Cloudlets are mobility-enhanced micro data centers located at the edge of a network and serve the mobile or smart device portion of the network. Along with cloud computing, fog and edge computing are becoming popular as well. Fog refers to the network connections between edge devices and the cloud. We have over 1500 global PoPs. So, in the cases, where security is a major concern, Fog and Edge are preferable. They attempt to reduce the amount of data sent to the cloud. An Extension of Cloud Computing — Fog Computing and Edge Computing. Today, the technology has evolved multifold, so much so you can live stream your videos in 4K to the world. Thank you for sharing some key differences between the fog, edge and cloud computing. Embedded hardware obtains data from on-site IIoT devices and passes it to the fog layer. It is going from centralized to distributed architectures, with videos streaming, augmented & virtual reality, and going beyond that which has enabled many advanced features for the end-users. On the other hand, Fog computing shifts the Edge computing tasks to processors that are connected to the LAN hardware or the LAN directly so that they may be physically more distant from the actuators and the sensors. The real opportunity is related to configuring nodes and optimizing performance. On the other hand, Fog and Edge computing are more suitable for the quick analysis required for real-time response. Their differences can be likened to those between an SUV and a racing car, for example. Most enterprises are now migrating towards a fog or edge infrastructure to increase the utilization of their end-user and IIoT devices. This is the key distinction between fog computing vs cloud computing, where all the intelligence and computing are performed on remote servers. Edge computing also improves security by encrypting data closer to the network core, while optimizing data that’s further from the core for performance. Here, full software portability between cloud and edge is a prerequisite. Cloud computing is best suited for long term in-depth analysis of data, while fog and edge computing are more suitable for the quick analysis required for real-time response. Thus, they are more apt for the use cases where the IoT sensors may not have seamless connectivity to the internet. Smart applications that make use of AI or ML usually deal with vast amounts of data, which becomes costly to send or store in a central cloud service. Internet of Things (IoT) has transformed the way businesses work, and the industry has seen a massive shift from on-premise software to cloud computing. it gives a good idea about each technology which helps in understanding the same. “The key difference between the two architectures is exactly where that intelligence and computing power is placed,” … Location of Data Processing The primary difference between cloud computing, Fog computing, and Edge computing is the location where data processing occurs. Data Communication Is it even necessary to send everything to the cloud? By storing and processing data using cloud technology, we have liberated ourselves from the relentless trouble of accessing data in a limited manner. The increased distribution of data processing and storage made possible by these systems reduces network traffic, thus improving operational efficiency. Both Edge computing and Fog computing offer similar functionalities in terms of pushing both intelligence and data to nearby analytic platforms that are located either on, or near to the source of origination of the data, be it be cars, motors, speakers, screens, sensors or pumps. Fog and edge computing are both extensions of cloud networks, which are a collection of servers comprising a distributed network. Fog and cloud both the computing platforms offer the company to manage their communication effectively and efficiently. Difference Between Cloud, Fog, and Edge Computing. Fog computing and edge computing appear similar since they both involve bringing intelligence and processing closer to the creation of data. However, this distinction isn’t always clear, since organizations can be highly variable in their approach to data processing. A fog environment places intelligence at the local area network (LAN). 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