CN109558450B - Automobile remote monitoring method and device based on distributed architecture - Google Patents
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Abstract
Aiming at the defects in the design of the existing automobile remote system architecture, the invention forms a high-concurrency and high-availability automobile remote monitoring system architecture taking Hadoop, hdfs, mongoDB as a storage basis and Netty, rabbitMQ as a message receiving basis by means of a big data technology and through practical platform construction test and test, stores and manages actual measurement big data of an automobile road, and particularly requests for protection of an automobile remote monitoring method and device based on a distributed architecture. Based on the receiving and processing of big data, the method for designing the automobile remote monitoring architecture meeting the requirements of high concurrency, high availability and mass data processing solves the problems of high concurrency data receiving and mass data query analysis existing in the current automobile monitoring system architecture design. And as supportive technology, the research can provide technical support in the aspects of mass data monitoring and intelligent network-connected automobile monitoring.
Description
Technical Field
The invention belongs to the modern computer transportation technology, and particularly relates to an automobile remote monitoring method based on a distributed architecture.
Background
Automobiles become an indispensable part of the daily life of the public families, and the automobile conservation amount rapidly rises in recent years in China, but the problems of frequent traffic accidents, urban road congestion, tail gas pollution, noise pollution and the like are caused to become serious. In this situation, the intelligent traffic system becomes the best solution to alleviate and improve the above road problems. Furthermore, china is used for accelerating construction of manufacturing countries, science and technology countries, network countries and traffic countries, and greatly promoting intelligent and networking technology development and industrial application of automobiles. The state promulgated by the state of the intelligent network-connected automobile road test management standard (trial run) clearly specifies that the test vehicle can return the motion states such as the vehicle control mode, the vehicle position, the vehicle speed, the acceleration and the like to the test management center in real time, and the test management center is required to have a platform meeting the real-time monitoring of the relevant parameters of the test vehicle.
Under the background, the automobile remote monitoring system has important roles in the intelligent transportation field and the intelligent networking field. The automobile remote monitoring system utilizes the technologies of communication technology, sensor technology, automatic control principle and the like to feed back the information of real-time positioning information, historical track, monitoring and the like of road participants to road traffic management personnel in real time through communication means, and the road vehicles are scientifically and accurately scheduled by analyzing and deciding the related information of the vehicles and the roads, so that the traffic management level is improved [3]. With the increasing number of monitored vehicles, automobile remote monitoring systems are facing demands for massive, high concurrency, real-time data processing and intelligent analysis, so that higher technical requirements are provided for operators. The problems that the data structure and the data storage capacity cannot be flexibly expanded, the distributed parallel data mining is difficult, the high fault tolerance recovery capability is poor and the like are continuously appeared in the implementation process of the system. How to upload, collect and store and utilize massive traffic flow data in real time and how to statistically mine the data becomes a great difficulty.
Aiming at the core common problems of mass, high concurrency, real-time processing and the like of an automobile remote monitoring system, a domestic research institution gradually obtains some practical experience and research results by means of big data processing technologies such as Hadoop, spark and the like and distributed data storage technologies such as Hdfs, hbase, mongoDB and the like, and meanwhile, the problems of further improvement are also existed. The intelligent traffic management is realized by combining the big data technology with the vehicle data in the United states of America, and the processing efficiency of traffic departments on accidents is greatly improved. The public transportation data processing system established in Shenzhen city has the functions of collecting data mining, storing mass collecting data, intelligent decision making, sharing multi-platform information and the like, and provides support for intelligent transportation cities. Domestic scholars utilize Hadoop and other big data technologies to realize the monitoring of high concurrent vehicles such as petroleum transportation vehicle monitoring, bus monitoring and logistics vehicle monitoring. However, in the remote monitoring system of the automobile based on big data at home and abroad, the current common internet big data architecture is mostly adopted for architecture design, and a standard mode is not formed aiming at the characteristics of high concurrency, complex data, long-term monitoring and the like of the automobile in the remote monitoring of the automobile, so that the system has the phenomena of message blocking, server resource consumption and the like.
Disclosure of Invention
Aiming at the defects in the design of the existing automobile remote system architecture, by means of big data technology and through practical platform building tests and tests, the invention forms the high-concurrency and high-availability automobile remote monitoring system architecture taking Hadoop, hdfs, mongoDB as a storage basis and Netty, rabbitMQ as a message receiving basis, and stores and manages actual measurement big data of an automobile road.
The invention firstly requests protection of an automobile remote monitoring method based on a distributed architecture, which is characterized in that:
a1, a data acquisition end sends acquired vehicle data to a remote monitoring server;
a2, the data is transmitted to a load balancing server after passing through a firewall;
a3, the data passing through the load balancing server passes through the message middleware, so that terminal data access and data persistence are decoupled fully, message pipelines are realized in the concurrent peak period of mass terminals, and the stability of data transmission and message consistency are ensured;
a4, after the data passes through the message application server, the data is stored into the distributed memory after the analysis is completed;
preferably, the remote monitoring method of the automobile based on the distributed architecture is performed in the steps A1-A4, and the user side also performs corresponding monitoring operation, which is characterized in that:
b1, the user side registers information such as vehicles and drivers through a pc side or a mobile app side by using a service registration server, and the registration information is stored in a Mysql database;
b2, the user sends query and analysis demands to a system service center through a pc end or a mobile app end, and the service center utilizes system services of a service engine according to the demands of the user and queries data from a Redis database through information data matching of Mysql;
b3, if the data cannot be queried in the Redis database, querying the Hbase database for the data;
and B4, after the data is queried, completing the retrieval and analysis of the data through a Spark or Solr platform, and providing different types of data information including vehicle alarm information, track playback information, data retrieval information, vehicle monitoring progress, report statistics information, and the like for the user based on the requirement of the user.
The invention also claims a remote monitoring device of an automobile based on a distributed architecture, which is characterized by comprising:
the Web module is mainly responsible for webUI (user interface) work such as page display, service application submission and the like of the automobile remote monitoring device, and comprises html5, CSS and Jquery components with excellent interaction performance and good display effect, and icon display work of application easeyUI, echart;
the communication module is responsible for receiving the data packet sent by the data acquisition terminal, and the framework adopts netty to receive the high concurrency data packet;
a resource scheduling module that uses zookeeper, flume to be responsible for completing resource scheduling among the various server clusters;
the analysis module is used for providing retrieval and analysis of mass data by utilizing the solr and spark;
and the storage module adopts a form of collocating a relational database and a distributed database, and is responsible for storing system service data and test data by using hbase and redis layers.
The invention designs an automobile remote monitoring architecture method which meets the requirements of high concurrency, high availability and mass data processing based on the receiving and processing of big data, and solves the problems of high concurrency data receiving and mass data query analysis existing in the current automobile monitoring system architecture design. And as supportive technology, the research can provide technical support in the aspects of mass data monitoring and intelligent network-connected automobile monitoring.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a workflow diagram of a distributed architecture-based remote automobile monitoring method according to the present invention;
FIG. 2 is a data flow diagram of a remote monitoring device for an automobile based on a distributed architecture according to the present invention;
fig. 3 is a structural diagram of an automobile remote monitoring device based on a distributed architecture 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.
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.
The invention firstly protects an automobile remote monitoring method based on a distributed architecture, which is characterized in that:
a1, a data acquisition end sends acquired vehicle data to a remote monitoring server;
a2, the data is transmitted to a load balancing server after passing through a firewall;
a3, the data passing through the load balancing server passes through the message middleware, so that terminal data access and data persistence are decoupled fully, message pipelines are realized in the concurrent peak period of mass terminals, and the stability of data transmission and message consistency are ensured;
a4, after the data passes through the message application server, the data is stored into the distributed memory after the analysis is completed;
further preferably, the remote automobile monitoring method based on the distributed architecture is performed in the steps A1-A4, and the user side also performs corresponding monitoring operation, and is characterized in that:
b1, the user side registers information such as vehicles and drivers through a pc side or a mobile app side by using a service registration server, and the registration information is stored in a Mysql database;
b2, the user sends query and analysis demands to a system service center through a pc end or a mobile app end, and the service center utilizes system services of a service engine according to the demands of the user and queries data from a Redis database through information data matching of Mysql;
b3, if the data cannot be queried in the Redis database, querying the Hbase database for the data;
and B4, after the data is queried, completing the retrieval and analysis of the data through a Spark or Solr platform, and providing different types of data information including vehicle alarm information, track playback information, data retrieval information, vehicle monitoring progress, report statistics information, and the like for the user based on the requirement of the user.
Preferably, the data acquisition end sends the acquired vehicle data to a remote monitoring server; the method comprises the following steps:
the data acquisition terminal is a data acquisition terminal installed on the vehicle or provided with the original vehicle, acquires vehicle information, and then composes the vehicle information into a data packet according to a specified protocol, and sends the data packet to the vehicle remote monitoring server through a wireless network. And in the automobile remote monitoring server, the data packet is analyzed, and then the data packet is monitored and displayed on the web page and stored in the storage part.
Preferably, the data passing through the load balancing server passes through the message middleware, fully decouples the terminal data access and data persistence, realizes a message pipeline in a massive terminal concurrency peak period, ensures the stability of data transmission and message consistency, and specifically comprises the following steps:
the data acquisition end sends acquired vehicle data to a remote monitoring server, and the problem of network flash, client reconnection, safety authentication, message encoding and decoding, half-packet processing and the like can be solved by the communication server inherent connection management in the process of receiving by the remote monitoring server. And because monitoring needs to face the high concurrent performance test of mass terminal access, the system needs to design a good memory management mechanism, the connection of the vehicle-mounted terminal is wireless connection based on GPRS, the signal is in an unstable state in the process of moving at a high speed in the wild, the connection is continuously interrupted and accessed although being based on long connection, and the server can reasonably allocate memory, avoid memory leakage and avoid memory accumulation rise in millions of calls when processing terminal access, data analysis, alarm analysis and batch warehousing.
The remote monitoring method for the automobile based on the distributed architecture is used for receiving data through a Netty communication framework, and the module is independent of other applications and is mainly responsible for maintaining the tcp link, the decoding, the encoding, the flow control, the black-white list and other safety control of the access terminal. Netty is a high-performance, asynchronous event-driven NIO framework that provides support for TCP, UDP and file transfer, as an asynchronous NIO framework, all IO operations of Netty are asynchronous and non-blocking, and users can conveniently and actively acquire IO operation results through a Future-Listener mechanism or through a notification mechanism. In data transmission, the robustness, the function, the performance, the customizability and the expandability of Netty are all first-aid in the similar framework, and the performance of the Netty is verified by hundreds of commercial projects, so that the problem of mass terminal access of an automobile remote monitoring system can be perfectly solved.
The automobile remote monitoring access module and the storage module need to interact with each other in a message mode, because massive vehicle terminal data concurrency peaks are not constant, and concurrency of the automobile remote monitoring access module relative to a real platform can be reduced at night. Therefore, after the message is received by the high-performance communication framework, the message middleware is needed to perform decoupling between the components, so that the message middleware is mainly used for decoupling between the components, and a sender of the message does not need to know the existence of a message user, and vice versa. The AMQP is mainly characterized by message-oriented, queue-oriented, routing (including point-to-point and publish/subscribe), reliability, safe concurrency and peak time, and the interaction has higher requirements on message consistency, and asynchronous interaction among individual systems is carried out through an MQ component and a response confirmation mechanism is needed. RabbitMQ is a message middleware for realizing AMQP (advanced message queuing protocol), originally originates from a financial system, is used for storing and forwarding messages in a distributed system, is popular in aspects of usability, expansibility, high availability and the like, and has the functional characteristics of reliability, flexible routing, clustering, transaction, high-availability queues, message ordering, problem tracking, visual management tools, plug-in systems and the like. And the RabbitMQ is used as a message middleware between the system communication module and the database, so that the terminal data access and data persistence are sufficiently decoupled. And a message pipeline is realized in a concurrent peak period of a large number of terminals, so that the stability of data transmission and the consistency of messages are ensured.
Preferably, after the data passes through the message application server, the data is stored in the distributed memory after the analysis is completed, and the user terminal registers the information such as the vehicle and the driver by using the service registration server through the pc terminal or the mobile app terminal, and the registration information is stored in the Mysql database specifically as follows:
in the context of high concurrency data uploading, the data of the monitored vehicle often has larger data read-write concurrency and accumulated data quantity. It is counted that at a vehicle of 3000 private cars, at a scale of 1HZ uploading frequency, the daily uploaded data can reach 3000 tens of thousands. For high concurrency access of data, the traditional relational database provides a read-write separation scheme, but brings about the problem of data consistency. For more and more mass data, the traditional database adopts database and table division, so that the realization is complex, and the migration maintenance is required to be continuously carried out in the later period. For the aspects of high availability and expansion, the traditional data adopts a scheme of main and standby, main and auxiliary and multiple main, but the expansibility is poor, and the data migration is needed by increasing nodes and downtime. Aiming at the problems, the distributed database HBase has a complete solution, and is suitable for the requirement of high concurrency mass data access. Hbase reduces IO based on column-type efficient storage, and general query does not need all fields of one row, and most of Hbase only needs a few fields; for a line-oriented storage system, all data are fetched for each inquiry, and then required fields are selected from the data; the storage system facing the column can independently inquire a certain column, so that IO is greatly reduced, and compression efficiency is improved; the same column data has high similarity, and the compression efficiency is increased.
Redis is a key-value storage system used to provide real-time status queries of vehicles, and is now increasingly used in various systems, in most cases, because of its high-performance characteristics, is used as a cache. Redis has high read-write speed, because the data exists in the memory, the method is similar to HashMap, and has the advantages that the time complexity of searching and operation is O (1); in addition, redis supports rich data types, support
string, list, set, requested set, hash, and support transactions, the operations are atomic, i.e., changes to the data are either all performed or not performed at all. Redis has rich properties: the method can be used for caching, setting the expiration time according to the key, and automatically deleting the message after expiration. Therefore, the redis is used as the query read-write cache of the whole system, so that the difficult problems of real-time data query and quick writing can be solved, and the speed of mass data reading and writing and the query speed are ensured.
Further preferably, the step B4 is that after the data is queried, the search and analysis of the data are completed through a Spark or Solr platform, and data information of different types including vehicle alarm information, track playback information, data search information, vehicle monitoring progress, report statistics information, and the like is provided for the user based on the requirement of the user, and specifically includes:
the data retrieval of the method adopts a Solr retrieval engine. Solr is a high-performance full-text search server based on lucene, provides a richer query language than lucene, provides a SolrCloud mode to support distributed indexes, and automatically carries out the cutting of the shring data; the performance of the search is improved by the master-slave (leader, replica) mode of each stamping. The indexing and storage operation of the data in the system are asynchronous, so that the availability and throughput can be greatly improved; only indexing operation is carried out on certain attribute fields, the identification key of the data is stored, and the size of the index is reduced; the data are stored in the distributed storage HBase, the Solr search function overcomes the defect that the HBase is poor in support of secondary index search, and multi-dimensional search statistics on the HBase can be achieved. By utilizing a confirm mechanism of Solr, the data to be indexed is deleted from the data queue to be indexed after the data is stored and indexed.
In order to meet the calculation requirements of mining analysis and interactive real-time query vehicle data, the method uses a Spark platform to support mining analysis class calculation, interactive real-time query calculation and quick query calculation of an allowable error range. Spark is a big data computing framework which pays more attention to iteration efficiency than MapReduce, is generally higher than MapReduce by more than 2 times in terms of SQL query performance, and is at least more than 10 times in performance by utilizing the characteristics of memory computation and a memory table. In terms of iterative computation and mining analysis, it is precisely recommended to convert the model training at the hour and day level into training at the Spark's minute level, while the compact programming interface makes the algorithm implementation much higher than MR in terms of time cost and code amount.
Spark provides a comprehensive, unified framework for managing the need for large data processing of various datasets with different properties (text data, chart data, etc.) and data sources (batch data or real-time streaming data). Core components such as Spark SQL, spark, streaming, MLlib, graphX, sparkR and the like solve a plurality of big data problems. The Spark read-write process is based on memory, unlike hadoop overflow write-in disk, so that the speed is high. In addition, the bandwidth dependence of the DAG job scheduling system increases Spark speed.
The method focuses on a method for designing a massive, high concurrency and real-time data processing framework, and mainly solves the problems of massive, high concurrency and real-time processing of an automobile remote monitoring system in the field of big data processing and analysis, and realizes a vehicle big data processing framework with excellent unified performance.
Referring to fig. 2, a data flow diagram of a remote monitoring device for an automobile based on a distributed architecture according to the present invention is described in detail with respect to a data flow direction and an object in which data participates of the remote monitoring device for an automobile based on the distributed architecture according to the present invention.
Firstly, a data acquisition end, namely an automobile end, of an automobile remote monitoring device based on a distributed architecture sends data to a system through a terminal box, and then the data flow through a firewall and are further transmitted to a load balancing server. The system utilizes the Netty module to create communication connection, and completes data access to allow data to flow into the system. And as the concurrency of the monitoring terminal is larger, the data flows into the Rabbit message queue to wait for data processing. After the data passes through the message application server, the data is stored to a Redis which is a memory server for quick retrieval and use of the data after the analysis is completed. For data with little need for no inquiry, the Hbase is written into a distributed database, and the Hbase is stored on Hdfs of Hadoop by using a distributed file.
On the other hand, the lower part of fig. 2 shows the data flow of the user side, the user side registers the information of the vehicle, the driver and the like through the pc side or the mobile app side by using the service registration server, and the registration information is stored in the Mysql database. The user sends query and analysis demands to a system service center through a pc end or a mobile app end, the service center utilizes system service of a service engine according to the demands of the user, queries data from a Redis database through information data matching of Mysql, queries data from an Hbase database if the data cannot be queried from the Redis database, and provides different types of data information including vehicle alarm information, track playback information, data retrieval information, vehicle monitoring, report statistics information and the like for the user through Spark or Solr platform after the data is queried.
Referring to fig. 3, an organization structure diagram of an automobile remote monitoring device based on a distributed architecture according to the present invention is shown.
The automobile remote monitoring device based on the distributed architecture is characterized by comprising:
the Web module is mainly responsible for webUI (user interface) work such as page display, service application submission and the like of the automobile remote monitoring device, and comprises html5, CSS and Jquery components with excellent interaction performance and good display effect, and icon display work of application easeyUI, echart;
the communication module is responsible for receiving the data packet sent by the data acquisition terminal, and the framework adopts netty to receive the high concurrency data packet;
a resource scheduling module that uses zookeeper, flume to be responsible for completing resource scheduling among the various server clusters;
the analysis module is used for providing retrieval and analysis of mass data by utilizing the solr and spark;
and the storage module adopts a form of collocating a relational database and a distributed database, and is responsible for storing system service data and test data by using hbase and redis layers.
Aiming at the method and the device, in order to analyze the effectiveness, an automobile remote monitoring system with data acquisition, storage, calculation and scheduling is built by using 20 servers, and performance verification of data receiving processing, data calculation and data storage reading and writing is performed, and the comparison is performed by using 20 servers with the same performance based on a common acquisition and storage mode.
1) Data reception processing test
And transmitting vehicle simulation data packet data by using a terminal simulation tool, observing whether the load of the server is supported to simulate a large amount of data or not, and judging whether the related data are normally transmitted or not. Writing a corresponding communication service connection address at the connection position of the server, starting to send a packet after confirming that the communication service connection address is correct, and starting to send a data packet to a permission system by the simulation terminal. If the communication is normal at this time, it can be seen that the transmission packets 41998.48/s are 4 ten thousand packets per second on average.
The local station server is utilized to generate the data 1365.6M which is simulated and uploaded, the data is communicated with a remote monitoring system and a comparison system of the automobile, data transmission is carried out, the data acquisition rate is observed, and the four-time processing result of the system is displayed.
TABLE 1 receiving the test results of the treatment
According to the test, the system can meet the requirement of 4 ten thousand trolleys to upload data simultaneously under the current architecture, and the analysis receiving rate of the data is obviously improved.
2) Storage test
In the experiment, a data simulation terminal is used for generating data to be written in, the data is sent to a data storage server, the data writing quantity in a certain time (60 seconds) is observed, and the data writing rate is calculated.
Table 2 storage performance test
Through verification, the automobile remote monitoring system architecture designed in the method is remarkably improved in terms of data reading and writing rate compared with a conventional storage system, and meets design requirements.
The present invention is not limited to the preferred embodiments, but is intended to cover modifications, equivalents, alternatives, and improvements within the spirit and principles of the invention.
Claims (1)
1. A remote automobile monitoring method based on a distributed architecture is characterized in that:
a1, a data acquisition end sends acquired vehicle data to a remote monitoring server;
a2, the data is transmitted to a load balancing server after passing through a firewall;
a3, the data passing through the load balancing server passes through the message middleware, so that terminal data access and data persistence are decoupled fully, message pipelines are realized in the concurrent peak period of mass terminals, and the stability of data transmission and message consistency are ensured;
a4, after the data passes through the message application server, the data is stored into the distributed memory after the analysis is completed; the steps A1-A4 are carried out, and simultaneously, the user side also carries out corresponding monitoring operation, specifically:
b1, the user side registers the information of the vehicle and the driver through a pc side or a mobile app side by using a service registration server, and the registration information is stored in a Mysql database;
b2, the user sends query and analysis requirements to a system service center through a pc end or a mobile app end, and the service center uses system services of a service engine to query data from a Redis database through Mysql information data matching according to the requirements of the user;
b3, if the data cannot be queried in the Redis database, querying the Hbase database for the data;
after inquiring the data, completing the retrieval and analysis of the data through a Spark or Solr platform, and providing data information comprising vehicle alarm information, track playback information, data retrieval information, vehicle monitoring information and report statistics information for the user based on the requirements of the user;
the A1, the data acquisition end sends the acquired vehicle data to a remote monitoring server, and specifically comprises the following steps:
the data acquisition terminal is a data acquisition terminal installed on the vehicle or provided with the original vehicle, acquires vehicle information, and then composes the vehicle information into a data packet according to a specified protocol, and sends the data packet to the vehicle remote monitoring server through a wireless network;
in the automobile remote monitoring server, the data packet is analyzed, and then is monitored and displayed on a web page and stored in a storage part;
the web page is responsible for page display and service application submitting work of the automobile remote monitoring and comprises html5, CSS and Jquery components, and icon display work of application easyUI, echart;
when receiving the data packet sent by the data acquisition end, receiving a high concurrency data packet by adopting netty;
using zookeeper, flume to be responsible for completing resource scheduling among the various server clusters;
searching and analyzing mass data by utilizing a solr and a spark;
the method adopts a form that a relational database is matched with a distributed database, and uses hbase and redis layers to take charge of storing system service data and test data.
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