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In 2011, the need to extend cloud computing with fog computing emerged, in order to cope with huge number of IoT devices and big data volumes for real-time low-latency applications. [5] Fog computing, also called edge computing, is intended for distributed computing where numerous "peripheral" devices connect to a cloud.
Decentralized Internet of things, or decentralized IoT, is a modified IoT which utilizes fog computing to handle and balance requests of connected IoT devices in order to reduce loading on the cloud servers and improve responsiveness for latency-sensitive IoT applications like vital signs monitoring of patients, vehicle-to-vehicle communication ...
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 ...
Edge computing is a distributed computing model that brings computation and data storage closer to the sources of data. More broadly, it refers to any design that pushes computation physically closer to a user, so as to reduce the latency compared to when an application runs on a centralized data centre.
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.
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
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