JEREMY COOK
With the growing number of data generated by the orbital system, developers need to revisit the location and manner of processing information. Traditional systems migrate data to the control center for analysis, but modern systems usually keep this function on the train.
The challenge with this fog calculation method is that it imposes a heavy burden on the onboard computer. In addition to increasing the computational load, the need to retain data locally may cause storage problems.
Smart databases can help solve these two problems. After proper configuration, the database can reduce processing and storage requirements.
Using fog calculation
The fog calculation brings many benefits to the track system. This configuration allows the on-board computer to perform calculations in real time and take immediate action. Data is processed at the train level and migrated to the control center so that the entire system can be trended.
Predictive maintenance is a good example of the many benefits offered by rail systems: Onboard analysis can monitor sound data to find bearing problems, monitor temperature sensors to prevent braking problems, and even track RFID and photo data to map potential problems with Specific trains are linked.
Control and safety subsystems can also participate in the action; examples include fire suppression, digital video surveillance and air conditioning.
Database is crucial to the track system
The database management system (DBMS) is critical to all these functions, and choosing the right DBMS is a key design decision.
The SQL database is an obvious choice, but the highly organized and self-referential structure of SQL occupies a relatively large amount of storage space and processing power.
The most important thing is that SQL is overkill. Steve Graves, co-founder and CEO of McObject, said: "Edge devices often don't require complex SQL databases." End users can't see the database, so many of SQL's features are not relevant at all. Similarly, expansion is usually not a decisive factor. Although trains may adopt new subsystems over time, there is very little change in demand.
Another option is to use a loosely formatted database, such as a NoSQL database. But data validation is not an inherent feature of these databases, so verifying the equipment that needs to collect data is done. If the device is set incorrectly, the data may be entered incorrectly and the presented information is useless.
Graves claims that a better choice is to use a database designed for embedded design. Graves believes that the ideal setting is to "share some of the properties of a suitable NoSQL database," but at the same time "provide native, non-SQL low-level (and type-safe) programming interfaces. These are usually faster, easier to program, and take up more space than SQL. smaller.
Graves uses McObject's eXtremeDB in-memory database system as an example. By using a hybrid architecture from SQL and NoSQL, eXtremeDB provides a lightweight, powerful database.
Graves added that this data structure minimizes deployment costs because it minimizes resource consumption. The lightweight database allows customers to use lower-cost processors and requires less system memory on the edge devices.
Safety is a top priority
Regardless, security needs to permeate every embedded system today. The orbit system is no exception.
Graves pointed out that because eXtremeDB was developed specifically for embedded systems, data integrity has been a primary concern since the beginning. So, don't be surprised that eXtremeDB supports secure communications over SSL, which allows you to fully encrypt database content.
The DBMS also provides a type-safe programming interface. This interface eliminates the most common source database corruption, that is, it uses void pointers to pass data between the database runtime and the application.
Similarly, eXtremeDB is designed for the highest reliability. For example, the database uses a fault-tolerant version called eXtremeDB High Availability. This runtime maintains multiple identical databases that enable thermal failover. Typical configurations include:
â– ? Multiple processes or threads on a single hardware
â– ? Two or more motherboards in the chassis
â– ? Multiple computers on the LAN
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