscription interface, and a large-scale data updating interface is adopted; the large-scale data updating interface is optimized according to the data type, and a special data structure is adopted; the large-scale data updating interface adopts a real-time compression mode, reduces redundant data and reduces network flow;
the multithreading specifically comprises: according to the performance of the server (the number of CPU cores and the size of a memory), the number and the type of data points, the data are processed by comprehensively adopting the modes of multithreading, multi-level caching, multi-level processing, dynamic priority and the like, the result data are stored in a data storage module, and the processing condition is fed back to a real-time dynamic influence factor library; detecting the number of CPU cores and determining the number of multiple threads; determining the cache size of each level according to the memory size; and determining the static priority and the basic dynamic priority of the data points and the processing modes (alarm, log, linkage and the like) in abnormal conditions according to the number and the types of the data points.
And the data storage module is used for storing the result data which is updated and published in real time, sending the result data to the real-time dynamic influence factor library and transmitting the result data which is updated and published in real time to the subscription inquiry module.
Referring to fig. 2, the method for updating and publishing the large-scale real-time data of the integrated monitoring system according to the present invention includes the following steps:
1) generating a dynamic update release strategy according to the static update release strategy and the real-time dynamic influence factors; wherein,
the static update distribution strategy comprises the following steps: rejecting data point data updating, directly abandoning data point data, processing data point data at low priority, processing data point data at normal processing, processing data point data at high priority and processing data point data at abnormal working condition;
the real-time dynamic influence factors are divided into four types, one type is according to inquiry and subscription conditions, including data point subscription times, data point latest subscription time, inquiry times of data points within a certain time and data point latest inquiry time; one is according to the preconditioning situation, including the total concurrent update quantity of short time, number of times of updating and data point recently updated in certain time; one is data processing situation, including data processing result, latest processing time; one is based on real-time result data storage, including data priority, data association relation, data last used time, data latest change time, and data update release result record in a certain time.
The dynamic update release policy specifically includes: if the data point is subscribed at present, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the subscription times and real-time dynamic influence factors except the subscription times; if the data point is inquired for many times in the latest period of time, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the inquiry times and real-time dynamic influence factors except the inquiry times; if the data point has a latest subscription or query, updating the data point cannot be rejected or abandoned, and the priority is determined according to the latest subscription or query time and real-time dynamic influence factors except the latest subscription time and query time; determining a special data point according to the characteristics of the data point and the data association relation, wherein the updating of the special data point must not be rejected or abandoned and is preferentially updated; adjusting the priority of the data points according to the updating result, the updating times and the updating time interval of the data points; and determining the current working condition according to the updating condition of the special points and the total concurrent updating data volume in a short time, and when the characteristic data updating occurs and the short-time concurrent updating data meets the requirement of the abnormal working condition, processing according to the strategy of the abnormal working condition.
2) Controlling the updating and the publishing of the real-time data point data according to the dynamic updating and publishing strategy, and feeding back the updating and publishing result data to a real-time dynamic influence factor library; the method specifically comprises the following steps: preprocessing data point data according to a dynamic update issuing strategy, namely rejecting data point data update and directly giving up data point data, and feeding back result information to a real-time dynamic influence factor library; and multithreading is carried out on the preprocessed data, the data of the real-time data point is updated and stored, and the updated result information is fed back to the real-time dynamic influence factor library;
the strategy execution module is connected with an updating interface, the updating interface is separated from the inquiry and subscription interface, and a large-scale data updating interface is adopted; the large-scale data updating interface is optimized according to the data type, and a special data structure is adopted; the large-scale data updating interface adopts a real-time compression mode, reduces redundant data and reduces network flow;
the multithreading specifically comprises: according to the performance of the server (the number of CPU cores and the size of a memory), the number and the type of data points, the data are processed by comprehensively adopting the modes of multithreading, multi-level cache, multi-level processing, dynamic priority and the like; detecting the number of CPU cores and determining the number of multiple threads; determining the cache size of each level according to the memory size; and determining the static priority and the basic dynamic priority of the data points according to the number and the types of the data points.
3) And storing the updated and released result data into a data storage module, and feeding the updated result information back to the real-time dynamic influence factor library. The updated result data comprises the updated data point value, the number of times of updating the data point within a certain time, the latest updating time of the data point, the latest change time of the data and the like, and the release result data comprises the last used time of the data, the number of times of releasing the data within a certain time and the like.
4) And updating the subscription and query information to the real-time dynamic influence factors. The subscription query information comprises data point subscription times, data point latest subscription time, query times of data points within a certain time, data point latest query time and the like.
5) Sending corresponding result data to a corresponding publishing interface according to the subscription and query information; the method specifically comprises the following steps: when receiving the query request, finding out corresponding query result data from the data stored in the data storage module, and outputting the query result data through a query interface; when the result data stored in the data storage module corresponding to the received subscription request changes, outputting the changed result data through an information publishing interface; and feeding back the query result information to the real-time dynamic influence factor library.
In addition, when the result data corresponding to the subscription and query request information received by the publishing interface changes, the subscription and query module publishes the real-time updated and published result data information acquired from the data storage module to the publishing interface, and feeds back the change information to the real-time dynamic influence factor library.
In the comprehensive monitoring system, after all data point data are changed, the data point data are updated to the comprehensive monitoring system through an updating interface; only when a user actively sends a query request, the query result can be obtained from the comprehensive monitoring system only by actively querying; after the comprehensive monitoring system receives the subscription request information, the comprehensive monitoring system can release the corresponding data point change information. The general integrated monitoring system has dozens to millions of points, and two to thirty thousand points of data information are updated every second under abnormal working conditions; each query or subscription request has only tens of points, and tens of subscription requests are opened, so that thousands of data points are required to be published simultaneously. According to the characteristic that the data updating concurrency of the comprehensive monitoring system is far greater than the data issuing concurrency of the query data, the updating interface is separated from the query interface, the updating interface is specially optimized, and the network flow is reduced.
While the invention has been described in terms of its preferred embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention.
Claims (10)
1. A large scale real-time data update distribution system for an integrated monitoring system, comprising:
the subscription inquiry module is used for receiving subscription and inquiry request information and outputting subscription and inquiry result information;
the real-time dynamic influence factor library is used for storing real-time dynamic influence factors;
the strategy synthesis module is used for generating a dynamic update release strategy according to the static update release strategy and the real-time dynamic influence factors;
the preprocessing module is used for preprocessing the data point data according to the dynamic update release strategy;
the strategy execution module is used for controlling the updating and the publishing of the preprocessed data point data according to the dynamic updating and publishing strategy;
and the data storage module is used for storing the result data which is updated and released in real time and sending the result data to the real-time dynamic influence factor library.
2. The large-scale real-time data updating and publishing system for the integrated monitoring system according to claim 1, wherein the subscription and query module receives subscription and query request information, and outputs corresponding result data in a query and information publishing interface mode after obtaining subscription and query result data in the data storage module; and feeding back the received subscription and query request information to the real-time dynamic influence factor library.
3. The large-scale real-time data updating and publishing system for the integrated monitoring system according to claim 1, wherein the dynamic updating and publishing strategy specifically comprises: if the data point is subscribed at present, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the subscription times and real-time dynamic influence factors except the subscription times; if the data point is inquired for many times in the latest period of time, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the inquiry times and real-time dynamic influence factors except the inquiry times; if the data point has a latest subscription or inquiry, updating the data point cannot be rejected or abandoned, and the priority is determined according to the latest subscription or inquiry time and real-time dynamic influence factors except the latest subscription time and the latest inquiry time; determining a special data point according to the characteristics of the data point and the data association relation, wherein the updating of the special data point must not be rejected or abandoned and is preferentially updated; adjusting the priority of the data points according to the updating result, the updating times and the updating time interval of the data points; and determining the current working condition according to the updating condition of the special points and the total concurrent updating data volume in a short time, and when the characteristic data updating occurs and the short-time concurrent updating data meets the requirement of the abnormal working condition, processing according to the strategy of the abnormal working condition.
4. The large-scale real-time data updating and publishing system for the integrated monitoring system as recited in claim 1, wherein the preprocessing module preprocesses the data point data according to the dynamic updating and publishing strategy, i.e. refusing data point data updating and directly abandoning data point data, and feeding back the result information to the real-time dynamic influence factor database.
5. The large-scale real-time data updating and publishing system for the integrated monitoring system as claimed in claim 1, wherein the policy executing module performs multi-thread processing on the preprocessed data point data according to the dynamic updating and publishing policy, updates and stores the real-time data point data to the data storage module, and then publishes the information, i.e. rejects, discards or directly publishes the data point data.
6. A large-scale real-time data updating and publishing method for an integrated monitoring system is characterized by comprising the following steps:
1) generating a dynamic update release strategy according to the static update release strategy and the real-time dynamic influence factors;
2) controlling the updating and the publishing of the real-time data point data according to the dynamic updating and publishing strategy, and feeding back the updating and publishing result data to a real-time dynamic influence factor library;
3) storing the updated and released result data;
4) updating the subscription and query information to real-time dynamic influence factors;
5) directly returning the query result to the query interface;
6) and finishing the information issuing state of the result data in the step 3) according to the dynamic updating issuing strategy.
7. The large-scale real-time data update distribution method for the integrated monitoring system according to claim 6, wherein the static update distribution policy in the step 1) comprises: rejecting data point data updating, directly abandoning data point data, processing data point data at low priority, processing data point data at normal processing, processing data point data at high priority and processing data point data at abnormal working condition.
8. The large-scale real-time data updating and publishing method for the integrated monitoring system according to claim 6, wherein the real-time dynamic influence factors in the step 1) are classified into four categories, one category is according to query and subscription conditions, and the category comprises data point subscription times, data point latest subscription time, query times within a certain time of data points, and data point latest query time; one is according to the preconditioning situation, including the total concurrent update quantity of short time, number of times of updating and data point recently updated in certain time; one is data processing situation, including data processing result, latest processing time; one is based on real-time result data storage, including data priority, data association relation, data last used time, data latest change time, and data update release result record in a certain time.
9. The large-scale real-time data updating and publishing method for the integrated monitoring system according to claim 6, wherein the dynamically updating and publishing strategy in the step 1) specifically comprises: if the data point is subscribed at present, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the subscription times and real-time dynamic influence factors except the subscription times; if the data point is inquired for many times in the latest period of time, updating of the data point cannot be rejected or abandoned, and the priority is determined according to the inquiry times and real-time dynamic influence factors except the inquiry times; if the data point has a latest subscription or inquiry, updating the data point cannot be rejected or abandoned, and the priority is determined according to the latest subscription or inquiry time and real-time dynamic influence factors except the latest subscription time and the latest inquiry time; determining a special data point according to the characteristics of the data point and the data association relation, wherein the updating of the special data point must not be rejected or abandoned and is preferentially updated; adjusting the priority of the data points according to the updating result, the updating times and the updating time interval of the data points; and determining the current working condition according to the updating condition of the special points and the total concurrent updating data volume in a short time, and when the characteristic data updating occurs and the short-time concurrent updating data meets the requirement of the abnormal working condition, processing according to the strategy of the abnormal working condition.
10. The large-scale real-time data updating and publishing method for the integrated monitoring system according to claim 6, wherein the step 2) specifically comprises: preprocessing data point data according to a dynamic update issuing strategy, namely rejecting data point data update and directly giving up data point data, and feeding back result information to a real-time dynamic influence factor library; and multithreading is carried out on the preprocessed data, the data of the real-time data point is updated and stored, then the information is issued, namely the data point data is refused, abandoned or directly issued, and the updated result information is fed back to the real-time dynamic influence factor library.
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