The distributed computing model harnesses the resources of multiple networked computers to solve a problem. Each computer within the distributed system has its own processing power. However, the distributed system appears to function as one powerful computer.
There are many examples of distributed computing. It is widely used in the financial services industry to support large volumes of financial transactions, identify potential fraud, and conduct simulations. Healthcare organizations rely on distributed computing to analyze medical imaging for clinical diagnoses and drug research. Energy companies use distributed computing to analyze vast amounts of data collected by smart devices.
Edge computing is sometimes considered a subcategory of distributed computing, but there are key differences. The edge model brings computing resources closer to data sources, such as smart devices. The emphasis is on the location of the data processing rather than on the system's distributed nature.
There are several types of distributed computing architectures:
Edge computing is similar to client-server computing. Edge devices may communicate with each other, with edge device gateways, or with servers. They collect and transmit data but may have limited processing power. An edge device gateway or server processes the data, which may be sent to the cloud for further analysis. Like distributed computing, there are various types of edge computing.
Centralized computing systems are still widely used today. They play a key role in the day-to-day operations of many of the world’s largest corporations. Banking, aviation, retail, healthcare, and government are among the industries that rely heavily on mainframes. However, distributed computing systems provide many tangible benefits over centralized systems, such as:
You can scale distributed computing systems by adding more nodes. This gives the system more processing power and storage to handle your workload. Adding nodes is relatively inexpensive compared to upgrading a centralized system.
With distributed computing, there’s no single point of failure. Because multiple nodes in a distributed computing system perform the same work, losing one node does not bring down the system.
Distributed systems enable more efficient use of computing resources than centralized systems. They also eliminate the potential bottleneck of a centralized system and can provide greater performance.
Distributed systems tend to be more flexible than centralized systems. They can be reconfigured relatively easily to meet changing requirements.
Fortunately, computing frameworks don’t have to be one or the other. Many organizations today employ centralized and distributed computing frameworks concurrently in their network architectures to get the best of both worlds.
Distributed and edge computing models require a sound data center infrastructure to operate optimally. Enconnex offers high-quality server cabinets with key features that streamline deployment and ongoing management.
Every Enconnex rack or cabinet is easy to maintain, scalable, and manufactured to our exacting standards. Additionally, all cabinets ship fully assembled for simple deployment. Contact one of our data center infrastructure specialists to discuss your requirements.