Fog computing

Fog computing[1][2][3][4] or fog networking, also known as fogging,[5][6] is an architecture that uses edge devices to carry out a substantial amount of computation, storage, and communication locally and routed over the internet backbone.

The OpenFog Consortium is an association of major tech companies aimed at standardizing and promoting fog computing.

Concept

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.[7]

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 (e.g. operational costs, security policies[8], resource exploitation), dense geographical distribution and context-awareness (for what concerns computational and IoT resources), latency reduction and backbone bandwidth savings to achieve better quality of service (QoS)[9] and edge analytics/stream mining, resulting in superior user-experience[10] and redundancy in case of failure while it is also able to be used in Assisted Living scenarios.[11][12][13][14][15][16]

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.[17][18][19][20][21]

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.[22]

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.[23]

History

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.[2][3]

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.[24] Cisco Sr. Managing-Director Helder Antunes became the consortium's first chairman and Intel's Chief IoT Strategist Jeff Fedders became its first president.[25]

Definition

Both cloud computing and fog computing provide storage, applications, and data to end-users. However, fog computing is closer to end-users and has wider geographical distribution.[26]

‘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.[27]

The term 'Fog Computing' was defined by Prof. Jonathan Bar-Magen Numhauser in the year 2011 as part of his PhD dissertation project proposal. In January 2012 he presented the concept in the Third International Congress of Silenced Writings in the University of Alcala and published in an official source[1][7].

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, storage resources, and services on or close to devices and systems in the control of end-users.[28][29] Fog computing is a medium weight and intermediate level of computing power.[30] Rather than a substitute, fog computing often serves as a complement to cloud computing.[31]

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.[32] This paradigm supports vertically-isolated, latency-sensitive applications by providing ubiquitous, scalable, layered, federated, distributed computing, storage, and network connectivity. Thus fog computing is most distinguished by distance from the edge. In the theoretical model of fog computing, fog computing nodes are physically and functionally operative between edge nodes and centralized cloud.[33] Much of the terminology is undefined, including key architectural terms like "smart", and the distinction between fog computing from edge computing is not generally agreed. Fog computing is more energy-efficient than cloud computing.[34]

Standards

IEEE adopted the Fog Computing standards proposed by OpenFog Consortium.[35]

See also

References
  1. Bar-Magen Numhauser, Jonathan (2012). Fog Computing introduction to a New Cloud Evolution. Escrituras silenciadas: paisaje como historiografía. Escrituras Silenciadas: Paisaje Como Historiografía / José Francisco Forniés Casals (Ed. Lit.), Paulina Numhauser (Ed. Lit.), Proceedings from the Cies III Congress, January 2012. Spain: University of Alcala. pp. 111–126. ISBN 978-84-15595-84-7.
  2. Bonomi, Flavio; Milito, Rodolfo; Zhu, Jiang; Addepalli, Sateesh (2012-08-17). Fog computing and its role in the internet of things. ACM. pp. 13–16. doi:10.1145/2342509.2342513. ISBN 9781450315197.
  3. Bonomi, Flavio (September 19–23, 2011). "Connected Vehicles, the Internet of Things, and Fog Computing, The 8th ACM International Workshop on VehiculAr Inter-NETworking (VANET 2011), Las Vegas, NV, USA". www.sigmobile.org. Retrieved 2019-08-07.
  4. Bonomi, Flavio (June 4–8, 2011). "Cloud and Fog Computing: Trade-offs and Applications. EON-2011 Workshop, International Symposium on Computer Architecture (ISCA 2011), San Jose, CA, USA". sites.google.com. Retrieved 2019-08-07.
  5. "IoT, from Cloud to Fog Computing". blogs@Cisco - Cisco Blogs. 2015-03-25. Retrieved 2017-04-07.
  6. "What Is Fog Computing? Webopedia Definition". www.webopedia.com. Retrieved 2017-04-07.
  7. Bar-Magen Numhauser, Jonathan (August 25, 2013). XMPP Distributed Topology as a Potential Solution for Fog Computing. MESH 2013 the Sixth International Conference on Advances in Mesh Networks. pp. 26–32. ISBN 9781612082998.
  8. Forti, Stefano; Ferrari, Gian-Luigi; Brogi, Antonio (January 2020). "Secure Cloud-Edge Deployments, with Trust". Future Generation Computer Systems. 102: 775–788. doi:10.1016/j.future.2019.08.020.
  9. Brogi, Antonio; Forti, Stefano (2017). "QoS-aware Deployment of IoT Applications Through the Fog" (PDF). IEEE Internet of Things Journal. PP (99): 1185–1192. doi:10.1109/JIOT.2017.2701408. ISSN 2327-4662.
  10. Cisco RFP-2013-078. Fog Computing, Ecosystem, Architecture and Applications: Also available from the Internet Archive: .
  11. Nikoloudakis, Y.; Panagiotakis, S.; Markakis, E.; Pallis, E.; Mastorakis, G.; Mavromoustakis, C. X.; Dobre, C. (November 2016). "A Fog-Based Emergency System for Smart Enhanced Living Environments". IEEE Cloud Computing. 3 (6): 54–62. doi:10.1109/mcc.2016.118. ISSN 2325-6095.
  12. "What Comes After the Cloud? How About the Fog?". IEEE Spectrum: Technology, Engineering, and Science News. Retrieved 2017-04-07.
  13. "Is There a Buzz Over Fog Computing?". Channelnomics. Retrieved 2017-04-07.
  14. "New Solutions on the Horizon—"Fog" or "Edge" Computing?". The National Law Review. Retrieved 2017-04-07.
  15. Cloud Evolution: Back to the Future?: Archived 2015-10-09 at the Wayback Machine.
  16. Arkian, Hamid Reza; Diyanat, Abolfazl; Pourkhalili, Atefe (2017-03-15). "MIST: Fog-based data analytics scheme with cost-efficient resource provisioning for IoT crowdsensing applications". Journal of Network and Computer Applications. 82: 152–165. doi:10.1016/j.jnca.2017.01.012.
  17. Bonomi, F., Milito, R., Zhu, J., and Addepalli,S. Fog Computing and its Role in the Internet of Things. In Proc of MCC (2012), pp. 13-16..
  18. Cisco-Delivers-Vision-of-Fog-Computing-to-Accelerate-Value-from-Billions-of-Connected-Devices: .
  19. IoT: Out Of The Cloud & Into The Fog: Archived 2015-12-23 at the Wayback Machine.
  20. Distributed intelligence and IoT fog: .
  21. Fog Computing Keeps Data Right Where the Internet of Things Needs It: .
  22. .
  23. Huang, Dijiang; Wu, Huijun (2017-09-08). Mobile Cloud Computing: Foundations and Service Models. Morgan Kaufmann. ISBN 9780128096444.
  24. Janakiram, MSV (18 April 2016). "Is Fog Computing the Next Big Thing in the Internet of Things". Forbes Magazine. Retrieved 18 April 2016.
  25. "Industrial Internet Consortium". www.iiconsortium.org.
  26. F. Bonomi, R. Milito, J. Zhu, and S. Addepalli, "Fog computing and its role in the internet of things," in Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, ser. MCC’12. ACM, 2012, pp. 13–16.
  27. "cloud computing | Definition of cloud computing in English by Oxford Dictionaries". Oxford Dictionaries | English. Retrieved 2017-11-10.
  28. Zhang, Chiang (2016). Fog and IoT: An Overview of Research Opportunities. IEEE Internet of Things Journal. 3. pp. 854–864. doi:10.1109/EuCNC.2017.7980667. ISBN 978-1-5386-3873-6.
  29. Ostberg; et al. (2017). "Reliable Capacity Provisioning for Distributed Cloud/Edge/Fog Computing Applications". Networks and Communications (EuCNC), 2017 European Conference on. 3 (6): 854–864. doi:10.1109/JIOT.2016.2584538.
  30. Perera, Charith; Qin, Yongrui; Estrella, Julio C.; Reiff-Marganiec, Stephan; Vasilakos, Athanasios V. (2017-10-09). "Fog Computing for Sustainable Smart Cities: A Survey" (PDF). ACM Computing Surveys. 50 (3): 32. arXiv:1703.07079. Bibcode:2017arXiv170307079P. doi:10.1145/3057266. ISSN 0360-0300.
  31. Matt, Christian (2018-04-19). "Fog Computing" (PDF). Business & Information Systems Engineering. 60 (4): 351–355. doi:10.1007/s12599-018-0540-6. ISSN 2363-7005.
  32. "Fog brings the cloud closer to the ground: Cisco innovates in fog computing". newsroom.cisco.com. Retrieved 2019-01-24.
  33. Sarkar, S.; Misra, S. (2016). "Theoretical modelling of fog computing: a green computing paradigm to support IoT applications". IET Networks. 5 (2): 23–29. doi:10.1049/iet-net.2015.0034. ISSN 2047-4954.
  34. Sarkar, S.; Chatterjee, S.; Misra, S. (2018). "Assessment of the Suitability of Fog Computing in the Context of Internet of Things". IEEE Transactions on Cloud Computing. 6 (1): 46–59. doi:10.1109/TCC.2015.2485206. ISSN 2168-7161.
  35. "IEEE 1934-2018 - IEEE Standard for Adoption of OpenFog Reference Architecture for Fog Computing". standards.ieee.org.

Further reading
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