CN109993506A - Intelligent mine industry Internet of Things operating system platform performance test methods - Google Patents
Intelligent mine industry Internet of Things operating system platform performance test methods Download PDFInfo
- Publication number
- CN109993506A CN109993506A CN201910285370.7A CN201910285370A CN109993506A CN 109993506 A CN109993506 A CN 109993506A CN 201910285370 A CN201910285370 A CN 201910285370A CN 109993506 A CN109993506 A CN 109993506A
- Authority
- CN
- China
- Prior art keywords
- data
- time
- operating system
- real
- system platform
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000011056 performance test Methods 0.000 title claims abstract description 21
- 230000004044 response Effects 0.000 claims abstract description 21
- 238000011156 evaluation Methods 0.000 claims abstract description 16
- 238000012360 testing method Methods 0.000 claims description 37
- 238000005259 measurement Methods 0.000 claims description 8
- VYZAMTAEIAYCRO-UHFFFAOYSA-N Chromium Chemical compound [Cr] VYZAMTAEIAYCRO-UHFFFAOYSA-N 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 7
- 230000005540 biological transmission Effects 0.000 claims description 6
- 238000004088 simulation Methods 0.000 claims description 4
- 241001269238 Data Species 0.000 claims description 3
- 230000002776 aggregation Effects 0.000 claims description 3
- 238000004220 aggregation Methods 0.000 claims description 3
- 230000007423 decrease Effects 0.000 claims description 3
- 230000009897 systematic effect Effects 0.000 claims 1
- 238000003860 storage Methods 0.000 abstract description 7
- 238000002474 experimental method Methods 0.000 description 20
- 230000006870 function Effects 0.000 description 5
- 238000005065 mining Methods 0.000 description 5
- 238000006243 chemical reaction Methods 0.000 description 4
- 230000003111 delayed effect Effects 0.000 description 4
- 238000009877 rendering Methods 0.000 description 3
- 238000011161 development Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 238000013401 experimental design Methods 0.000 description 1
- 238000010422 painting Methods 0.000 description 1
- 238000013102 re-test Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Theoretical Computer Science (AREA)
- Tourism & Hospitality (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Marketing (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Data Mining & Analysis (AREA)
- Mining & Mineral Resources (AREA)
- Life Sciences & Earth Sciences (AREA)
- Animal Husbandry (AREA)
- Agronomy & Crop Science (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Marine Sciences & Fisheries (AREA)
- Primary Health Care (AREA)
- Game Theory and Decision Science (AREA)
- Debugging And Monitoring (AREA)
Abstract
The present invention provides a kind of intelligent mine industry Internet of Things operating system platform performance test methods, by building hardware foundation environment, software service environment, data environment, the comprehensive performance of evaluation system platform, comprehensive performance includes the loading velocity of system main page, response speed, the real-time of data access, the readwrite performance of time series database, the data of key operation are uniformly accessed into ability in user interface.By evaluation, determines that micro services frame entirety can satisfy the use needs under real scene, real time data timely can be acquired as expected, be put in storage, inquire, and quick response user's operation.
Description
Technical field
The present invention relates to a kind of performance test methods, flat more particularly, to a kind of intelligent mine industry Internet of Things operating system
Platform performance test methods.
Background technique
Current mining authority system platform before actual use, can only determine whether operate in by relevant parameter
In mining industry, after coming into operation, data processing and related display cannot be fed back in time, need to detect system with
And search problem, it is time-consuming and laborious, cause production to be delayed, dally over one's work process.
Summary of the invention
The present invention provides a kind of intelligent mine industry Internet of Things operating system platform performance test methods, for studying and
Examine whether the overall performance of intelligent mine operating system micro services frame can satisfy the use needs under real scene.True
Under the working environment in real mine, whether system as expected can timely acquire real time data, be put in storage, inquire, and fast
Speed response user's operation, is one of the key point concerning mining production safety.The present invention is established by simulation of real scenes and is invented,
And the overall performance of micro services frame is evaluated by Key Performance Indicator.
It is described that its technical solution is as follows:
A kind of intelligent mine industry Internet of Things operating system platform performance test methods, by build hardware foundation environment,
Software service environment, data environment, the comprehensive performance of evaluation system platform, comprehensive performance include:
(1) loading velocity of system main page, by the loading velocity of measuring system main page, to assess whole system
System provides the ability of service；
(2) in user interface key operation response speed, by measurement user interface on key operation response speed,
Carry out assessment system to complete typical services logic and respond user's the time it takes, that is, the real-time operated；
(3) real-time of data access is generated into caused by MOS system from equipment by measurement data and is delayed,
To assess the real time data acquisition of data access correlation micro services；
(4) readwrite performance of time series database by inquiry of the measurement time series database under different magnitude data and is write
The time-consuming for entering operation carrys out the problem of whether assessment system system can encounter performance decline when data volume increases, and when assessment
Whether the readwrite performance of sequence database can satisfy the application needs in mine；
(5) data are uniformly accessed into ability, and according to mainstream industry equipment commonly based on the agreement of network transmission, evaluation is corresponded to
The access performance of data.
Hardware foundation environment includes server cluster, interchanger, test terminating machine, data acquisition intelligent gateway, server
Cluster, test terminating machine, data acquisition intelligent gateway are all connected by interchanger；Server cluster includes at least three physics
Machine, wherein a physical machine is management node, other physical machines are working node；Data acquire intelligent gateway and are used for data access
With Test data generation function.
The operating system of the software service environment built on the basis of hardware foundation environment, server cluster uses CentOS
7, containerization engine uses Docker 18.0CE version, uses the service discovery and load balancing of the primary offer of Docker engine
Function supports micro services operation；The operating system macOS 10.13 of terminating machine is tested, the browser used is Google
Chrome 69.0。
Data environment refer to data processing simulation of real scenes under workload, including normal data access amount with
The each task of inquiry request number, comprehensive performance is surveyed in the case where 2000 data points, average every five seconds acquire primary frequency
Examination, and at least there is 90 days historical data amounts in experimental situation.
The loading velocity of system main page is in evaluation, by four systems interface as test object, comprising:
1) System Overview page: complication system synoptic chart, multisystem aggregation of data are presented；
2) integrated alarm page: real-time system alarm list is shown；
3) real time data of a certain subsystem the real time data page: is shown with diversified forms such as text, table, charts；
4) historical data of user query the historical data page: is shown with curve, table.
The evaluation of the response speed of key operation in user interface is chosen following wherein four contents and is operated, is related to
Call back end interface, real time data inquiry, the inquiry of historical data, front end script execution, data parsing, graph making, report in front end
Table generation, file download.
After choosing four contents, speed statistics is carried out by two ways:
1) in the front-end interface code of aforesaid operations, it is manually inserted timing code, and in the beginning of execution movement, end
Position carries out time-consuming statistics, is accurate to millisecond, and result is output to browser console；
2) consumption of the corresponding network request of each movement is recorded using the network request analysis tool of Chrome DevTools
When situation, including request transmission time, rear end execute time, result time of return.
The evaluation of the real-time of data access, from specific Modbus data source, plc data source and text file number
Initial data is read according to source, the final data format of all measuring points is IEEE-754 floating number, and data measuring point number is set as
1000,2000,3000 groupings tested, the above direct ratio of different data sources remains unchanged.
The evaluation of the readwrite performance of time series database needs to select one group of true time series data, including at 25,000,000
Ordinal number according to be continuously written into continuous read operation, test carry out in three times, data volume be followed successively by 5,000,000,10,000,000,
25000000, database of record it is complete reading and the write time.
Data are uniformly accessed into the evaluation of ability, be respectively collection period be 10s, 5s, 1s, the condition of 500ms, 100ms
Lower progress data points are 1K, 2K, 5K, 10K, 50K, 100K, 150K, the access test of 200K.
Intelligent mine industry Internet of Things operating system platform performance test methods are by building associated analog environment, using adopting
The initial data collected is tested, and can be commented the comprehensive performance of intelligent mine industry Internet of Things operating system platform
It surveys, micro services frame entirety can satisfy the use needs under real scene, can carry out timely to real time data as expected
Acquisition, storage, inquiry, and quick response user's operation, The present invention reduces security risks, runnability are improved, to be
Platform unite after actual use, the processing of mining industry related data can be competent at.
Detailed description of the invention
Fig. 1 is the overall performance experimental test hardware invention schematic diagram of micro services frame；
Fig. 2 is the software environment schematic diagram of service terminal software experiment.
Specific embodiment
Of the invention building is divided into hardware foundation environment, software service environment, data environment.In order to enable experimental result
Show the system performance under actual scene, the software and hardware structure of invention must standardize, and identical as true usage scenario；Together
When, since the performance of this experiment concern micro services frame guarantees the tight of test run environment in hardware environment configuration
Causticity could embody the validity of experimental data.The hardware environment structure of this experiment is as shown in Figure 1.
Micro services frame needs to run on a server cluster, this experiment using one by three physics units at
Server cluster, including a management node and two working nodes.Data access uses the intelligent gateway of MOS standard, subsidiary
Test data generation function.Browser end uses the personal computer of a mainstream as test terminating machine.Between server, intelligence
Energy gateway, test terminating machine all pass through a 100 m switch connection, and all links are not related to switch-link in this experiment
The limitation of bandwidth.Server, intelligent gateway, the particular hardware configuration of test terminating machine are as shown in Table 5-1.
Table 5-1 Experimental Hardware allocation list
The service terminal software running environment of experiment is as shown in Figure 2.Operating system uses CentOS 7, and containerization engine uses
Docker 18.0CE version supports micro services to transport using the service discovery and load-balancing function of the primary offer of Docker engine
Row.The operating system macOS 10.13 of terminating machine is tested, the browser used is Google Chrome 69.0.
In order to enable experimental result preferably to embody the system performance under actual environment, when executing experimental duties, system
Need the workload under simulation of real scenes, including normal data access amount and inquiry request number.It is not specified again
In the case of, following experimental duties carry out under the primary frequency of 2000 data points, acquisition in average every 5 seconds, and guarantee invention extremely
There is 90 days historical data amounts less.
5.1.3 experimental duties and method
In order to measure the comprehensive performance of frame comprehensively, this experimental design carries out following five experimental duties:
Task 1: the loading velocity of assessment system main page.
By the loading velocity of measuring system main page, the ability of service is provided to assess total system.It needs to test
Loading velocity of the representative page under different concurrent request numbers.
Task 2: the response speed of key operation in assessment user interface.
By the response speed of key operation in measurement user interface, carrys out assessment system and complete typical services logic and respond
User's the time it takes, that is, the real-time operated.The operation for needing to choose a variety of different service types is tested.
Task 3: the real-time of data access is assessed.
It is generated from equipment into caused by MOS system and is delayed by measurement data, it is micro- to assess data access correlation
The real time data acquisition of service.This process include intelligent gateway from terminal hardware acquisition data, protocol analysis, format conversion,
It is sent to data loading service.Need to assess the data delay of different data measuring point number respectively.
Task 4: the readwrite performance of time series database is assessed.
By the time-consuming of inquiry and write operation of the measurement time series database under different magnitude data, come assessment system system
Whether the problem of whether system can encounter performance decline when data volume increases, and the readwrite performance of assessment time series database can
Meet mine applies needs.
Task 5: data are uniformly accessed into ability.
Scheme supports most of mainstream industry equipment commonly based on the agreement of network transmission.Agreement that is current and incorporating
Have: ModbusTCP, RS485, ProfiNet, WebSocket, TCP&UDP, Siemens S7Ethernet etc..
Scheme supports certain non-standard data source access ways:
Device drives plug-in unit customized development
It provides HTTP Server POST mode to access, can support any language
It provides rpc mode to access, can support mainstream speech, such as C, C++, Python, JAVA etc..
5.1.4 experiment content
5.1.4.1 the loading velocity of assessment system main page.
The typical system interface of following four is chosen as test object, uses Chrome DevTools performance evaluation work
Have to record the load time of each page and situation time-consuming in detail.
Table 5-2 page loading velocity tests page listings
| Number | Page Name | Major function point |
| P1 | System Overview page | Complication system synoptic chart, multisystem aggregation of data are presented |
| P2 | Integrated alarm page | Show real-time system alarm list |
| P3 | The real time data page | The real time data of a certain subsystem is shown with diversified forms such as text, table, charts |
| P4 | The historical data page | The historical data of user query is shown with curve, table |
Experiment need to record using Chrome DevTools performance analysis tool each page actual loaded it is total when
Between, it additionally needs record data load (Loading), script execution (Scripting), rendering (Rendering), draw
(Painting), other (Other) several detailed time-consumings, are accurate to millisecond (ms).Browser is used at least before executing test
Target pages of access in advance have ensured that browser has possessed caching when executing test for the first time.Each page is also invented
Lower test 10 times, is averaged as final page loading velocity index.
5.1.4.2 the response speed of key operation in user interface is assessed.
This experiment link chooses following four key operations, is related to front end and calls back end interface, real time data inquiry, history
The key links such as data query, front end script execution, data parsing, graph making, report generation, file download.
Speed statistics is carried out by two ways.First, in the front-end interface code of aforesaid operations, it is manually inserted timing
Code, and carry out time-consuming statistics in the beginning of execution movement, end position, is accurate to millisecond (ms), and result is output to clear
Look at device console；Second, the corresponding network of each movement is recorded using the network request analysis tool of Chrome DevTools
The time-consuming situation of request, including request transmission time, rear end execute time, result time of return.The above operation is in same case
Lower carry out retest, each operation are executed 10 times, are averaged as final operation response speed index.
Table 5-3 key operation response speed list of experiments
5.1.4.3 the real-time of data access is assessed.
This experiment reads initial data from specific Modbus data source, plc data source and text file data source,
The final data format of all measuring points is IEEE-754 floating number, and data measuring point number is set as 1000,2000,3000
Grouping is tested.The above direct ratio of different data sources remains unchanged.
Before experiment, unified clock synchronization carried out to intelligent gateway and system server, system time control errors 1 millisecond with
It is interior.When experiment, timing code is inserted into intelligent gateway and the code of System Back-end service, data are generated from source record data
Timestamp, the record storage timestamp in data ready, the difference between the two is the delay of data access.
During this, the protocol analysis of program meeting statistical data, format conversion, data loading three parts are time-consuming.Every group real
Test the real-time index for being repeated 10 times and being averaged as final data access.
5.1.4.4 the readwrite performance of time series database is assessed.
Experiment is written and read aptitude tests for the InfluxDB database of storage time series data.Selected one group of test true
Time series data connected including 25,000,000 time series datas (be equivalent to above-mentioned experimental system one day generate total amount of data)
Continue into continuous read operation.Test executes data read-write operation using the script voluntarily write, and records operation and execute
Time.Test carries out in three times, and data volume is followed successively by 5,000,000,10,000,000,25,000,000, the complete reading of database of record
Out and the write time.
5.1.5 mine Internet of Things operating system data are uniformly accessed into experimental result and analysis
The purpose of this experiment is whether the performance for testing intelligent data acquisition gateway meets the needs of site environment, and attempts
The limiting performance performance for testing gateway, does data supporting for Optimal Development.This experiment respectively collection period be 10s, 5s, 1s,
It is 1K, 2K, 5K that data points are carried out under conditions of 500ms, 100ms, and the access of 10K, 50K, 100K, 150K, 200K are tested,
Test result is as shown in table 5-4.
Table 5-4 data are uniformly accessed into experimental result (10s collection period)
| Project (weight) | 1K | 2K | 5K | 10K | 50K | 100K | 150K | 200K |
| CPU (10%) | 0.1% | 0.0% | 0.3% | 0.5% | 1.1% | 3.0% | 5.0% | 10% |
| Mem (10%) | 10M | 10M | 11M | 17M | 20M | 22M | 30M | 35M |
| Delay (30%) | 0.1ms | 0.1ms | 0.1ms | 0.2ms | 0.3ms | 0.3ms | 0.5ms | 0.7ms |
| IO (20%) | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% |
| Accuracy (30%) | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
Table 5-5 data are uniformly accessed into experimental result (5s collection period)
| Project (weight) | 1K | 2K | 5K | 10K | 50K | 100K | 150K | 200K |
| CPU (10%) | 0.1% | 0.2% | 0.3% | 0.5% | 1.1% | 3.0% | 5.0% | 10% |
| Mem (10%) | 10M | 11M | 11M | 12M | 17M | 20M | 26M | 30M |
| Delay (30%) | 0.1ms | 0.1ms | 0.1ms | 0.2ms | 0.3ms | 0.3ms | 0.5ms | 0.7ms |
| IO (20%) | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% |
| Accuracy (30%) | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% |
Table 5-6 data are uniformly accessed into experimental result (1s collection period)
| Project (weight) | 1K | 2K | 5K | 10K | 50K | 100K | 150K | 200K |
| CPU (10%) | 0.1% | 0.2% | 0.3% | 0.5% | 1.1% | 3.0% | 5.0% | 10% |
| Mem (10%) | 10M | 11M | 11M | 12M | 17M | 20M | 26M | 30M |
| Delay (30%) | 0.1ms | 0.1ms | 0.2ms | 0.4ms | 0.5ms | 0.5ms | 0.7ms | 1.1ms |
| IO (20%) | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% |
| Accuracy (30%) | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 99.8% |
Table 5-7 data are uniformly accessed into experimental result (500ms collection period)
| Project (weight) | 1K | 2K | 5K | 10K | 50K | 100K | 150K | 200K |
| CPU (10%) | 0.5% | 0.9% | 1.5% | 2.1% | 5.0% | 7.0% | 10% | 13% |
| Mem (10%) | 15M | 17M | 20M | 22M | 30M | 37M | 50M | 60M |
| Delay (30%) | 0.3ms | 0.2ms | 0.3ms | 0.5ms | 1ms | 1.1ms | 1.1ms | 1.5ms |
| IO (20%) | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% |
| Accuracy (30%) | 100% | 100% | 100% | 100% | 100% | 100% | 99.9% | 99.8% |
Table 5-8 data are uniformly accessed into experimental result (100ms collection period)
| Project (weight) | 1K | 2K | 5K | 10K | 50K | 100K | 150K | 200K |
| CPU (10%) | 0.7% | 1.2% | 2.2% | 4.7% | 7.1% | 11% | 15% | 20% |
| Mem (10%) | 15M | 20M | 25M | 40M | 60M | 70M | 100M | 170M |
| Delay (30%) | 0.3ms | 0.5ms | 0.7ms | 1.1ms | 2ms | 4.9ms | 7ms | 10ms |
| IO (20%) | 0.0% | 0.0% | 0.0% | 0.1% | 0.1% | 0.1% | 0.2% | 0.2% |
| Accuracy (30%) | 100% | 100% | 99.7% | 99.5% | 99.5% | 99.1% | 99.0% | 87% |
Thus experimental data it may be concluded that
1) when data point is less than 10K point, the optimal acquisition period is 1s, and the optimal acquisition period is 5s when being greater than at 2000.This
Scheme supports the acquisition of this scale data amount with this strategy.
2) under the common collection period of 1s, validity limit acquisition points are 150K.
3) under 2000 points of common acquisition points, validity limit collection period is 100ms.
4) data point is when less than 50000, delay in 1ms hereinafter, accuracy rate is 100%, real-time and accuracy
It can effectively ensure that.
5.1.6 mine Internet of Things operating system experiment result and analysis
The assessment experimental result of page loading velocity is as shown in table 5-9.Experiment measures the detailed of four representative pages of system
Thin load time situation.It can be seen that the average load time of the page is 834.2 milliseconds, the most slow System Overview page load time
It is 1036.4 milliseconds, system can accomplish that the second grade of the page is opened substantially.In addition, experiment also had recorded using testing tool it is each
The detailed time-consuming situation of different task when the page loads, it can be seen that the time-consuming most task of four pages is script execution
(Scripting), average 695.5 milliseconds of time-consuming, significantly more than other several generic tasks.Script execution time-consuming is that browser dynamic is held
Row page JavaScript the time it takes, therefore the browser performance that this time-consuming and the performance of terminating machine, user use
There is substantial connection.
Similar, the response speed test result of key operation is as shown in table 5-10.Realization has selected four typically to answer
Miscellaneous operation (being related to network request, back-end processing, data access) is used as experimental subjects.User issues operational order from browser
Afterwards, time-consuming occurs mainly in rear end execution network request and front-end processing returns the result two parts.From the experimental results, four
The total time-consuming of item operation is respectively less than 300 milliseconds, and it is 153.6 milliseconds time-consuming averagely to complete an operation.According to the difference of action type,
The position that delay generates is likely located at front end or rear end.
Data access real-time experimental result is as shown in table 5-11.1000,2000,3000 data are chosen in experiment respectively
Point is used as test benchmark, has counted protocol analysis, format conversion, data loading three parts time-consuming situation.The experimental results showed that being
Every thousand data of system data access is delayed at 25 milliseconds or so, and obviously increases as data volume increases nothing.This illustrates to invent
Data access pressure do not reach the bearing capacity of single intelligent gateway and two working nodes, the case where 3000 data points
It can accomplish that 25 milliseconds of data loading is ready down.
The readwrite performance test result of time series database is as shown in table 5-12.Experiment has chosen 5,000,000 respectively, 10,000,000,
25000000 data amounts are as test benchmark.The experimental results showed that the readwrite performance of InfluxDB time series database is more stable,
When data volume increases, there is no significant declines for performance.Writing speed is at 60,000 per second or more, and reading speed is per second 4
Ten thousand or more.
In summary experimental result, we are available such as to draw a conclusion.System page loading velocity is second grade, main page
It can accomplish to complete loaded and displayed in 1 second；System core operates the response time within 200 milliseconds, supports quick response.Data
Access has compared with high real-time, and under single intelligent gateway access conditions, every 1000 data completes 25 milliseconds of access delay, when ordinal number
It is greater than 60,000 data per second according to warehouse-in efficiency, search efficiency is greater than 40,000 data per second.Micro services frame entirety can satisfy
Use under real scene needs, and can timely be acquired to real time data as expected, be put in storage, inquires, and quick response
User's operation.
Table 5-9 page loading velocity test result (ms)
| Content | P1 | P2 | P3 | P4 | It is average |
| Data load | 29.2 | 18.4 | 35.4 | 41.9 | 31.2 |
| Script execution | 903.4 | 328.1 | 810.3 | 740.2 | 695.5 |
| Rendering | 27.1 | 10.6 | 29.8 | 50.2 | 29.4 |
| It draws | 2.5 | 1.8 | 3.4 | 7.9 | 3.9 |
| Other | 74.2 | 82.4 | 60.4 | 79.4 | 74.1 |
| It amounts to | 1036.4 | 441.3 | 939.3 | 919.6 | 834.2 |
Table 5-10 key operation response speed test result (ms)
| Content | A1 | A2 | A3 | A4 | It is average |
| The network request time | 76.5 | 9.8 | 41.4 | 159.1 | 71.7 |
| Total time | 125.1 | 18.1 | 292.3 | 178.8 | 153.6 |
Table 5-11 data access browsing real-time data result (ms)
| Content | 1000 data points | 2000 data points | 3000 data points |
| Protocol analysis | 7.3 | 13.9 | 28.1 |
| Format conversion | 1.2 | 2.7 | 3.8 |
| Data loading | 14.9 | 28.9 | 44.1 |
| It amounts to | 23.4 | 45.5 | 76.0 |
| Every thousand datas delay | 23.4 | 22.7 | 25.3 |
Table 5-12 time series database readwrite performance test result (ms)
| Content | It is written total time (s) | It reads total time (s) | Write-in (ten thousand) per second | Reading (ten thousand) per second |
| 5000000 | 393.7 | 556.9 | 6.3498 | 4.4892 |
| 10000000 | 366.4 | 560.3 | 6.8239 | 4.4620 |
| 25000000 | 376.0 | 581.6 | 6.6491 | 4.2983 |
Intelligent mine industry Internet of Things operating system platform performance test methods are by building associated analog environment, using adopting
The initial data collected is tested, and can be commented the comprehensive performance of intelligent mine industry Internet of Things operating system platform
It surveys, micro services frame entirety can satisfy the use needs under real scene, can carry out timely to real time data as expected
Acquisition, storage, inquiry, and quick response user's operation, The present invention reduces security risks, runnability are improved, to be
Platform unite after actual use, the processing of mining industry related data can be competent at.
Claims (10)
1. a kind of intelligent mine industry Internet of Things operating system platform performance test methods, it is characterised in that: by building hardware
Basic environment, software service environment, data environment, the comprehensive performance of evaluation system platform, comprehensive performance include:
(1) loading velocity of system main page is mentioned by the loading velocity of measuring system main page to assess total system
For the ability of service；
(2) in user interface key operation response speed, by measurement user interface on key operation response speed, to comment
Estimate system to complete typical services logic and respond user's the time it takes, that is, the real-time operated；
(3) real-time of data access is generated from equipment to delay caused by MOS system is entered, to comment by measurement data
Estimate the real time data acquisition of data access correlation micro services；
(4) readwrite performance of time series database is grasped by measuring inquiry and write-in of the time series database under different magnitude data
The time-consuming of work comes the problem of whether assessment system system can encounter performance decline when data volume increases, and ordinal number when assessment
Whether can satisfy the application needs in mine according to the readwrite performance in library；
(5) data are uniformly accessed into ability, according to mainstream industry equipment commonly based on the agreement of network transmission, evaluate corresponding data
Access performance.
2. intelligent mine industry Internet of Things operating system platform performance test methods according to claim 1, feature exist
In: hardware foundation environment include server cluster, interchanger, test terminating machine, data acquisition intelligent gateway, server cluster,
Test terminating machine, data acquisition intelligent gateway are all connected by interchanger；Server cluster includes at least three physical machines,
In physical machine be management node, other physical machines are working node；Data acquire intelligent gateway and are used for data access and survey
Try data systematic function.
3. intelligent mine industry Internet of Things operating system platform performance test methods according to claim 2, feature exist
In: the operating system of the software service environment built on the basis of hardware foundation environment, server cluster uses CentOS7, holds
Device engine uses Docker18.0 CE version, using the service discovery and load-balancing function of the primary offer of Docker engine,
Support micro services operation；The operating system macOS10.13 of terminating machine is tested, the browser used is Google
Chrome69.0。
4. intelligent mine industry Internet of Things operating system platform performance test methods according to claim 1, feature exist
In: data environment refers to the workload under the processing simulation of real scenes of data, including normal data access amount and inquiry
The each task of number of request, comprehensive performance is tested in the case where 2000 data points, average every five seconds acquire primary frequency, and
And at least there is 90 days historical data amounts in experimental situation.
5. intelligent mine industry Internet of Things operating system platform performance test methods according to claim 1, feature exist
In: the loading velocity of system main page is in evaluation, by four systems interface as test object, comprising:
1) System Overview page: complication system synoptic chart, multisystem aggregation of data are presented；
2) integrated alarm page: real-time system alarm list is shown；
3) real time data of a certain subsystem the real time data page: is shown with diversified forms such as text, table, charts；
4) historical data of user query the historical data page: is shown with curve, table.
6. intelligent mine industry Internet of Things operating system platform performance test methods according to claim 1, feature exist
In: the evaluation of the response speed of key operation in user interface is chosen following wherein four contents and is operated, is related to front end tune
With back end interface, real time data inquiry, the inquiry of historical data, front end script execution, data parsing, graph making, report generation,
File download.
7. intelligent mine industry Internet of Things operating system platform performance test methods according to claim 6, feature exist
In: after choosing four contents, speed statistics is carried out by two ways:
1) in the front-end interface code of aforesaid operations, it is manually inserted timing code, and in the beginning of execution movement, end position
Time-consuming statistics is carried out, is accurate to millisecond, and result is output to browser console；
2) the time-consuming feelings of the corresponding network request of each movement are recorded using the network request analysis tool of Chrome DevTools
Condition, including request transmission time, rear end execute time, result time of return.
8. intelligent mine industry Internet of Things operating system platform performance test methods according to claim 1, feature exist
In: the evaluation of the real-time of data access is read from specific Modbus data source, plc data source and text file data source
Take initial data, the final data format of all measuring points is IEEE-754 floating number, data measuring point number be set as 1000,
2000,3000 groupings tested, the above direct ratio of different data sources remains unchanged.
9. intelligent mine industry Internet of Things operating system platform performance test methods according to claim 1, feature exist
In: the evaluation of the readwrite performance of time series database needs to select one group of true time series data, including 25,000,000 time series datas
It is continuously written into and is carried out in three times with continuous read operation, test, data volume is followed successively by 5,000,000,10,000,000,25,000,000
Item, the complete reading of database of record and write time.
10. intelligent mine industry Internet of Things operating system platform performance test methods according to claim 1, feature exist
In: data are uniformly accessed into the evaluation of ability, be respectively in collection period are 10s, 5s, 1s, carry out under conditions of 500ms, 100ms
Data points are 1K, 2K, 5K, 10K, 50K, 100K, 150K, the access test of 200K.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910285370.7A CN109993506A (en) | 2019-04-10 | 2019-04-10 | Intelligent mine industry Internet of Things operating system platform performance test methods |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910285370.7A CN109993506A (en) | 2019-04-10 | 2019-04-10 | Intelligent mine industry Internet of Things operating system platform performance test methods |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109993506A true CN109993506A (en) | 2019-07-09 |
Family
ID=67132762
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910285370.7A Withdrawn CN109993506A (en) | 2019-04-10 | 2019-04-10 | Intelligent mine industry Internet of Things operating system platform performance test methods |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109993506A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110348821A (en) * | 2019-07-19 | 2019-10-18 | 杭州物源科技有限公司 | A kind of the intelligence manufacture management system and method for combination Internet of Things |
| CN111193610A (en) * | 2019-11-30 | 2020-05-22 | 祝珍珍 | Intelligent monitoring data system and method based on Internet of things |
| CN112835334A (en) * | 2020-12-31 | 2021-05-25 | 广州明珞装备股份有限公司 | Industrial data platform testing method and device, computer equipment and storage medium |
| CN113204493A (en) * | 2021-05-28 | 2021-08-03 | 中国工商银行股份有限公司 | Performance evaluation method and device based on pressure test |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101159607A (en) * | 2007-11-22 | 2008-04-09 | Ut斯达康通讯有限公司 | Network management system of implementing remote browse network element MIB node |
| CN103067502A (en) * | 2012-12-31 | 2013-04-24 | 博彦科技（上海）有限公司 | Hardware system for cloud development and testing |
| CN107135091A (en) * | 2016-02-29 | 2017-09-05 | 华为技术有限公司 | A kind of application quality index mapping method, server and client side |
| US20170288986A1 (en) * | 2016-04-01 | 2017-10-05 | Thomson Licensing | METHOD FOR PREDICTING A LEVEL OF QoE OF AN APPLICATION INTENDED TO BE RUN ON A WIRELESS USER EQUIPMENT |
-
2019
- 2019-04-10 CN CN201910285370.7A patent/CN109993506A/en not_active Withdrawn
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101159607A (en) * | 2007-11-22 | 2008-04-09 | Ut斯达康通讯有限公司 | Network management system of implementing remote browse network element MIB node |
| CN103067502A (en) * | 2012-12-31 | 2013-04-24 | 博彦科技（上海）有限公司 | Hardware system for cloud development and testing |
| CN107135091A (en) * | 2016-02-29 | 2017-09-05 | 华为技术有限公司 | A kind of application quality index mapping method, server and client side |
| US20170288986A1 (en) * | 2016-04-01 | 2017-10-05 | Thomson Licensing | METHOD FOR PREDICTING A LEVEL OF QoE OF AN APPLICATION INTENDED TO BE RUN ON A WIRELESS USER EQUIPMENT |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110348821A (en) * | 2019-07-19 | 2019-10-18 | 杭州物源科技有限公司 | A kind of the intelligence manufacture management system and method for combination Internet of Things |
| CN111193610A (en) * | 2019-11-30 | 2020-05-22 | 祝珍珍 | Intelligent monitoring data system and method based on Internet of things |
| CN112835334A (en) * | 2020-12-31 | 2021-05-25 | 广州明珞装备股份有限公司 | Industrial data platform testing method and device, computer equipment and storage medium |
| CN112835334B (en) * | 2020-12-31 | 2022-05-27 | 广州明珞装备股份有限公司 | Industrial data platform testing method and device, computer equipment and storage medium |
| CN113204493A (en) * | 2021-05-28 | 2021-08-03 | 中国工商银行股份有限公司 | Performance evaluation method and device based on pressure test |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109993506A (en) | Intelligent mine industry Internet of Things operating system platform performance test methods | |
| CN108446210A (en) | Measure, storage medium and the server of system performance | |
| CN107391373B (en) | AutoIT-based automatic performance testing method | |
| CN103541948B (en) | Test stand for hydraulic element Distributed Status Monitoring network system | |
| CN106254145A (en) | network request tracking processing method and device | |
| CN113268403B (en) | Time series analysis and prediction method, device, equipment and storage medium | |
| CN107360026A (en) | Distributed message performance of middle piece is predicted and modeling method | |
| CN111753034A (en) | One-stop type geographical big data platform | |
| CN110750414A (en) | Mobile data monitoring and analyzing method and device, computer equipment and storage medium | |
| Li | Research on big data analysis data acquisition and data analysis | |
| CN112463432A (en) | Inspection method, device and system based on index data | |
| CN111767193A (en) | Server data anomaly detection method and device, storage medium and equipment | |
| CN112784435B (en) | GPU real-time power modeling method based on performance event counting and temperature | |
| Ilkhani et al. | Extraction test cases by using data mining; reducing the cost of testing | |
| CN111444635B (en) | System dynamics simulation modeling method and system based on XML language | |
| CN103207804A (en) | MapReduce load simulation method based on cluster job logging | |
| CN117709715A (en) | Tunnel engineering construction risk assessment method, system, terminal and medium | |
| CN115952236A (en) | Power failure data analysis processing method and device based on real-time flow calculation | |
| CN114595473A (en) | Access data processing method and device, electronic equipment and computer readable medium | |
| CN110928705B (en) | Communication characteristic analysis method and system for high-performance computing application | |
| CN113722288A (en) | Modeling method for time-space data statistics | |
| Mohror et al. | Trace profiling: Scalable event tracing on high-end parallel systems | |
| CN115599621A (en) | Micro-service abnormity diagnosis method, device, equipment and storage medium | |
| Zan | Prospects for using Big Data to improve the effectiveness of an education organization | |
| Talaver et al. | Dynamic system analysis using telemetry. |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20190709 |
|
| WW01 | Invention patent application withdrawn after publication |