CN102929772A - Monitoring method and system of intelligent real-time system - Google Patents
Monitoring method and system of intelligent real-time system Download PDFInfo
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- CN102929772A CN102929772A CN2012103919447A CN201210391944A CN102929772A CN 102929772 A CN102929772 A CN 102929772A CN 2012103919447 A CN2012103919447 A CN 2012103919447A CN 201210391944 A CN201210391944 A CN 201210391944A CN 102929772 A CN102929772 A CN 102929772A
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Abstract
The invention provides a monitoring method and system of an intelligent real-time system. The method comprises the following steps of: S1, obtaining a scheduling grade corresponding to a scheduling time sheet of an existing intelligent real-time system; counting a real-time loading condition of the existing intelligent real-time system to judge that whether the existing intelligent real-time system exceeds a load or not or whether the system is abnormal or not; and S2, according to a judging result of the step S1, if determining that the existing intelligent real-time system exceeds the load or the system is abnormal, executing pre-treatment or initiatively extending the existing intelligent real-time system to obtain abnormal information of the existing intelligent real-time system; and if the existing intelligent real-time system does not exceed the load or the system is abnormal, continually monitoring the existing intelligent real-time system. When a resource of the system is lacked, the system condition can be reliably monitored and system abnormal information can be successfully obtained, so that the reliability of the system is improved; and corresponding information support is supplied to fault positioning of the system.
Description
[technical field]
The present invention relates to a kind of intelligent real-time system monitoring method and system, especially relate to a kind of intelligent real-time system monitoring method and system of high availability.
[background technology]
The real-time system monitoring technology of prior art usually is to support watchdog on the hardware, ceaselessly feeds dog (feeddog) by user's attitude program, the effect of doing like this is, when system resource lacked, feeddog can not get scheduling, and watchdog hardware can autoboot equipment after a period of time.Yet existing technical scheme is the meeting monitors failure when system resource is convertd by kernel and can't be obtained system call, and in addition, but hardware watchdog can reset automatically when system resource lacks can't obtain system exception information.
[summary of the invention]
The purpose of this invention is to provide a kind of intelligent real-time system monitoring method.The method based on data digging technology, solved the problem of the monitoring of legacy system when system resource is convertd by kernel monitors failure system call can't be obtained the time, and hardware watchdog when lacking, system resource can reset automatically and still can't obtain the problem of system exception information.
Another object of the present invention provides a kind of intelligent real-time system monitoring system.
Wherein, the intelligent real-time system monitoring method of an embodiment of the present invention may further comprise the steps:
S1, obtain current intelligent real-time system scheduling time sheet and dispatch accordingly grade, and add up the real-time loading condition of current intelligent real-time system, to judge whether current intelligent real-time system has surpassed load or system often leads;
S2, according to the S1 judged result, surpassed load or system exception if determine current intelligent real-time system, then carry out and defaultly process or current intelligent real-time system is initiatively opened up machine to obtain current intelligent real-time system abnormal information; If do not surpass load or system exception, then continue the current intelligent real-time system of monitoring.
As a further improvement on the present invention, described S1 step specifically comprises:
S11, add a HOOK in system time sheet scheduling part, this HOOK transmits the intelligent real-time system that a flags parameter is come in to registration;
S12, kernel module of increase, the HOOK that this module adds to the system time sheet scheduling part that increases registers one and monitors module;
After the particular task of S13, system time sheet scheduling particular schedule priority, this particular schedule priority is passed to described supervision module, and calls this supervision module;
S14, this timeslice of information calculations of transmitting according to HOOK are by the occupancy of the particular task of particular schedule priority;
S15, import flags into statistical module and add up accordingly; For after intelligence system monitoring corresponding Data support is provided;
S16, be that the system time sheet calls and adds up to flags;
S17, determine that according to the Information Statistics of cpu usage whether current intelligent real-time system has surpassed load or system leads often.
As a further improvement on the present invention, described S16 step specifically comprises:
S16, be that the system time sheet calls and adds up to flags; Only keeping last 10 seconds is 10*1000 statistics node; The Information Statistics of the situation that last 10 seconds CPU is used.
As a further improvement on the present invention, after the described S12 step, also comprise:
S13 ', time slice scheduling HOOK whenever are scheduled and carry out an internal memory detection for 500 times;
S14 ', by the cnt data of nonresident portion in the read apparatus UMA, obtain current memory usage;
S15 ', according to each testing result statistics, draw corresponding memory usage and trend.
Correspondingly, the intelligent real-time system monitoring system of an embodiment of the present invention comprises:
Detection module is used for obtaining current intelligent real-time system scheduling time sheet and dispatches accordingly grade, and adds up the real-time loading condition of current intelligent real-time system, to judge whether current intelligent real-time system has surpassed load or system often leads;
Execution module for the judged result according to detection module, has surpassed load or system exception if determine current intelligent real-time system, then carries out default processing or current intelligent real-time system is initiatively opened up machine to obtain current intelligent real-time system abnormal information; If do not surpass load or system exception, then continue the current intelligent real-time system of monitoring.
As a further improvement on the present invention, described detection module specifically is used for:
Add a HOOK in system time sheet scheduling part, this HOOK transmits the intelligent real-time system that a flags parameter is come in to registration;
Increase a kernel module, this module monitors module to one of the HOOK registration that the system time sheet scheduling part that increases adds;
After the particular task of system time sheet scheduling particular schedule priority, this particular schedule priority is passed to described supervision module, and calls this supervision module;
Transmit next this timeslice of information calculations by the occupancy of the particular task of particular schedule priority according to HOOK;
Importing flags into statistical module adds up accordingly; For after intelligence system monitoring corresponding Data support is provided;
Be that the system time sheet calls and adds up to flags;
Determine according to the Information Statistics of cpu usage whether current intelligent real-time system has surpassed load or system leads often.
As a further improvement on the present invention, described detection module specifically is used for:
Be that the system time sheet calls and adds up to flags; Only keeping last 10 seconds is 10*1000 statistics node; The Information Statistics of the situation that last 10 seconds CPU is used.
As a further improvement on the present invention, described detection module also is used for:
Time slice scheduling HOOK whenever is scheduled and carries out an internal memory detection for 500 times;
Cnt data by nonresident portion in the read apparatus UMA obtain current memory usage;
Testing result statistics according to each draws corresponding memory usage and trend.
Than prior art, the present invention realizes that in system be source reliable monitoring system situation and successfully obtain system exception information, the high reliability of raising system still when lacking; And provide corresponding information support for system failure location.
[description of drawings]
Fig. 1 is the process flow diagram of the intelligent real-time system monitoring method of one embodiment of the invention;
Fig. 2 is the module map of the intelligent real-time system monitoring system of one embodiment of the invention.
[embodiment]
In order to make the purpose, technical solutions and advantages of the present invention clearer, describe the present invention below in conjunction with the drawings and specific embodiments.
As shown in Figure 1, in an embodiment of the present invention, intelligent real-time system monitoring method may further comprise the steps:
S1, obtain current intelligent real-time system scheduling time sheet and dispatch accordingly grade, and add up the real-time loading condition of current intelligent real-time system, to judge whether current intelligent real-time system has surpassed load or system often leads; Preferably, before this step, also comprise: by revising intelligent real-time system time scheduling device so that intelligent real-time system to each scheduling time sheet call corresponding system detection module;
S2, according to the S1 judged result, surpassed load or system exception if determine current intelligent real-time system, then carry out and defaultly process or current intelligent real-time system is initiatively opened up machine to obtain current intelligent real-time system abnormal information; If do not surpass load or system exception, then continue the current intelligent real-time system of monitoring.Preferably, opening up machine has corresponding action to guarantee the external system normal operation before.
Preferably, in an embodiment of the present invention, described " adding up the real-time loading condition of current intelligent real-time system; to determine whether current intelligent real-time system has surpassed load or system leads often " specifically comprises the loading condition of adding up CPU and the loading condition of internal memory, load or system exception whether have been surpassed with CPU and/or the internal memory of determining current intelligent implementation system, wherein, described S1 step specifically comprises:
S11, add a HOOK in system time sheet scheduling part, this HOOK transmits the intelligent real-time system that a flags parameter is come in to registration; Preferably, even the characteristic of this HOOK is the operation endless loop of a high priority of intelligent real-time system, can guarantee that still this HOOK by intelligent real-time system normal consistency, has guaranteed high availability and the real-time of the method;
S12, kernel module of increase, the HOOK that this module adds to the system time sheet scheduling part that increases registers one and monitors module;
After the particular task of S13, system time sheet scheduling particular schedule priority, this particular schedule priority is passed to described supervision module, and call this supervision module, for example, when the system time sheet is dispatched to the A task, the dispatching priority of supposing the A task be the a(task priority be assumed to be a, b, c, idel (certainly be not limited to a, b, c, idel can expand a, b, c ..., idel)), after the A task is scheduled, monitor that then module is called subsequently, and can pass to the supervision module to a priority of A task;
S14, this timeslice of information calculations of transmitting according to HOOK are by the occupancy of the particular task of particular schedule priority; When if this particular task is system's idle task then flags is IDEL;
S15, import flags into statistical module and add up accordingly; For after intelligence system monitoring corresponding Data support is provided;
S16, be that the system time sheet calls and adds up to flags; Only keeping last 10 seconds is 10*1000 statistics node; The Information Statistics of the situation that last 10 seconds CPU is used;
S17, determine that according to the Information Statistics of cpu usage whether current intelligent real-time system has surpassed load or system leads often.
It is worth mentioning that: after the S12 step, also can insert and detect the internal memory step:
S13 ', time slice scheduling HOOK whenever are scheduled and carry out an internal memory detection for 500 times;
S14 ', to save as example in the UMA: can by the cnt data of nonresident portion in the read apparatus UMA, obtain current memory usage;
S15 ', according to each testing result statistics, (all then think on the rise rising continuous 5 times, continuous 5 times all descend then think be downtrending) draw corresponding memory usage and trend.
The S2 step specifically comprises according to the statistical information of above-mentioned CPU and/or internal memory judges that current intelligent real-time system has surpassed load or system exception, and carries out corresponding operating, is specially:
A) when the system business CPU usage reaches 95% (this value can be self-defined), temporarily stop the processing (can be self-defined, different operation systems has different demands) of related service;
B) when the system business CPU usage reaches this value of 80%(can be self-defined) and when also having a kind of trend of rising, cut off the business of part high priority;
C) as action b) after, when CPU usage is reduced to 60%, automatically recover the business (whether need recover, may lead the concussion of part industry such as automatic recovery if can set up on their own) of being cut off;
C) when there is task closed loop in system, initiatively open up machine by calling the panic method, all information of final system are kept, and orientation problem;
A) when using above 95%(, internal memory can customize); All business (can customize) of halt system;
B) when using above journey 85%(, internal memory can customize); The partial service of halt system (can customize);
C) as b) after the action, if internal memory gets back to 60% and return to recover corresponding business (whether need recover, may lead the concussion of part industry such as automatic recovery if can set up on their own) when also having downtrending.
As shown in Figure 2, in an embodiment of the present invention, intelligent real-time system monitoring system may further comprise the steps:
Detection module is used for obtaining current intelligent real-time system scheduling time sheet and dispatches accordingly grade, and adds up the real-time loading condition of current intelligent real-time system, to judge whether current intelligent real-time system has surpassed load or system often leads; Preferably, before this step, also comprise: by revising intelligent real-time system time scheduling device so that intelligent real-time system to each scheduling time sheet call corresponding system detection module;
Execution module for the judged result according to detection module, has surpassed load or system exception if determine current intelligent real-time system, then carries out default processing or current intelligent real-time system is initiatively opened up machine to obtain current intelligent real-time system abnormal information; If do not surpass load or system exception, then continue the current intelligent real-time system of monitoring.Preferably, opening up machine has corresponding action to guarantee the external system normal operation before.
Preferably, in an embodiment of the present invention, described detection module specifically is used for:
Add a HOOK in system time sheet scheduling part, this HOOK transmits the intelligent real-time system that a flags parameter is come in to registration; Preferably, even the characteristic of this HOOK is the operation endless loop of a high priority of intelligent real-time system, can guarantee that still this HOOK by intelligent real-time system normal consistency, has guaranteed high availability and the real-time of the method;
Increase a kernel module, this module monitors module to one of the HOOK registration that the system time sheet scheduling part that increases adds;
After the particular task of system time sheet scheduling particular schedule priority, this particular schedule priority is passed to described supervision module, and call this supervision module, for example, when the system time sheet is dispatched to the A task, the dispatching priority of supposing the A task be the a(task priority be assumed to be a, b, c, idel (certainly be not limited to a, b, c, idel can expand a, b, c ..., idel)), after the A task is scheduled, monitor that then module is called subsequently, and can pass to the supervision module to a priority of A task;
Transmit next this timeslice of information calculations by the occupancy of the particular task of particular schedule priority according to HOOK; When if this particular task is system's idle task then flags is IDEL;
Importing flags into statistical module adds up accordingly; For after intelligence system monitoring corresponding Data support is provided;
Be that the system time sheet calls and adds up to flags; Only keeping last 10 seconds is 10*1000 statistics node; The Information Statistics of the situation that last 10 seconds CPU is used;
Determine according to the Information Statistics of cpu usage whether current intelligent real-time system has surpassed load or system leads often.
It is worth mentioning that: described detection module is also for detection of internal memory:
Time slice scheduling HOOK whenever is scheduled and carries out an internal memory detection for 500 times;
To save as example in the UMA: can by the cnt data of nonresident portion in the read apparatus UMA, obtain current memory usage;
According to each testing result statistics, and (all then think on the rise rising continuous 5 times, continuous 5 times all descend then think be downtrending) draw corresponding memory usage and trend.
Described execution module can judge that current intelligent real-time system has surpassed load or system exception according to the statistical information of above-mentioned CPU and/or internal memory, and carries out corresponding operating, specifically is used for:
A) when the system business CPU usage reaches 95% (this value can be self-defined), temporarily stop the processing (can be self-defined, different operation systems has different demands) of related service;
B) when the system business CPU usage reaches this value of 80%(can be self-defined) and when also having a kind of trend of rising, cut off the business of part high priority;
C) as action b) after, when CPU usage is reduced to 60%, automatically recover the business (whether need recover, may lead the concussion of part industry such as automatic recovery if can set up on their own) of being cut off;
C) when there is task closed loop in system, initiatively open up machine by calling the panic method, all information of final system are kept, and orientation problem;
A) when using above 95%(, internal memory can customize); All business (can customize) of halt system;
B) when using above journey 85%(, internal memory can customize); The partial service of halt system (can customize);
C) as b) after the action, if internal memory gets back to 60% and return to recover corresponding business (whether need recover, may lead the concussion of part industry such as automatic recovery if can set up on their own) when also having downtrending.
In sum, the present invention realizes that in system be source reliable monitoring system situation and successfully obtain system exception information, the high reliability of raising system still when lacking; And provide corresponding information support for system failure location.
Be to be understood that, although this instructions is described according to embodiment, but be not that each embodiment only comprises an independently technical scheme, this narrating mode of instructions only is for clarity sake, those skilled in the art should make instructions as a whole, technical scheme in each embodiment also can through appropriate combination, form other embodiments that it will be appreciated by those skilled in the art that.
Above listed a series of detailed description only is specifying for feasibility embodiment of the present invention; they are not to limit protection scope of the present invention, allly do not break away from equivalent embodiment or the change that skill spirit of the present invention does and all should be included within protection scope of the present invention.
Claims (8)
1. an intelligent real-time system monitoring method is characterized in that, described method comprises:
S1, obtain current intelligent real-time system scheduling time sheet and dispatch accordingly grade, and add up the real-time loading condition of current intelligent real-time system, to judge whether current intelligent real-time system has surpassed load or system often leads;
S2, according to the S1 judged result, surpassed load or system exception if determine current intelligent real-time system, then carry out and defaultly process or current intelligent real-time system is initiatively opened up machine to obtain current intelligent real-time system abnormal information; If do not surpass load or system exception, then continue the current intelligent real-time system of monitoring.
2. intelligent real-time system monitoring method according to claim 1 is characterized in that, described S1 step specifically comprises:
S11, add a HOOK in system time sheet scheduling part, this HOOK transmits the intelligent real-time system that a flags parameter is come in to registration;
S12, kernel module of increase, the HOOK that this module adds to the system time sheet scheduling part that increases registers one and monitors module;
After the particular task of S13, system time sheet scheduling particular schedule priority, this particular schedule priority is passed to described supervision module, and calls this supervision module;
S14, this timeslice of information calculations of transmitting according to HOOK are by the occupancy of the particular task of particular schedule priority;
S15, import flags into statistical module and add up accordingly; For after intelligence system monitoring corresponding Data support is provided;
S16, be that the system time sheet calls and adds up to flags;
S17, determine that according to the Information Statistics of cpu usage whether current intelligent real-time system has surpassed load or system leads often.
3. intelligent real-time system monitoring method according to claim 2 is characterized in that, described S16 step specifically comprises:
S16, be that the system time sheet calls and adds up to flags; Only keeping last 10 seconds is 10*1000 statistics node; The Information Statistics of the situation that last 10 seconds CPU is used.
4. intelligent real-time system monitoring method according to claim 2 is characterized in that, after the described S12 step, also comprises:
S13 ', time slice scheduling HOOK whenever are scheduled and carry out an internal memory detection for 500 times;
S14 ', by the cnt data of nonresident portion in the read apparatus UMA, obtain current memory usage;
S15 ', according to each testing result statistics, draw corresponding memory usage and trend.
5. an intelligent real-time system monitoring system is characterized in that, described system comprises:
Detection module is used for obtaining current intelligent real-time system scheduling time sheet and dispatches accordingly grade, and adds up the real-time loading condition of current intelligent real-time system, to judge whether current intelligent real-time system has surpassed load or system often leads;
Execution module for the judged result according to detection module, has surpassed load or system exception if determine current intelligent real-time system, then carries out default processing or current intelligent real-time system is initiatively opened up machine to obtain current intelligent real-time system abnormal information; If do not surpass load or system exception, then continue the current intelligent real-time system of monitoring.
6. intelligent real-time system monitoring system according to claim 5 is characterized in that, described detection module specifically is used for:
Add a HOOK in system time sheet scheduling part, this HOOK transmits the intelligent real-time system that a flags parameter is come in to registration;
Increase a kernel module, this module monitors module to one of the HOOK registration that the system time sheet scheduling part that increases adds;
After the particular task of system time sheet scheduling particular schedule priority, this particular schedule priority is passed to described supervision module, and calls this supervision module;
Transmit next this timeslice of information calculations by the occupancy of the particular task of particular schedule priority according to HOOK;
Importing flags into statistical module adds up accordingly; For after intelligence system monitoring corresponding Data support is provided;
Be that the system time sheet calls and adds up to flags;
Determine according to the Information Statistics of cpu usage whether current intelligent real-time system has surpassed load or system leads often.
7. intelligent real-time system monitoring system according to claim 6 is characterized in that, described detection module specifically is used for:
Be that the system time sheet calls and adds up to flags; Only keeping last 10 seconds is 10*1000 statistics node; The Information Statistics of the situation that last 10 seconds CPU is used.
8. intelligent real-time system monitoring system according to claim 6 is characterized in that, described detection module also is used for:
Time slice scheduling HOOK whenever is scheduled and carries out an internal memory detection for 500 times;
Cnt data by nonresident portion in the read apparatus UMA obtain current memory usage;
Testing result statistics according to each draws corresponding memory usage and trend.
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| CN109117141A (en) * | 2018-09-04 | 2019-01-01 | 深圳市木瓜移动科技有限公司 | Simplify method, apparatus, the electronic equipment, computer readable storage medium of programming |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104780393A (en) * | 2015-04-10 | 2015-07-15 | 天脉聚源（北京）教育科技有限公司 | Method and device for allocating resources |
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| CN109117141A (en) * | 2018-09-04 | 2019-01-01 | 深圳市木瓜移动科技有限公司 | Simplify method, apparatus, the electronic equipment, computer readable storage medium of programming |
| CN109117141B (en) * | 2018-09-04 | 2021-09-24 | 深圳市木瓜移动科技有限公司 | Method, device, electronic equipment and computer readable storage medium for simplifying programming |
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Application publication date: 20130213 |