Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation, storage, communication locally and routed over the internet backbone, and most definitively has input and output from the physical world known as transduction. Fog computing consists of Edge nodes directly performing physical input and output often to achieve sensor input, display output, or full closed loop process control, and may also use smaller Edge Clouds often called as Cloudlets at the Edge or nearer to the Edge than centralized Clouds residing in very large data centers. The processing power in advanced Edge Clouds like those that control autonomous vehicles can be considerable compared to more traditional Edge personal devices such as mobile phones and personal computers.
Fog computing can be perceived both in large cloud systems and big data structures, making reference to the growing difficulties in accessing information objectively. This results in a lack of quality of the obtained content. The effects of fog computing on cloud computing and big data systems may vary; yet, a common aspect that can be extracted is a limitation in accurate content distribution, an issue that has been tackled with the creation of metrics that attempt to improve accuracy.
Fog networking consists of a control plane and a data plane. For example, on the data plane, fog computing enables computing services to reside at the edge of the network as opposed to servers in a data-center. Compared to cloud computing, fog computing emphasizes proximity to end-users and client objectives, dense geographical distribution and local resource pooling, latency reduction and backbone bandwidth savings to achieve better quality of service (QoS) and edge analytics/stream mining, resulting in superior user-experience and redundancy in case of failure while it is also able to be used in AAL scenarios.
Fog networking supports the Internet of Things (IoT) concept, in which most of the devices used by humans on a daily basis will be connected to each other. Examples include phones, wearable health monitoring devices, connected vehicle and augmented reality using devices such as the Google Glass.
SPAWAR, a division of the US Navy, is prototyping and testing a scalable, secure Disruption Tolerant Mesh Network to protect strategic military assets, both stationary and mobile. Machine control applications, running on the mesh nodes, "take over", when internet connectivity is lost. Use cases include Internet of Things e.g. smart drone swarms: .
ISO/IEC 20248 provides a method whereby the data of objects identified by edge computing using Automated Identification Data Carriers [AIDC], a barcode and/or RFID tag, can be read, interpreted, verified and made available into the "Fog" and on the "Edge" even when the AIDC tag has moved on.
In 2012, 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.
On November 19, 2015, Cisco Systems, ARM Holdings, Dell, Intel, Microsoft, and Princeton University, founded the OpenFog Consortium, to promote interests and development in fog computing. Cisco Sr. Managing-Director Helder Antunes became the consortium's first chairman and Intel's Chief IoT Strategist Jeff Fedders became its first president.
Cloud Computing – the practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer . Cloud Computing can be a heavyweight and dense form of computing power.
Fog computing – a term created by Cisco that refers to extending cloud computing to the edge of an enterprise's network. Also known as Edge Computing or fogging, fog computing facilitates the operation of compute, storage, and networking services between end devices and cloud computing data centers. While edge computing is typically referred to the location where services are instantiated, fog computing implies distribution of the communication, computation, and storage resources and services on or close to devices and systems in the control of end-users. Fog computing is a medium weight and intermediate level of computing power. Rather than a substitute, fog computing often serves as a complement to cloud computing.
Mist computing – a lightweight and rudimentary form of computing power that resides directly within the network fabric at the extreme edge of the network fabric using microcomputers and microcontrollers to feed into Fog Computing nodes and potentially onward towards the Cloud Computing platforms.
National Institute of Standards and Technology in March, 2018 released a definition of the Fog computing adopting much of Cisco's commercial terminology as NIST Special Publication 500-325, Fog Computing Conceptual Model that defines Fog computing as an horizontal, physical or virtual resource paradigm that resides between smart end-devices and traditional cloud computing or data center. This paradigm supports vertically-isolated, latency-sensitive applications by providing ubiquitous, scalable, layered, federated, and distributed computing, storage, and network connectivity. Thus Fog Computing is most distinguished by distance from the Edge. Fog Computing is physically and functionally intermediate between Edge nodes and centralized Clouds. Much of the terminology is not defined including key architectural terms like "smart" and the distinction between Fog Computing from Edge Computing does not have generally agreed acceptance.
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