CN117914833A - Health analysis method, device and storage medium of broadcast system - Google Patents
Health analysis method, device and storage medium of broadcast system Download PDFInfo
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- 230000036541 health Effects 0.000 title claims abstract description 115
- 238000004458 analytical method Methods 0.000 title claims abstract description 76
- 238000003745 diagnosis Methods 0.000 claims abstract description 367
- 230000000977 initiatory effect Effects 0.000 claims abstract description 30
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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
- H04L65/60—Network streaming of media packets
- H04L65/61—Network streaming of media packets for supporting one-way streaming services, e.g. Internet radio
- H04L65/611—Network streaming of media packets for supporting one-way streaming services, e.g. Internet radio for multicast or broadcast
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/069—Management of faults, events, alarms or notifications using logs of notifications; Post-processing of notifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/06—Selective distribution of broadcast services, e.g. multimedia broadcast multicast service [MBMS]; Services to user groups; One-way selective calling services
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Abstract
The invention discloses a health analysis method, a device and a storage medium of a broadcasting system, wherein the method comprises the following steps: responding to a request for health diagnosis of a broadcasting system, acquiring server logs of a broadcasting server, front-end equipment and network node equipment, performing error analysis on each server log, and generating white box diagnosis parameters; initiating a black box diagnosis request to a broadcasting server, indicating the broadcasting server to send a black box diagnosis instruction to front-end equipment, and generating black box diagnosis parameters after the front-end equipment executes the black box diagnosis instruction; trend analysis is carried out on the white box diagnostic parameters and the black box diagnostic parameters, so that trend diagnostic parameters are generated; initiating a risk diagnosis request to a broadcast server, and generating risk diagnosis parameters after the broadcast server executes a risk diagnosis instruction; and calculating the health degree value of the broadcasting system according to the white box diagnosis parameter, the black box diagnosis parameter, the trend diagnosis parameter and the risk diagnosis parameter, and generating a health diagnosis result so as to improve the availability and reliability of the broadcasting system.
Description
Technical Field
The present invention relates to the field of public broadcasting technologies, and in particular, to a method and apparatus for health analysis of a broadcasting system, and a storage medium.
Background
The existing public broadcasting systems all adopt a post-analysis method, and the problem analysis can be performed only when problems or faults occur. The existing methods such as log recording are used for analyzing the problems and restoring the reasons of faults. However, the current public broadcasting system is discrete log records, such as a software system log, an operating system log and a switch network equipment log, are all running logs of the module, and do not have global records, so that the problem analysis accuracy of the current public broadcasting system is low, and the occurrence of the problem is difficult to predict.
Disclosure of Invention
The invention provides a health analysis method, a health analysis device and a storage medium of a broadcasting system, which are used for improving the usability and reliability of the broadcasting system.
The invention provides a health analysis method of a broadcasting system, which is applied to a diagnosis server, wherein the broadcasting system comprises the diagnosis server, a broadcasting server, front-end equipment and network node equipment; the diagnosis server is respectively in communication connection with the broadcasting server, the front-end equipment and the network node equipment;
The health analysis method comprises the following steps:
Responding to a request for health diagnosis of a broadcasting system, respectively acquiring server logs of a broadcasting server, front-end equipment and network node equipment, and performing error analysis on each server log to generate white box diagnosis parameters;
Initiating a black box diagnosis request to the broadcasting server, and indicating the broadcasting server to send a black box diagnosis instruction to the front-end equipment so that the front-end equipment returns black box diagnosis result parameters to a diagnosis server after executing the black box diagnosis instruction;
Taking the diagnosis result parameter returned by the front-end equipment as a black box diagnosis parameter;
trend analysis is carried out on the white box diagnostic parameters and the black box diagnostic parameters, and trend diagnostic parameters are generated;
initiating a risk diagnosis request to the broadcast server so that the broadcast server returns a risk diagnosis result parameter to a diagnosis server after executing a risk diagnosis instruction;
Taking the risk diagnosis result parameter returned by the broadcast server as a risk diagnosis parameter;
and calculating the health value of the broadcasting system according to the white box diagnosis parameter, the black box diagnosis parameter, the trend diagnosis parameter and the risk diagnosis parameter to generate a health diagnosis result.
Further, performing error analysis on each server log to generate white box diagnosis parameters, which specifically include:
Counting the number of warning logs and the number of error logs in each server log; and carrying out weighted summation operation after configuring corresponding weights for the number of the warning logs and the number of the error logs, and generating white box diagnosis parameters.
Further, the step of initiating a black box diagnosis request to the broadcast server, instructing the broadcast server to send a black box diagnosis instruction to the front-end device, so that after the front-end device executes the black box diagnosis instruction, the black box diagnosis result parameter is returned to the diagnosis server, and specifically includes:
Initiating a black box diagnosis request to the broadcasting server, and indicating the broadcasting server to send a black box diagnosis instruction to the front-end equipment so that the broadcasting function is detected after the front-end equipment executes the black box diagnosis instruction; the broadcasting function includes: task execution function, sound playing function and volume feedback function; each of the broadcast functions is configured with a corresponding standard;
and calculating the score of the broadcasting function of the front-end equipment according to the standard of each broadcasting function, and returning the score as a black box diagnosis result parameter to a diagnosis server.
Further, the trend analysis is performed on the white box diagnostic parameter and the black box diagnostic parameter to generate trend diagnostic parameters, which specifically are:
Counting fault data in the white box diagnosis parameters and the black box diagnosis parameters within a preset time period; generating a corresponding growth model according to the growth trend of each fault data; and taking the product of each fault data and the corresponding growth model as a trend value of each fault data, and combining the trend values of all the fault data to generate a trend diagnosis parameter.
Further, the step of initiating a risk diagnosis request to the broadcast server, so that after the broadcast server executes a risk diagnosis instruction, the risk diagnosis result parameter is returned to the diagnosis server, specifically:
Initiating a risk diagnosis request to the broadcast server so that the broadcast server calculates the fault times of a fault source according to the fault data; and generating a risk diagnosis result parameter according to the fault frequency of each fault source, and returning the risk diagnosis result parameter to the diagnosis server.
Further, the calculating the health value of the broadcasting system according to the white box diagnostic parameter, the black box diagnostic parameter, the trend diagnostic parameter and the risk diagnostic parameter, and generating a health diagnostic result specifically includes:
the white box diagnosis parameters, the black box diagnosis parameters, the trend diagnosis parameters and the risk diagnosis parameters are configured with corresponding weights and then subjected to weighted summation operation to generate health parameters;
generating a health degree value as a health diagnosis result according to the health parameters;
the health value is expressed as follows: h=100- { i=1 } { n } f_i } { w_i;
Wherein H is a health value, f_i is a value of an i-th diagnostic parameter, and the diagnostic parameter is a white-box diagnostic parameter, a black-box diagnostic parameter, a trend diagnostic parameter or a risk diagnostic parameter; w_i is the weight of the ith diagnostic parameter; Σ_ { i=1 } { n } is a weighted sum of the 1 st to nth diagnostic parameters; n is the total number of diagnostic parameters.
As a preferred scheme, the invention changes the defect that the current industry is post fault analysis in a predictive mode, and starts from the health degree of the system, the broadcasting system is subjected to health analysis, and a health degree value is generated as a health diagnosis result to remind relevant operation and maintenance personnel to solve the fault problem in time instead of processing after the system is paralyzed, so that the availability and reliability of the broadcasting system are improved. In addition, from the global system, the invention considers the matching problem between modules, performs overall analysis on the broadcasting server, the front-end equipment and the network node equipment, and improves the global availability of the broadcasting system.
Additional features and advantages of the invention will be set forth in the detailed description which follows.
Correspondingly, the invention also provides a health analysis device of the broadcasting system, which is applied to the diagnosis server, wherein the broadcasting system comprises the diagnosis server, the broadcasting server, the front-end equipment and the network node equipment; the diagnosis server is respectively in communication connection with the broadcasting server, the front-end equipment and the network node equipment;
The health analysis device includes: the system comprises a white box diagnosis module, a black box diagnosis module, a trend diagnosis module, a risk diagnosis module and a health analysis module;
the white box diagnosis module is used for respectively acquiring server logs of the broadcasting server, the front-end equipment and the network node equipment, carrying out error analysis on each server log and generating white box diagnosis parameters;
The black box diagnosis module is used for initiating a black box diagnosis request to the broadcast server, instructing the broadcast server to send a black box diagnosis instruction to the front-end equipment, so that the front-end equipment returns black box diagnosis result parameters to the diagnosis server after executing the black box diagnosis instruction;
Taking the diagnosis result parameter returned by the front-end equipment as a black box diagnosis parameter;
The trend diagnosis module is used for carrying out trend analysis on the white box diagnosis parameters and the black box diagnosis parameters to generate trend diagnosis parameters;
The risk diagnosis module is used for initiating a risk diagnosis request to the broadcast server so that the broadcast server returns risk diagnosis result parameters to the diagnosis server after executing a risk diagnosis instruction;
Taking the risk diagnosis result parameter returned by the broadcast server as a risk diagnosis parameter;
The health analysis module is used for calculating the health value of the broadcasting system according to the white box diagnosis parameter, the black box diagnosis parameter, the trend diagnosis parameter and the risk diagnosis parameter, and generating a health diagnosis result.
Further, the health analysis module comprises an analysis unit;
The analysis unit is used for carrying out weighted summation operation on the white box diagnosis parameters, the black box diagnosis parameters, the trend diagnosis parameters and the risk diagnosis parameters after corresponding weights are configured, so as to generate health parameters;
generating a health degree value as a health diagnosis result according to the health parameters;
the health value is expressed as follows: h=100- { i=1 } { n } f_i } { w_i;
Wherein H is a health value, f_i is a value of an i-th diagnostic parameter, and the diagnostic parameter is a white-box diagnostic parameter, a black-box diagnostic parameter, a trend diagnostic parameter or a risk diagnostic parameter; w_i is the weight of the ith diagnostic parameter; Σ_ { i=1 } { n } is a weighted sum of the 1 st to nth diagnostic parameters; n is the total number of diagnostic parameters.
Correspondingly, the invention also provides a broadcasting system, which comprises: the system comprises a diagnosis server, a broadcasting server, front-end equipment and network node equipment; the diagnosis server is respectively in communication connection with the broadcasting server, the front-end equipment and the network node equipment;
the diagnosis server is used for responding to a request for health diagnosis of the broadcasting system, respectively obtaining server logs of the broadcasting server, the front-end equipment and the network node equipment, carrying out error analysis on each server log and generating white box diagnosis parameters;
Initiating a black box diagnosis request to the broadcasting server, and indicating the broadcasting server to send a black box diagnosis instruction to the front-end equipment so that the front-end equipment returns black box diagnosis result parameters to a diagnosis server after executing the black box diagnosis instruction;
Taking the diagnosis result parameter returned by the front-end equipment as a black box diagnosis parameter;
trend analysis is carried out on the white box diagnostic parameters and the black box diagnostic parameters, and trend diagnostic parameters are generated;
initiating a risk diagnosis request to the broadcast server so that the broadcast server returns a risk diagnosis result parameter to a diagnosis server after executing a risk diagnosis instruction;
Taking the risk diagnosis result parameter returned by the broadcast server as a risk diagnosis parameter;
and calculating the health value of the broadcasting system according to the white box diagnosis parameter, the black box diagnosis parameter, the trend diagnosis parameter and the risk diagnosis parameter to generate a health diagnosis result.
Accordingly, the present invention also provides a computer-readable storage medium including a stored computer program; wherein the computer program, when running, controls the device in which the computer readable storage medium is located to execute a method for health analysis of a broadcast system according to the present disclosure.
Drawings
FIG. 1 is a flow chart of an embodiment of a method for health analysis of a broadcast system provided by the present invention;
Fig. 2 is a schematic structural diagram of an embodiment of a broadcasting system provided by the present invention;
fig. 3 is a schematic structural diagram of an embodiment of a health analysis device of a broadcasting system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1, a health analysis method of a broadcast system provided by an embodiment of the present invention is applied to a diagnostic server, where the broadcast system includes a diagnostic server, a broadcast server, a front-end device and a network node device; the diagnosis server is respectively in communication connection with the broadcasting server, the front-end equipment and the network node equipment; the method comprises the steps of S101-S103:
Step S101: responding to a request for health diagnosis of a broadcasting system, respectively acquiring server logs of a broadcasting server, front-end equipment and network node equipment, and performing error analysis on each server log to generate white box diagnosis parameters;
Further, performing error analysis on each server log to generate white box diagnosis parameters, which specifically include:
Counting the number of warning logs and the number of error logs in each server log; and carrying out weighted summation operation after configuring corresponding weights for the number of the warning logs and the number of the error logs, and generating white box diagnosis parameters.
In this embodiment, referring to fig. 2, the broadcasting system includes a diagnosis server, a broadcasting server, a front-end device, and a network node device; the front-end equipment comprises N front-end horns; the network node equipment is respectively and directly connected with the diagnosis server, the broadcasting server and the N front-end horns; the diagnosis server is respectively in communication connection with the broadcasting server, the N front-end horns and the network node equipment.
In this embodiment, the broadcast server, the N front-end horns, and the network node devices are monitored points, and the diagnostic server may monitor the server logs of each module, so as to obtain warning logs and error logs in each server log; and counting the number of warning logs and the number of error logs, wherein the duty ratio weight of the error logs is 70%, the duty ratio weight of the warning class is 30%, and performing weighted summation operation according to the respective duty ratio weights to generate a white box diagnosis parameter f_1.
Step S102: initiating a black box diagnosis request to the broadcasting server, and indicating the broadcasting server to send a black box diagnosis instruction to the front-end equipment so that the front-end equipment returns black box diagnosis result parameters to a diagnosis server after executing the black box diagnosis instruction; taking the diagnosis result parameter returned by the front-end equipment as a black box diagnosis parameter;
Further, the step of initiating a black box diagnosis request to the broadcast server, instructing the broadcast server to send a black box diagnosis instruction to the front-end device, so that after the front-end device executes the black box diagnosis instruction, the black box diagnosis result parameter is returned to the diagnosis server, and specifically includes:
Initiating a black box diagnosis request to the broadcasting server, and indicating the broadcasting server to send a black box diagnosis instruction to the front-end equipment so that the broadcasting function is detected after the front-end equipment executes the black box diagnosis instruction; the broadcasting function includes: task execution function, sound playing function and volume feedback function; each of the broadcast functions is configured with a corresponding standard;
and calculating the score of the broadcasting function of the front-end equipment according to the standard of each broadcasting function, and returning the score as a black box diagnosis result parameter to a diagnosis server.
In this embodiment, when a black box diagnosis request is initiated to the broadcast server, the diagnosis server sends a black box diagnosis instruction to the broadcast server, and when the broadcast server receives the black box diagnosis request and the black box diagnosis instruction, the broadcast server issues the black box diagnosis instruction to each front-end device, that is, issues the black box diagnosis instruction to N front-end horns respectively, and instructs the front-end devices to execute the black box diagnosis instruction. When N front-end horns receive the black box diagnosis instruction and the instruction of the broadcasting server, the black box diagnosis instruction is executed, and the broadcasting function detection mainly comprises the following steps: whether the task is normally executed, whether the sound is normally played and whether the volume feedback value is normal.
The black box diagnosis instruction comprises a plurality of test instructions, each test instruction correspondingly detects a broadcasting function, each test instruction has a qualified standard, for example, the network quality requirement delay of a broadcasting level is lower than 10 milliseconds, the packet loss rate is lower than 0.03 percent, and the jitter is lower than 10ms; the end audio requires a decay rate of less than 3%, etc. When the broadcasting functions are detected, according to the passing or failing of the broadcasting functions, each broadcasting function generates a corresponding score, the scores of all the broadcasting functions are combined, and each front-end loudspeaker generates an overall score of the broadcasting function.
And combining the scores of the N front-end horns to obtain the total score of the broadcasting function of the front-end equipment, and returning the score to the diagnosis server as the black box diagnosis parameter f_2.
The method uniformly considers the integral damage of the server, the equipment, the network node and the transmission line, discovers the short board in time, and avoids the defect that the bandwidth of the tail end is less than hundred megabytes because of the low-end network cable or the construction problem of the gigabit high-end switch.
Step S103: trend analysis is carried out on the white box diagnostic parameters and the black box diagnostic parameters, and trend diagnostic parameters are generated;
further, the trend analysis is performed on the white box diagnostic parameter and the black box diagnostic parameter to generate trend diagnostic parameters, which specifically are:
Counting fault data in the white box diagnosis parameters and the black box diagnosis parameters within a preset time period; generating a corresponding growth model according to the growth trend of each fault data; and taking the product of each fault data and the corresponding growth model as a trend value of each fault data, and combining the trend values of all the fault data to generate a trend diagnosis parameter.
In this embodiment, analyzing the growth trend of each fault data F (F e R) according to the unit of 24 hours, and generating a corresponding growth model; the growth model includes: constant growth, linear growth, and exponential growth.
The growth model mapping function G is { constant growth, linear growth, exponential growth } - {1,2,4};
Calculating a trend value of each fault data, wherein the expression of the trend value T is as follows: t (F, G) =f×g.
And merging trend values of all the fault data to generate a trend diagnosis parameter f_3, and returning the trend diagnosis parameter f_3 to the diagnosis server.
Step S104: initiating a risk diagnosis request to the broadcast server so that the broadcast server returns a risk diagnosis result parameter to a diagnosis server after executing a risk diagnosis instruction; taking the risk diagnosis result parameter returned by the broadcast server as a risk diagnosis parameter;
Further, the step of initiating a risk diagnosis request to the broadcast server, so that after the broadcast server executes a risk diagnosis instruction, the risk diagnosis result parameter is returned to the diagnosis server, specifically:
Initiating a risk diagnosis request to the broadcast server so that the broadcast server calculates the fault times of a fault source according to the fault data; and generating a risk diagnosis result parameter according to the fault frequency of each fault source, and returning the risk diagnosis result parameter to the diagnosis server.
In this embodiment, the fault sources include: exposed terminal security vulnerabilities, defective software and defective hardware, etc. According to the fault frequency of each fault source, the potential fault which is burst can be analyzed, for example, the fault rate of a batch of raw materials is 10%, manufacturers know and confirm that the related problems are not exposed on the project, if the project is a high-reliability place such as a college entrance examination place or an airport, the batch of equipment can be replaced completely because of 10% hidden danger, and other places with low requirements such as parks can be used continuously. And returning the analyzed failure rate of the raw material of the certain batch to the diagnosis server as a risk diagnosis result parameter f_4.
Step S105: and calculating the health value of the broadcasting system according to the white box diagnosis parameter, the black box diagnosis parameter, the trend diagnosis parameter and the risk diagnosis parameter to generate a health diagnosis result.
Further, the calculating the health value of the broadcasting system according to the white box diagnostic parameter, the black box diagnostic parameter, the trend diagnostic parameter and the risk diagnostic parameter, and generating a health diagnostic result specifically includes:
the white box diagnosis parameters, the black box diagnosis parameters, the trend diagnosis parameters and the risk diagnosis parameters are configured with corresponding weights and then subjected to weighted summation operation to generate health parameters;
generating a health degree value as a health diagnosis result according to the health parameters;
the health value is expressed as follows: h=100- { i=1 } { n } f_i } { w_i;
Wherein H is a health value, f_i is a value of an i-th diagnostic parameter, and the diagnostic parameter is a white-box diagnostic parameter, a black-box diagnostic parameter, a trend diagnostic parameter or a risk diagnostic parameter; w_i is the weight of the ith diagnostic parameter; Σ_ { i=1 } { n } is a weighted sum of the 1 st to nth diagnostic parameters; n is the total number of diagnostic parameters.
In the present embodiment, the 1 st to 4 th diagnostic parameters are a white-box diagnostic parameter, a black-box diagnostic parameter, a trend diagnostic parameter, and a risk diagnostic parameter in this order, w_ 1=30%; w_2=30%; w_3=30%; w_4=10%. Specific numerical values can be adjusted according to actual conditions of projects after project debugging is completed, for example, on-site network construction is poor, networking equipment performance is low, probability of occurrence of problems is high, and then the duty ratio of the risk analysis module is high.
The prior art has the following disadvantages:
defect one: post hoc analysis. Along with the rapid development of rail transit, the traffic travel is more convenient and rapid, the traffic of the high-speed rail station and the traffic of people in the public places at airports are exponentially increased year by year, and public broadcasting is used as a channel for forcedly issuing information and plays a key role in people-stream dense places. The reliability and availability of public broadcasting present new challenges, and traditional broadcasting is post analysis after failure, which not only affects usage but also causes serious social impact.
Defect two: the states of the modules work individually. The current public broadcasting is generally divided into three parts of a background server, an intermediate transmission network and a front-end loudspeaker device, each part is formed by combining sub-modules or sub-systems, for example, the background server is formed by combining an operating system, broadcasting server software (the broadcasting server software is formed by combining a plurality of modules such as a front-end client, a relay server, a logic server, a service server and the like), the intermediate network part is provided with a core switch, a firewall, a fort machine, a two-layer switch and the like, and the front end is formed by combining various modules such as a power amplifier, a loudspeaker, an embedded system and the like. At present, the modules record the running log of the module, and feedback is not provided for the availability of the whole broadcasting system.
Defect three: the backup system is not necessarily emergency-ready. The prior public broadcasting system has the means for improving the stability and the usability by using backup systems, such as hot backup, cold backup, switch stacking backup, speaker AB backup, power amplifier 2 primary-backup, 4 primary-backup, 1 secondary-backup, 8 primary-backup and the like. Although theoretical values such as MTTF (mean time between failure), MTTR (mean time between repair) and the like are improved, the backup system often fails before the main system in actual projects, so that the dilemma that the broadcasting system still cannot be used when the backup scheme is actually started is caused.
The implementation of the embodiment of the invention has the following effects:
The invention changes the defect that the current industry is post fault analysis in a predictive mode, starts from the health degree of the system, carries out health analysis on the broadcasting system, generates a health degree value as a health diagnosis result, reminds relevant operation and maintenance personnel to solve the fault problem in time, does not carry out treatment after the system is paralyzed, and improves the availability and reliability of the broadcasting system. In addition, from the global system, the invention considers the matching problem between modules, performs overall analysis on the broadcasting server, the front-end equipment and the network node equipment, and improves the global availability of the broadcasting system.
Example two
Referring to fig. 3, a health analysis device of a broadcasting system according to an embodiment of the present invention is applied to a diagnosis server, where the broadcasting system includes the diagnosis server, a broadcasting server, a front-end device and a network node device; the diagnosis server is respectively in communication connection with the broadcasting server, the front-end equipment and the network node equipment;
The health analysis device includes: a white box diagnostic module 201, a black box diagnostic module 202, a trend diagnostic module 203, a risk diagnostic module 204, and a health analysis module 205;
the white box diagnosis module is used for respectively acquiring server logs of the broadcasting server, the front-end equipment and the network node equipment, carrying out error analysis on each server log and generating white box diagnosis parameters;
The black box diagnosis module is used for initiating a black box diagnosis request to the broadcast server, instructing the broadcast server to send a black box diagnosis instruction to the front-end equipment, so that the front-end equipment returns black box diagnosis result parameters to the diagnosis server after executing the black box diagnosis instruction;
Taking the diagnosis result parameter returned by the front-end equipment as a black box diagnosis parameter;
The trend diagnosis module is used for carrying out trend analysis on the white box diagnosis parameters and the black box diagnosis parameters to generate trend diagnosis parameters;
The risk diagnosis module is used for initiating a risk diagnosis request to the broadcast server so that the broadcast server returns risk diagnosis result parameters to the diagnosis server after executing a risk diagnosis instruction;
Taking the risk diagnosis result parameter returned by the broadcast server as a risk diagnosis parameter;
The health analysis module is used for calculating the health value of the broadcasting system according to the white box diagnosis parameter, the black box diagnosis parameter, the trend diagnosis parameter and the risk diagnosis parameter, and generating a health diagnosis result.
Further, the white-box diagnostic module includes: a white box diagnosis unit;
The white box diagnosis unit is used for counting the number of warning logs and the number of error logs in each server log; and carrying out weighted summation operation after configuring corresponding weights for the number of the warning logs and the number of the error logs, and generating white box diagnosis parameters.
Further, the black box diagnostic module includes: a black box diagnosis unit;
The black box diagnosis unit is used for initiating a black box diagnosis request to the broadcast server, instructing the broadcast server to send a black box diagnosis instruction to the front-end equipment, so that the front-end equipment detects a broadcast function after executing the black box diagnosis instruction; the broadcasting function includes: task execution function, sound playing function and volume feedback function; each of the broadcast functions is configured with a corresponding standard;
and calculating the score of the broadcasting function of the front-end equipment according to the standard of each broadcasting function, and returning the score as a black box diagnosis result parameter to a diagnosis server.
Further, the trend diagnosis module includes: a trend diagnosis unit;
The trend diagnosis unit is used for counting fault data in the white box diagnosis parameters and the black box diagnosis parameters within a preset time period; generating a corresponding growth model according to the growth trend of each fault data; and taking the product of each fault data and the corresponding growth model as a trend value of each fault data, and combining the trend values of all the fault data to generate a trend diagnosis parameter.
Further, the risk diagnosis module includes: a risk diagnosis unit;
The risk diagnosis unit is used for initiating a risk diagnosis request to the broadcast server so that the broadcast server calculates the fault times of a fault source according to the fault data; and generating a risk diagnosis result parameter according to the fault frequency of each fault source, and returning the risk diagnosis result parameter to the diagnosis server.
Further, the health analysis module includes: a health analysis unit;
The health analysis unit is used for carrying out weighted summation operation on the white box diagnosis parameters, the black box diagnosis parameters, the trend diagnosis parameters and the risk diagnosis parameters after corresponding weights are configured, so as to generate health parameters;
generating a health degree value as a health diagnosis result according to the health parameters;
the health value is expressed as follows: h=100- { i=1 } { n } f_i } { w_i;
Wherein H is a health value, f_i is a value of an i-th diagnostic parameter, and the diagnostic parameter is a white-box diagnostic parameter, a black-box diagnostic parameter, a trend diagnostic parameter or a risk diagnostic parameter; w_i is the weight of the ith diagnostic parameter; Σ_ { i=1 } { n } is a weighted sum of the 1 st to nth diagnostic parameters; n is the total number of diagnostic parameters.
The health analysis device of the broadcasting system can implement the health analysis method of the broadcasting system of the method embodiment. The options in the method embodiments described above are also applicable to this embodiment and will not be described in detail here. The rest of the embodiments of the present application may refer to the content of the above method embodiments, and in this embodiment, no further description is given.
Example III
Correspondingly, the invention further provides a computer readable storage medium, which comprises a stored computer program, wherein the computer program is used for controlling equipment where the computer readable storage medium is located to execute the health analysis method of the broadcasting system according to any embodiment.
The computer program may be divided into one or more modules/units, which are stored in the memory and executed by the processor to accomplish the present invention, for example. The one or more modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments are used for describing the execution of the computer program in the terminal device.
The terminal equipment can be computing equipment such as a desktop computer, a notebook computer, a palm computer, a cloud server and the like. The terminal device may include, but is not limited to, a processor, a memory.
The processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processor, digital signal processor (DIGITAL SIGNAL processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field-programmable gate array (field-programmable GATE ARRAY, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is a control center of the terminal device, and which connects various parts of the entire terminal device using various interfaces and lines.
The memory may be used to store the computer program and/or the module, and the processor may implement various functions of the terminal device by running or executing the computer program and/or the module stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to the use of the mobile terminal, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart memory card (SMART MEDIA CARD, SMC), secure Digital (SD) card, flash memory card (FLASH CARD), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
Wherein the terminal device integrated modules/units may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as stand alone products. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention, and are not to be construed as limiting the scope of the invention. It should be noted that any modifications, equivalent substitutions, improvements, etc. made by those skilled in the art without departing from the spirit and principles of the present invention are intended to be included in the scope of the present invention.
Claims (10)
1. A health analysis method of a broadcasting system, which is characterized by being applied to a diagnosis server, wherein the broadcasting system comprises the diagnosis server, a broadcasting server, a front-end device and a network node device; the diagnosis server is respectively in communication connection with the broadcasting server, the front-end equipment and the network node equipment;
The health analysis method comprises the following steps:
Responding to a request for health diagnosis of a broadcasting system, respectively acquiring server logs of a broadcasting server, front-end equipment and network node equipment, and performing error analysis on each server log to generate white box diagnosis parameters;
Initiating a black box diagnosis request to the broadcasting server, and indicating the broadcasting server to send a black box diagnosis instruction to the front-end equipment so that the front-end equipment returns black box diagnosis result parameters to a diagnosis server after executing the black box diagnosis instruction;
Taking the diagnosis result parameter returned by the front-end equipment as a black box diagnosis parameter;
trend analysis is carried out on the white box diagnostic parameters and the black box diagnostic parameters, and trend diagnostic parameters are generated;
initiating a risk diagnosis request to the broadcast server so that the broadcast server returns a risk diagnosis result parameter to a diagnosis server after executing a risk diagnosis instruction;
Taking the risk diagnosis result parameter returned by the broadcast server as a risk diagnosis parameter;
and calculating the health value of the broadcasting system according to the white box diagnosis parameter, the black box diagnosis parameter, the trend diagnosis parameter and the risk diagnosis parameter to generate a health diagnosis result.
2. The method for health analysis of a broadcasting system according to claim 1, wherein said performing error analysis on each of said server logs generates white-box diagnostic parameters, specifically:
Counting the number of warning logs and the number of error logs in each server log; and carrying out weighted summation operation after configuring corresponding weights for the number of the warning logs and the number of the error logs, and generating white box diagnosis parameters.
3. The method for analyzing health of a broadcasting system according to claim 1, wherein said sending a black box diagnosis request to said broadcasting server instructs said broadcasting server to send a black box diagnosis instruction to said front-end device, so that said front-end device returns black box diagnosis result parameters to said diagnosis server after executing said black box diagnosis instruction, specifically:
Initiating a black box diagnosis request to the broadcasting server, and indicating the broadcasting server to send a black box diagnosis instruction to the front-end equipment so that the broadcasting function is detected after the front-end equipment executes the black box diagnosis instruction; the broadcasting function includes: task execution function, sound playing function and volume feedback function; each of the broadcast functions is configured with a corresponding standard;
and calculating the score of the broadcasting function of the front-end equipment according to the standard of each broadcasting function, and returning the score as a black box diagnosis result parameter to a diagnosis server.
4. The method for health analysis of a broadcasting system according to claim 1, wherein said trend analysis is performed on said white box diagnostic parameter and said black box diagnostic parameter to generate trend diagnostic parameters, specifically:
Counting fault data in the white box diagnosis parameters and the black box diagnosis parameters within a preset time period; generating a corresponding growth model according to the growth trend of each fault data; and taking the product of each fault data and the corresponding growth model as a trend value of each fault data, and combining the trend values of all the fault data to generate a trend diagnosis parameter.
5. The method for analyzing health of a broadcasting system according to claim 4, wherein said issuing a risk diagnosis request to said broadcasting server causes said broadcasting server to execute a risk diagnosis instruction, and then returns a risk diagnosis result parameter to a diagnosis server, specifically:
Initiating a risk diagnosis request to the broadcast server so that the broadcast server calculates the fault times of a fault source according to the fault data; and generating a risk diagnosis result parameter according to the fault frequency of each fault source, and returning the risk diagnosis result parameter to the diagnosis server.
6. The method for analyzing the health of a broadcasting system according to claim 1, wherein the calculating the health value of the broadcasting system according to the white box diagnostic parameter, the black box diagnostic parameter, the trend diagnostic parameter and the risk diagnostic parameter generates a health diagnostic result, specifically:
the white box diagnosis parameters, the black box diagnosis parameters, the trend diagnosis parameters and the risk diagnosis parameters are configured with corresponding weights and then subjected to weighted summation operation to generate health parameters;
generating a health degree value as a health diagnosis result according to the health parameters;
the health value is expressed as follows: h=100- { i=1 } { n } f_i } { w_i;
Wherein H is a health value, f_i is a value of an i-th diagnostic parameter, and the diagnostic parameter is a white-box diagnostic parameter, a black-box diagnostic parameter, a trend diagnostic parameter or a risk diagnostic parameter; w_i is the weight of the ith diagnostic parameter; Σ_ { i=1 } { n } is a weighted sum of the 1 st to nth diagnostic parameters; n is the total number of diagnostic parameters.
7. A health analysis device of a broadcasting system, which is applied to a diagnosis server, wherein the broadcasting system comprises the diagnosis server, a broadcasting server, a front-end device and a network node device; the diagnosis server is respectively in communication connection with the broadcasting server, the front-end equipment and the network node equipment;
The health analysis device includes: the system comprises a white box diagnosis module, a black box diagnosis module, a trend diagnosis module, a risk diagnosis module and a health analysis module;
the white box diagnosis module is used for respectively acquiring server logs of the broadcasting server, the front-end equipment and the network node equipment, carrying out error analysis on each server log and generating white box diagnosis parameters;
The black box diagnosis module is used for initiating a black box diagnosis request to the broadcast server, instructing the broadcast server to send a black box diagnosis instruction to the front-end equipment, so that the front-end equipment returns black box diagnosis result parameters to the diagnosis server after executing the black box diagnosis instruction;
Taking the diagnosis result parameter returned by the front-end equipment as a black box diagnosis parameter;
The trend diagnosis module is used for carrying out trend analysis on the white box diagnosis parameters and the black box diagnosis parameters to generate trend diagnosis parameters;
The risk diagnosis module is used for initiating a risk diagnosis request to the broadcast server so that the broadcast server returns risk diagnosis result parameters to the diagnosis server after executing a risk diagnosis instruction;
Taking the risk diagnosis result parameter returned by the broadcast server as a risk diagnosis parameter;
The health analysis module is used for calculating the health value of the broadcasting system according to the white box diagnosis parameter, the black box diagnosis parameter, the trend diagnosis parameter and the risk diagnosis parameter, and generating a health diagnosis result.
8. The health analysis apparatus of a broadcasting system as set forth in claim 7, wherein said health analysis module comprises an analysis unit;
The analysis unit is used for carrying out weighted summation operation on the white box diagnosis parameters, the black box diagnosis parameters, the trend diagnosis parameters and the risk diagnosis parameters after corresponding weights are configured, so as to generate health parameters;
generating a health degree value as a health diagnosis result according to the health parameters;
the health value is expressed as follows: h=100- { i=1 } { n } f_i } { w_i;
Wherein H is a health value, f_i is a value of an i-th diagnostic parameter, and the diagnostic parameter is a white-box diagnostic parameter, a black-box diagnostic parameter, a trend diagnostic parameter or a risk diagnostic parameter; w_i is the weight of the ith diagnostic parameter; Σ_ { i=1 } { n } is a weighted sum of the 1 st to nth diagnostic parameters; n is the total number of diagnostic parameters.
9. A broadcast system, comprising: the system comprises a diagnosis server, a broadcasting server, front-end equipment and network node equipment; the diagnosis server is respectively in communication connection with the broadcasting server, the front-end equipment and the network node equipment;
the diagnosis server is used for responding to a request for health diagnosis of the broadcasting system, respectively obtaining server logs of the broadcasting server, the front-end equipment and the network node equipment, carrying out error analysis on each server log and generating white box diagnosis parameters;
Initiating a black box diagnosis request to the broadcasting server, and indicating the broadcasting server to send a black box diagnosis instruction to the front-end equipment so that the front-end equipment returns black box diagnosis result parameters to a diagnosis server after executing the black box diagnosis instruction;
Taking the diagnosis result parameter returned by the front-end equipment as a black box diagnosis parameter;
trend analysis is carried out on the white box diagnostic parameters and the black box diagnostic parameters, and trend diagnostic parameters are generated;
initiating a risk diagnosis request to the broadcast server so that the broadcast server returns a risk diagnosis result parameter to a diagnosis server after executing a risk diagnosis instruction;
Taking the risk diagnosis result parameter returned by the broadcast server as a risk diagnosis parameter;
and calculating the health value of the broadcasting system according to the white box diagnosis parameter, the black box diagnosis parameter, the trend diagnosis parameter and the risk diagnosis parameter to generate a health diagnosis result.
10. A computer readable storage medium, wherein the computer readable storage medium comprises a stored computer program; wherein the computer program, when run, controls a device in which the computer readable storage medium is located to perform a method of health analysis of a broadcast system as claimed in any one of claims 1 to 6.
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