Process the data at the point or near the point where it is being generated and produce the result for real time action, there is a measurable cost in moving all IoT data to a cloud versus processing it at the edge (edge processing), or extending cloud services downward into an edge router (fog computing). In the first place, fog computing aims at extending the Cloud by bringing computational power, storage and communication capabilities to the edge of the network, in support of the IoT.
Edge computing enables connected devices to process data where it is created (at the edge of the network), reducing latency and providing an alternative to sending data to a centralised cloud or data centre for processing, it enables provisioning resources and services outside the cloud, at the edge of the network, closer to end devices or eventually, at locations stipulated by SLAs, additionally, by providing elastic resources at the edge of network, fog computing can better support a variety of emerging applications.
Derived from cloud computing, edge computing aims to collect and process data at the edge of a digital network, close to the source of the data, as data centers evolve with big data, cloud computing and virtualization, organizations are going to need to know how to make storage more efficient, particularly, through the environment detection and the combination of computing, communication and control process, the physical real-time perception and dynamic control function are realized.
Cloud computing is a new way of purchasing computing and storage resources on demand through virtualization technologies. In addition, the edge computing opportunity has inspired a massive rush to market by a wide range of organizations and has generated an awful lot of hype. As well as some interesting trials, product announcements, investments and strategic moves.
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