Summary
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This is expected to improve response times and save bandwidth. Edge computing is an architecture rather than a specific technology, and a topology- and location-sensitive form of distributed computing. The origins of edge computing lie in content distributed networks that were created in the late 1990s to serve web and video content from edge servers that were deployed close to users. In the early 2000s, these networks evolved to host applications and application components on edge servers, resulting in the first commercial edge computing services that hosted applications such as dealer locators, shopping carts, real-time data aggregators, and ad insertion engines. Internet of things (IoT) is an example of edge computing. A common misconception is that edge and IoT are synonymous. One definition of edge computing is the use of any type of computer program that delivers low latency nearer to the requests. Karim Arabi, in an IEEE DAC 2014 Keynote and subsequently in an invited talk at MIT's MTL Seminar in 2015, defined edge computing broadly as all computing outside the cloud happening at the edge of the network, and more specifically in applications where real-time processing of data is required. Thus, edge computing does not have the climate-controlled advantages of data centers despite the large amount of processing power necessary. The term is often used as synonymous with fog computing. This especially is quite relevant for small deployments. However, when the deployment size is large, e.g., for Smart Cities, fog computing can be a distinct layer between the Edge and the Cloud. Hence in such deployments, Edge layer is a distinct layer too which has specific responsibilities. According to The State of the Edge report, edge computing concentrates on servers "in proximity to the last mile network".
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