Details about Distributed Systems

Distributed Software Systems (Distributed Software Systems) is a Software system that supports Distributed processing and executes tasks in a multi-processor architecture interconnected by a communication network. It includes distributed operating systems, distributed programming languages, compilation (Interpretation) systems, distributed file systems, and distributed database systems.

The distributed operating system manages distributed processing system resources and controls distributed programs. It differs from a centralized operating system in terms of resource management, process communication, and system structure.

The distributed programming language is used to compile distributed programs running on Distributed Computer Systems. A Distributed Program is composed of several program modules that can be executed independently. They are executed simultaneously on multiple computers of a distributed processing system. Compared with a centralized programming language, it has three features: distribution, communication, and robustness.

The distributed file system can perform remote file access and manage and access files distributed on the network in a transparent manner.

A distributed database system is composed of several database systems distributed on multiple computer nodes. It provides effective access methods to manipulate sub-databases on these nodes. Distributed databases can be regarded as a complete database, but they are actually distributed across geographically dispersed nodes. Of course, the sub-databases distributed on each node are logically related.

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A distributed database system is composed of several sites. These sites are also called nodes. They are connected together in the communication network. Each node is an independent database system. They all have their own databases, central processors, and terminals, and their local database management systems. Therefore, the distributed database system can be seen as a combination of a series of centralized database systems. They belong to the same system logically, but are distributed in the physical structure.

The distributed database system has become an important area of information processing and is developing rapidly. The reasons are as follows:

1. It can solve the problem that the Organization is scattered and data needs to be interconnected. For example, in the banking system, the head office and its branches are in different cities or regions in different cities. In terms of business, they need to process their own data and exchange and process each other, this requires a distributed system.

2. If an organizational unit needs to add a new relatively independent organizational unit to expand the organization, the distributed database system can be expanded with minimal impact on the current organization.

3. Load Balancing needs. Data decomposition maximizes local applications, minimizing mutual interference between processors. Load is shared among various processors to avoid critical bottlenecks.

4. When there are several database systems in the current organization and the necessity for implementing global applications is increased, these databases can form a distributed database system from the bottom up.

5. a distributed database system of equal scale is not less likely to fail than a centralized database system. However, due to its failure, it is only applicable to local data applications, therefore, the reliability of the entire system is relatively high.

Features

1. In a distributed database system, the concept of centralized control is not emphasized. It has a hierarchical control structure based on the global database administrator, but each local database administrator has a high degree of autonomy.

2. The concept of Data independence is equally important in distributed database systems. However, a new concept is added, that is, distributed transparency. The so-called distributed transparency means that when writing a program, it seems that the data is not distributed, so transferring the data will not affect the correctness of the program. However, the execution speed of the program is reduced.

3. Different centralized database systems, data redundancy is seen as a required feature in distributed systems. The reason is: first, if you copy data on the desired node, to improve local applicability. When a node fails, you can copy data from other nodes. Therefore, this increases the effectiveness of the system. Of course, the evaluation of optimal redundancy in Distributed Systems is complicated.

The types of distributed systems can be roughly classified into three types:

1. distributed data, but there is only one total? No local database.

2. Hierarchical processing. Each layer has its own database.

3. A fully-dispersed distributed network without central control. There are multiple connection methods between nodes, such as loose connection, close connection, and dynamic connection, broadcast and notification connections.

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What is distributed intelligence?
The Distributed Intelligence of NI LabVIEW 8 combines related technologies and tools to solve some challenges encountered in distributed system development. More importantly, the solution provided by NI LabVIEW 8 distributed intelligence not only solves these challenges, but also is easy to implement. The Distributed Intelligence of LabVIEW 8 includes:

You can program all nodes in a distributed system, including hosts and terminals. You can use LabVIEW graphical programming to program a large number of different types of objects, such as desktop processors, real-time systems, FPGAs, PDAs, embedded microprocessors, and DSPs.
Navigate to the view system of all system nodes-LabVIEW Project Explorer. You can use Project Explorer to view, edit, run, and debug nodes running on any object.
Simplified data sharing programming interface-shared variables. With shared variables, you can easily transfer data between systems (or even between real-time systems) without affecting performance. No communication loop, no rt fifo, no need for low-level TCP functions. You can use a simple dialog box to configure shared variables to transfer data between systems or connect data to different data sources. You can also add data services such as records, alarms, and events-everything can be done with simple conversations.
Synchronization between remote devices and systems or between devices and systems-timing and synchronization are always the key issue for defining high-performance measurement and control systems. Using the NI technology-based system, we can explore the internal device and compile its internal operation mechanism to achieve more flexible solutions than traditional instruments or PLC.

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With the support of the Distributed Computer Operating System, interconnected computers can work together to complete a task.

It can also be explained as follows:
A configuration method for computer hardware and corresponding functional configuration methods. It is a multi-processor computer system. Each processor forms a unified system through an interconnected network. The system uses a distributed computing structure, that is, the tasks processed by the central processor in the original system are distributed to the corresponding processor, so that different processors with different functions can coordinate with each other and share system peripherals and software. This accelerates the processing speed of the system and simplifies the logic structure of the host.