Cisco working on carve out a new computing category introduce as Fog Computing by combining two existing categories “Internet of Things” + “cloud computing”. Fog computing, also known as fogging, is a model in which data, processing and applications are concentrated in devices at the network edge rather than existing almost entirely in the cloud.
(When people talk about “edge computing,” what they literally mean is the edge of the network, the periphery where the Internet ends and the real world begins. Data centers are in the “center” of the network, personal computers, phones,surveillance cameras and IoT devices are on the edge.)
The problem of how to get things done when we’re dependent on the cloud is becoming all the more acute as more and more objects become “smart,” or able to sense their environments, connect to the Internet, and even receive commands remotely. Everything from jet engines to refrigerators is being pushed onto wireless networks and joining the “Internet of Things. Modern 3G and 4G cellular networks simply aren’t fast enough to transmit data from devices to the cloud at the pace it is generated, and as every mundane object at home and at work gets in on this game, it’s only going to get worse unless bandwidth increasing.
If devices at the network routing can be self learning, organizing and healing it will decentralize the network. Cisco wants to turn its routers into hubs for gathering data and making decisions about what to do with it. In Cisco’s vision, its smart routers will never talk to the cloud unless they have to—say, to alert operators to an emergency on a sensor-laden rail car on which one of these routers acts as the nerve center.
Fog Computing can enable a new breed of aggregated applications and services, such as smart energy distribution. This is where energy load-balancing applications run on network edge devices that automatically switch to alternative energies like solar and wind, based on energy demand, availability, and the lowest price.
The Fog computing applications and services include :
- Interplay between the Fog and the Cloud. Typically, the Fog platform supports real-time, actionable analytics, processes, and filters the data, and pushes to the Cloud data that is global in geographical scope and time.
- Data collection and analytics (pulled from access devices, pushed to Cloud)
- Data storage for redistribution (pushed from Cloud, pulled by downstream devices)
- Technologies that facilitate data fusion in the above contexts.
- Analytics relevant for local communities across various verticals (ex: advertisements, video analytics, health care, performance monitoring, sensing etc.)
- Methodologies, Models and Algorithms to optimize the cost and performance through workload mobility between Fog and Cloud.
Another example are smart traffic lights. A video camera senses an ambulance’s flashing lights and then automatically changes streetlights for the vehicle to pass through traffic. Also through Fog Computing, sensors on self-maintaining trains can monitor train components. If they detect trouble, they send an automatic alert to the train operator to stop at the next station for emergency maintenance.