Edge computing is a distributed IT infrastructure, comparable to fog computing. Edge computing is about capturing, analyzing and processing the enormous amounts of data from the Internet of Things( IoT) of smart grids, smart cities, smart homes or automotive technology directly at the point where they are generated.
With edge computing, the computing power is taken over by smart clients, which are IoT devices equipped with intelligence, or by an edge device, directly at the edge of the network (edge), without the data traversing the core network. The advantages of edge computing and edge analytics are that data is processed much faster in the field, data volumes are reduced, time-sensitive data is processed at the point it is generated, and transfer times and delay times are extremely short. On-site data processing reduces the amount of data and network bandwidth required to transfer data to the data center and the cloud. Less time-sensitive data is transferred to the cloud, where it is analyzed and processed for long-term storage.
Edge computing involves a wide variety of networks and network infrastructures. These include wireless sensor networks(WSN), peer-to-peer networks( P2P), cellular networks, into local area networks ( LAN) and WLANs, wide area networks(WAN), and metropolitan area networks ( MAN). In terms of processing, edge computing can work with cloud computing, fog computing, grid computing, and distributed computing.
An interesting alternative to classic edge computing is mobile edge computing( MEC), because the 5th generationmobile network( 5G) supports latency-sensitive services with ultra-high reliability and low latency communication( uRLLC).