Today's businesses are flooded with data that have been extracted in vast quantities from sensors and IoT devices in real-time. The traditional cloud computing solutions are facing new challenges, so edge computing and fog computing have emerged as potential solutions to process and analyze data in real-time. Edge computing, cloud computing, and fog computing though seem the same as related to distributed computing, but are different in technical functionality. The common focus of these three is related to physical deployment and storage.

The term "Edge computing" refers to a computing architecture designed to bring processing power closer to the device or data source, focusing on handling data at the "edge" or near the network's periphery. The concept of edge computing objective is to minimize the amount of data sent to a central server for processing, thereby reducing network latency and enhancing overall system performance. This approach has emerged as a result of the advancements in Internet of Things (IoT) devices.

The term “Cloud computing “refers to accessing computing power via the internet or “cloud”. Cloud services refer to servers, storage, and databases. It provides the speed, scalability, and flexibility for business data to develop, innovate, and support business IT solutions.

The term “Fog computing” refers to accessing computing power in a decentralized manner where data, computation, storage, and applications are located, distributed, or executed between the data source and the cloud. The term "fog" is derived from the meteorological concept of a cloud near the ground, similar to how fog concentrates at the edge of the computer network.

Edge Computing vs Cloud Computing: The key differences between Edge computing and Cloud computing are following from location, latency, bandwidth, processing power, and scalability. The Edge computing focuses on storage resources closer to the data source point, processing data locally with limited resources whereas cloud computing relies on centralized data centers anywhere in the world and processes on a high scale. The applications of edge computing are real-time data processing from IoT devices, autonomous vehicles, and healthcare. Similarly, cloud computing applications are in big data analytics, machine learning, and artificial intelligence.

Edge Computing vs Fog Computing: The key differences between edge computing and fog computing are following from architecture, scope, latency, bandwidth, and processing power. While edge computing works on a decentralized architecture with high bandwidth connectivity to transmit data to and from the cloud, in other way fog computing uses a hierarchical architecture with multilevel connections to fog nodes with less bandwidth, which can be more powerful than edge devices. The application areas of fog computing are in industrial automation, smart cities, and multimedia applications.

Cloud Computing vs Fog Computing: The key differences between cloud computing and fog computing are in location, latency, scalability, and security. While Cloud computing is a highly scalable centralized model for storing, processing, and accessing data centers, while fog computing is a less scalable decentralized model and processes data closer to edge devices. The best feature of the cloud is securing data with advanced features as compared to fog computing.

In a nutshell, Fog computing extends cloud computing and services to an enterprise’s network for real-time data analysis and decision-making. Whereas, edge computing has functionality to a higher level in processing data directly on devices ensuring high operational speed and efficiency. These computing frameworks can help businesses enhance operational efficiency, drive informed decision-making, and ultimately accelerate revenue generation and marketing initiatives.

References:

• [1] Asghari, A., & Sohrabi, M. K. (2024). Server placement in mobile cloud computing: A comprehensive survey for edge computing, fog computing and cloudlet. Computer Science Review, 51, 100616.

• [2] Huaranga-Junco, E., González-Gerpe, S., Castillo-Cara, M., Cimmino, A., & García-Castro, R. (2024). From cloud and fog computing to federated-fog computing: A comparative analysis of computational resources in real-time IoT applications based on semantic interoperability. Future Generation Computer Systems, 159, 134-150.

• [3] Ometov, A., Molua, O. L., Komarov, M., & Nurmi, J. (2022). A survey of security in cloud, edge, and fog computing. Sensors, 22(3), 927.

• [4] Abdulqadir, H. R., Zeebaree, S. R., Shukur, H. M., Sadeeq, M. M., Salim, B. W., Salih, A. A., & Kak, S. F. (2021). A study of moving from cloud computing to fog computing. Qubahan Academic Journal, 1(2), 60-70.