Distributed Systems: An Introduction

Networks

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The earliest example of a distributed system happened in the 1970s when ethernet was invented and LAN (local area networks) were created. For the first time computers would be able to send messages to other systems with a local IP address. Peer-to-peer networks evolved and e-mail and then the Internet as we know it continue to be the biggest, ever growing example of distributed systems. As the internet changed from IPv4 to IPv6, distributed systems have evolved from “LAN” based to “Internet” based.

Telecommunication networks

Telephone and cellular networks are also examples of distributed networks. Telephone networks have been around for over a century and it started as an early example of a peer to peer network. Cellular networks are distributed networks with base stations physically distributed in areas called cells. As telephone networks have evolved to VOIP (voice over IP), it continues to grow in complexity as a distributed network.

Distributed Real-time Systems

Many industries use real-time systems that are distributed locally and globally. Airlines use flight control systems, Uber and Lyft use dispatch systems, manufacturing plants use automation control systems, logistics and e-commerce companies use real-time tracking systems.

Parallel Processing

There used to be a distinction between parallel computing and distributed systems. Parallel computing was focused on how to run software on multiple threads or processors that accessed the same data and memory. Distributed systems meant separate machines with their own processors and memory. With the rise of modern operating systems, processors and cloud services these days, distributed computing also encompasses parallel processing.

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Distributed artificial intelligence

Distributed Artificial Intelligence is a way to use large scale computing power and parallel processing to learn and process very large data sets using multi-agents.

Distributed Database Systems

A distributed database is a database that is located over multiple servers and/or physical locations. The data can either be replicated or duplicated across systems.

Most popular applications use a distributed database and need to be aware of the homogenous or heterogenous nature of the distributed database system.

A homogenous distributed database means that each system has the same database management system and data model. They are easier to manage and scale performance by adding new nodes and locations.

Heterogenous distributed databases allow for multiple data models, different database management systems. Gateways are used to translate the data between nodes and usually happen as a result of merging applications and systems.

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