Skip to main content
SpringerLink
Log in
Book cover

NEO 2016 pp 87–115Cite as

Distributing Computing in the Internet of Things: Cloud, Fog and Edge Computing Overview

  • Chapter
  • First Online:

Part of the book series: Studies in Computational Intelligence ((SCI,volume 731))

Abstract

The main postulate of the Internet of things (IoT) is that everything can be connected to the Internet, at anytime, anywhere. This means a plethora of objects (e.g. smart cameras, wearables, environmental sensors, home appliances, and vehicles) are ‘connected’ and generating massive amounts of data. The collection, integration, processing and analytics of these data enable the realisation of smart cities, infrastructures and services for enhancing the quality of life of humans. Nowadays, existing IoT architectures are highly centralised and heavily rely on transferring data processing, analytics, and decision-making processes to cloud solutions. This approach of managing and processing data at the cloud may lead to inefficiencies in terms of latency, network traffic management, computational processing, and power consumption. Furthermore, in many applications, such as health monitoring and emergency response services, which require low latency, delay caused by transferring data to the cloud and then back to the application can seriously impact their performances. The idea of allowing data processing closer to where data is generated, with techniques such as data fusion, trending of data, and some decision making, can help reduce the amount of data sent to the cloud, reducing network traffic, bandwidth and energy consumption. Also, a more agile response, closer to real-time, will be achieved, which is necessary in applications such as smart health, security and traffic control for smart cities. Therefore, this chapter presents a review of the more developed paradigms aimed to bring computational, storage and control capabilities closer to where data is generated in the IoT: fog and edge computing, contrasted with the cloud computing paradigm. Also an overview of some practical use cases is presented to exemplify each of these paradigms and their main differences.

This is a preview of subscription content, log in via an institution.

We’re sorry, something doesn't seem to be working properly.

Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

References

  1. Zhou, H.: The Internet of Things in the Cloud: A Middleware Perspective. CRC Press, Boca Raton (2013)

    Google Scholar 

  2. Weiser, M., Gold, R., Brown, J.S.: The origins of ubiquitous computing research at PARC in the late 1980s. IBM Syst. J. 38(4), 693–696 (1999)

    Article  Google Scholar 

  3. Ashton, K.: That “Internet of things” thing. RFiD J. 22(7), 97–114 (2009)

    Google Scholar 

  4. Uckelmann, D., Harrison, M., Michahelles, F.: An architectural approach towards the future Internet of things. In: Uckelmann, D., Harrison, M., Michahelles, F. (eds.) Architecting the Internet of Things, pp. 1–24. Springer, Berlin (2011)

    Chapter  Google Scholar 

  5. Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M.: Internet of things (IoT): a vision, architectural elements, and future directions. Future Gener. Comput. Syst. 29(7), 1645–1660 (2013)

    Article  Google Scholar 

  6. Kotis, K., Katasonov, A.: Semantic interoperability on the web of things: the semantic smart gateway framework. In: Proceedings of the IEEE Sixth International Conference on Complex, Intelligent and Software Intensive Systems (CISIS), pp. 630–635 (2012)

    Google Scholar 

  7. Mazhelis, O., Warma, H., Leminen, S., Ahokangas, P., Pussinen, P., Rajahonka, M., Siuruainen, R., Okkonen, H., Shveykovskiy, A., Myllykoski, J.: Internet-of-things market, value networks, and business models: State of the art report. University of Jyvaskyla. http://internetofthings.fi/extras/IoTSOTAReport2013.pdf. Accessed 23 February 2017 (2013)

  8. McFadin, P.: Internet of things: where does the data go? WIRED. Accessed 15 Jan 2017 (2015). https://www.wired.com/insights/2015/03/internet-things-data-go/

  9. Dey, S., Mukherjee, A., Paul, H.S., Pal, A.: Challenges of using edge devices in IoT computation grids. In: Porceedings of IEEE 2013 International Conference on Parallel and Distributed Systems (ICPADS), pp. 564–569 (2013)

    Google Scholar 

  10. MQTT. Accessed 17 April 2017. http://mqtt.org/documentation

  11. Krawiec, P., Sosnowski, M., Batalla, J.M., Mavromoustakis, C.X., Mastorakis, G., Pallis, E.: Survey on technologies for enabling real-time communication in the web of things. In: Batalla, J.M. et al. (eds.) Beyond the Internet of Things, pp. 323–339. Springer International Publishing, Switzerland (2017)

    Google Scholar 

  12. CoAP. Accessed 17 April 2017. http://coap.technology/

  13. Patierno, P.: Hybrid IoT: On fog computing, gateways, and protocol translation. DZone/IoT Zone. Accessed 19 Dec 2016 (2016). https://dzone.com/articles/the-hybrid-internet-of-things-1

  14. Cox, P.A.: Mobile cloud computing devices, trends, issues, and the enabling technologies, developerWorks, IBM. Accessed 20 Dec 2016 (2011). https://www.ibm.com/developerworks/cloud/library/cl-mobilecloudcomputing/cl-mobilecloudcomputing-pdf.pdf

  15. IBM Watson.: The power of analytics at the edge. IBM. Accessed 15 November 2016 (2016). http://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=WWS12351USEN

  16. Rayes, A., Salam, S.: Fog computing. In: Internet of Things — From Hype to Reality, pp. 139–164 . Springer International Publishing AG. (2017)

    Google Scholar 

  17. CISCO: Connections counter: The Internet of everything in motion. Accessed 3 March 2017 (2013). http://newsroom.cisco.com/feature-content?articleId=1208342

  18. Nielsen, J.: Nielsen’s law of Internet bandwidth. Accessed 3 March 2017 (1998). https://www.nngroup.com/articles/law-of-bandwidth/

  19. Byers, C.C., Wetterwald, P.: Fog computing distributing data and intelligence for resiliency and scale necessary for IoT: the internet of things (Ubiquity symposium). Ubiquity 2015, 4:1–4:12 (2015)

    Article  Google Scholar 

  20. Internet Edge Solution Overview. Accessed 5 February 2017 (2010). http://www.cisco.com/c/en/us/td/docs/solutions/Enterprise/WAN_and_MAN/Internet_Edge/InterEdgeOver.pdf

  21. Biron, J., Follett, J.: Foundational Elements of an IoT Solution. O’Reilly Media Inc, Sebastopol (2016)

    Google Scholar 

  22. Mell, P., Grance, T.: The NIST Definition of Cloud Computing, pp. 800–145. NIST Special Publication (2011)

    Google Scholar 

  23. Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., Zaharia, M.: A view of cloud computing. Commun. ACM 53(4), 50–58 (2010)

    Article  Google Scholar 

  24. What is cloud computing? IBM. Accessed 3 March 2017 (2017). https://www.ibm.com/cloud-computing/learn-more/what-is-cloud-computing/

  25. Vaquero, L.M., Rodero-Merino, L.: Finding your way in the fog: towards a comprehensive definition of fog computing. ACM SIGCOMM Comput. Commun. Rev. 44(5), 27–32 (2014)

    Article  Google Scholar 

  26. Dinh, H.T., Lee, C., Niyato, D., Wang, P.: A survey of mobile cloud computing: architecture, applications, and approaches. Wireless communications and mobile computing 13(18), 1587–1611 (2013)

    Article  Google Scholar 

  27. Tordera, E. M., Masip-Bruin, X., Garcia-Alminana, J., Jukan, A., Ren, G. J., Zhu, J., Farre, J.: What is a Fog Node: a tutorial on current concepts towards a common definition (2016). arXiv:1611.09193

  28. Bonomi, F., Milito, R., Zhu, J., Addepalli, S.: Fog computing and its role in the Internet of things. In: Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, pp. 13–16. Helsinki, Finland, (2012)

    Google Scholar 

  29. Varghese, B., Wang, N., Nikolopoulos, D.S., Buyya, R.: Feasibility of fog computing (2017). arXiv:1701.05451

  30. OpenFog reference architecture for fog computing, OpenFog Consortium. OPFRA001.020817. Accessed 3 March 2017 (2017). https://www.openfogconsortium.org/ra/

  31. Stojmenovic, I.: Fog computing: a cloud to the ground support for smart things and machine-to-machine networks. In: IEEE Australasian Telecommunication Networks and Applications Conference (ATNAC), pp. 117–122 (2014)

    Google Scholar 

  32. Yi, S., Li, C., Li, Q.: A survey of fog computing: concepts, applications and issues. In: Proceedings of the 2015 Workshop on Mobile Big Data. ACM (2015)

    Google Scholar 

  33. Garcia-Lopez, P., Montresor, A., Epema, D., Datta, A., Higashino, T., Iamnitchi, A., Barcellos, M., Felber, P., Riviere, E.: Edge-centric computing: vision and challenges. ACM SIGCOMM Comput. Commun. Rev. 45(5), 37–42 (2015)

    Article  Google Scholar 

  34. Reinders, J.: Intel Threading Building Blocks: Outfitting C++ for Multi-core Processor Parallelism. O’Reilly, Sebastopol (2007)

    Google Scholar 

  35. Varghese, B., Wang, N., Barbhuiya, S., Kilpatrick, P., Nikolopoulos, D.S.: Challenges and opportunities in edge computing. In: IEEE International Conference on Smart Cloud (SmartCloud), pp. 20–26 (2016)

    Google Scholar 

  36. Mobile edge computing - Introductory technical white paper. ETSI. https://portal.etsi.org/portals/0/tbpages/mec/docs/mobile-edge_computing_-_introductory_technical_white_paper_v1%2018-09-14.pdf. Accessed 3 March 2017 (2014)

  37. Beck, M.T., Werner, M., Feld, S., Schimper, S.: Mobile edge computing: a taxonomy. In: Proceedings of the Sixth International Conference on Advances in Future Internet (2014)

    Google Scholar 

  38. Ahmed, A., Ahmed, E.: A survey on mobile edge computing. In: IEEE 10th International Conference on Intelligent Systems and Control (ISCO), pp. 1–8 (2016)

    Google Scholar 

  39. Satyanarayanan, M., Bahl, P., Caceres, R., Davies, N.: The case for VM-based cloudlets in mobile computing. IEEE Pervasive Comput. 8(4), 2–11 (2009)

    Article  Google Scholar 

  40. Satyanarayanan, M., Chen, Z., Ha, K., Hu, W., Richter, W., Pillai, P.: Cloudlets: at the leading edge of mobile-cloud convergence. In: Proceedings of IEEE 6th International Conference on Mobile Computing, Applications and Services (MobiCASE), pp. 1–9 (2014)

    Google Scholar 

  41. Gao, L., Luan, T.H., Liu, B., Zhou, W., Yu, S.: Fog computing and its applications in 5G. In: 5G Mobile Communications, pp. 571–593. Springer International Publishing, Switzerland (2017)

    Google Scholar 

  42. Abawajy, J.H., Hassan, M.M.: Federated Internet of things and cloud computing pervasive patient health monitoring system. IEEE Commun. Mag. 55(1), 48–53 (2017)

    Article  Google Scholar 

  43. Yang, C., Yu, M., Hu, F., Jiang, Y., Li, Y.: Utilizing cloud computing to address big geospatial data challenges. Comput. Environ. Urban Syst. 61, 120–128 (2017)

    Article  Google Scholar 

  44. Bellavista, P., Zanni, A.: Feasibility of fog computing deployment based on Docker containerization over RaspberryPi. In: Proceedings of the ACM 18th International Conference on Distributed Computing and Networking. Hyderabad, India (2017)

    Google Scholar 

  45. Kura. Accessed 3 March 2017. https://eclipse.org/kura

  46. Docker. Accessed 3 March 2017. https://www.docker.io

  47. Raspberry Pi. Accessed 17 May 2017. https://www.raspberrypi.org/

  48. Andriopoulou, F., Dagiuklas, T., Orphanoudakis, T.: Integrating IoT and fog computing for healthcare service delivery. In: Keramidas, G. et al. (eds.) Components and Services for IoT Platforms, pp. 213–232. Springer International Publishing, Switzerland (2017)

    Google Scholar 

  49. Hu, W., Gao, Y., Ha, K., Wang, J., Amos, B., Chen, Z., Pillai, P., Satyanarayanan, M.: Quantifying the impact of edge computing on mobile applications. In: Proceedings of the 7th ACM SIGOPS Asia-Pacific Workshop on Systems. Hong Kong, China (2016)

    Google Scholar 

  50. Habak, K., Ammar, M., Harras, K.A., Zegura, E.: Femto clouds: leveraging mobile devices to provide cloud service at the edge. In: IEEE 8th International Conference on Cloud Computing (CLOUD), pp. 9–16 (2015)

    Google Scholar 

Download references

Acknowledgements

The authors acknowledge the support to carry out this work from Instituto Politécnico Nacional under grant SIP-1894.

Author information

Authors and Affiliations

  1. Instituto Politécnico Nacional Centro de Investigación en Computación, Mexico City, Mexico

    P. J. Escamilla-Ambrosio, E. Aguirre-Anaya, R. Acosta-Bermejo & M. Salinas-Rosales

  2. Instituto Politécnico Nacional Escuela Superior de Ingeniería Mecánica y Eléctrica, Unidad Zacatenco, Mexico City, Mexico

    A. Rodríguez-Mota

Authors
  1. P. J. Escamilla-Ambrosio
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Rodríguez-Mota
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. E. Aguirre-Anaya
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. R. Acosta-Bermejo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. Salinas-Rosales
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P. J. Escamilla-Ambrosio .

Editor information

Editors and Affiliations

  1. Instituto Tecnológico de Tijuana, Tijuana, Mexico

    Yazmin Maldonado

  2. Instituto Tecnológico de Tijuana, Tijuana, Mexico

    Leonardo Trujillo

  3. Departamento de Computación, CINVESTAV-IPN, Mexico City, Mexico

    Oliver Schütze

  4. University of Strathclyde, Glasgow, United Kingdom

    Annalisa Riccardi

  5. University of Strathclyde, Glasgow, United Kingdom

    Massimiliano Vasile

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Cite this chapter

Escamilla-Ambrosio, P.J., Rodríguez-Mota, A., Aguirre-Anaya, E., Acosta-Bermejo, R., Salinas-Rosales, M. (2018). Distributing Computing in the Internet of Things: Cloud, Fog and Edge Computing Overview. In: Maldonado, Y., Trujillo, L., Schütze, O., Riccardi, A., Vasile, M. (eds) NEO 2016. Studies in Computational Intelligence, vol 731. Springer, Cham. https://doi.org/10.1007/978-3-319-64063-1_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-64063-1_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64062-4

  • Online ISBN: 978-3-319-64063-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation