What is Distributed Computing?
Distributed computing is a software system model of sharing components across nodes or computers, but which is managed as a single system. A distributed computing architecture improves performance, efficiency, and resilience. This approach is commonly used for application and database design due to its reliability and scalability.
Distributed computing environments can be designed within local networks or using a wide area network (WAN) if component machines are in disparate locations. The typical design is a three-tier model:
- The user interface on the end-user PC or end device.
- The application tier on a remote computer which handles application processing.
- The data tier on another computer which offers centralized database access and handles processing algorithms.
While the three-tier model is the most common among enterprises, other models include client-server (in which clients contact a server for data), n-tier (in which web applications forward requests to enterprise services), and peer-to-peer (in which responsibilities are divided across all peer computers).
Benefits of Distributed Computing
Distributed computing networks have many benefits to the organizations who choose to use them, including:
- Efficiency – breaking down complex requests and distributing them, simplifying the request through parallel computing.
- Resilience – using multiple computers to provide services or fulfill requests increases resilience and redundancy, since if a single node or data center location goes down, requests are redirected to the other nodes on the system.
- Scalability – new hardware can be added to a distributed computing network as required.
- Cost-effectiveness – hardware requirements are low-cost and available off-the- shelf without specialty requirements, and due to scalability, there is no need to purchase more components than required.
- Performance – each computer in a cluster can handle elements of processes and tasks simultaneously.
Case Study: Risk Monitoring in Fortune-100 Financial Firm
DownloadWhat Are Some Distributed Computing Use Cases?
Cloud and distributed computing is an approach used across many industries and organizations today. A few common and popular use cases include:
Healthcare and Life Sciences
Distributed computing platforms are useful in the healthcare and life sciences space, where complex data sets are commonplace. A distributed approach means drug research and gene structure analysis are handled and processed more rapidly.
This model also supports doctors in diagnosing patients by processing complex images including CT scans, x-rays, and MRIs. With gene data processing, early detection of diseases such as cancer, cystic fibrosis, and Alzheimer’s are possible.
Financial Services and FinTech
In the financial services industry, organizations use distributed computing to run economic simulations to assess portfolio risks, predict market events, and enable more insightful business decision making. Distributed databases support high-volume financial transactions, and monitoring increases fraud detection and protection.
Environment and Energy
In order to make better-informed choices related to sustainability and climate-friendliness, the energy sector uses distributed computing models. These systems can analyze data streams at high volumes, and process data from intelligent devices and sensors.
Environmental organizations rely on distributed computing for seismic data monitoring and processing. Energy companies use distributed computing for proactive risk management.
Engineering and Research
Using distributed systems, engineering entities can use simulations to model complex structures, improve product design, and design more efficient products. Using highly intricate models to study the behavior of liquids, engineers can improve car or aircraft design. Computational modeling enables engineers to test new electronics or consumer products, fine-tuning the outcome before building prototypes and thereby saving time,
money, and resources.
