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The OpenFog Consortium was an association of major tech companies aimed at standardizing and promoting fog computing.. Fog computing [1] [2] or fog networking, also known as fogging, [3] [4] is an architecture that uses edge devices to carry out a substantial amount of computation (edge computing), storage, and communication locally and routed over the Internet backbone.
Fog robotics mainly consists of a fog robot server and the cloud. [3] It acts as a companion to cloud by shoving the data near to the user with the help of a local server. . Moreover, these servers are adaptable, consists of processing power for computation, network capability, and secured by sharing the outcomes to other robots for advanced performance with the lowest possible late
Hall and his correspondents soon realized that utility fog could be manufactured en masse to occupy the entire atmosphere of a planet and replace any physical instrumentality necessary to human life. By foglets exerting concerted force, an object or human could be carried from location to location.
The idea for a consortium centered on the advancement and dissemination of fog computing was thought up by Helder Antunes, a Cisco executive with a history in IoT, Mung Chiang, then a Princeton University professor and now President of Purdue University, [13] and Dr. Tao Zhang, a Cisco Distinguished Engineer and CIO for the IEEE Communications ...
Fog computing is a viable alternative to prevent such a large burst of data flow through the Internet. [144] The edge devices ' computation power to analyze and process data is extremely limited. Limited processing power is a key attribute of IoT devices as their purpose is to supply data about physical objects while remaining autonomous.
Smartdust [1] is a system of many tiny microelectromechanical systems (MEMS) such as sensors, robots, or other devices, that can detect, for example, light, temperature, vibration, magnetism, or chemicals.
The efficiency of algorithms affects the amount of computer resources required for any given computing function and there are many efficiency trade-offs in writing programs. Algorithm changes, such as switching from a slow (e.g. linear) search algorithm to a fast (e.g. hashed or indexed) search algorithm can reduce resource usage for a given ...
Natural computing, [1] [2] also called natural computation, is a terminology introduced to encompass three classes of methods: 1) those that take inspiration from nature for the development of novel problem-solving techniques; 2) those that are based on the use of computers to synthesize natural phenomena; and 3) those that employ natural materials (e.g., molecules) to compute.