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.
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. However, a common aspect 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 Assisted Living 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’ is 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’ is 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.
National Institute of Standards and Technology in March, 2018 released a definition of fog computing adopting much of Cisco's commercial terminology as NIST Special Publication 500-325, Fog Computing Conceptual Model, that defines fog computing as a 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. As per the theoretical model of fog computing, fog computing nodes are physically and functionally operative between edge nodes and centralized cloud. 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. Fog computing is also considered to be more energy efficient as compared to cloud computing.
IEEE adopted the Fog Computing standards proposed by OpenFog Consortium.
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