research-article

Fog Computing Platforms for Smart City Applications: A Survey

Authors:

Thiago Pereira Da Silva,

Frederico Lopes,

Aluizio Rocha Neto,

Flávia C. Delicato,

Paulo F. Pires,

Atslands R. Da RochaAuthors Info & Claims

ACM Transactions on Internet Technology, Volume 22, Issue 4

Article No.: 96, Pages 1 - 32

https://doi.org/10.1145/3488585

Published: 22 December 2022 Publication History

Abstract

Emerging IoT applications with stringent requirements on latency and data processing have posed many challenges to cloud-centric platforms for Smart Cities. Recently, Fog Computing has been advocated as a promising approach to support such new applications and handle the increasing volume of IoT data and devices. The Fog Computing paradigm is characterized by a horizontal system-level architecture where devices close to end-users and IoT devices are used for processing, storage, and networking functions. Fog Computing platforms aim to facilitate the development of applications and systems for Smart Cities by providing services and abstractions designed to integrate data from IoT devices and various information systems deployed in the city. Despite the potential of the Fog Computing paradigm, the literature still lacks a broad, comprehensive overview of what has been investigated on the use of such paradigm in platforms for Smart Cities and open issues to be addressed in future research and development. In this paper, a systematic mapping study was performed and we present a comprehensive understanding of the use of the Fog Computing paradigm in Smart Cities platforms, providing an overview of the current state of research on this topic, and identifying important gaps in the existing approaches and promising research directions.

References

[1]

M. Aazam, I. Khan, A. Abdullah Alsaffar, and E. Huh. 2014. Cloud of things: Integrating internet of things and cloud computing and the issues involved. In 2014 11th International Bhurban Conference on Applied Sciences & Technology (IBCAST) Islamabad, Pakistan. IEEE, 414–419.

[2]

Hosny Abbas, Samir Shaheen, Mohamed Elhoseny, Amit Kumar Singh, and Majid Alkhambashi. 2018. Systems thinking for developing sustainable complex smart cities based on self-regulated agent systems and fog computing. Sustain. Comput. Informatics Syst. 19 (2018), 204–213.

[3]

Gregory Abowd, Anind Dey, Peter Brown, Nigel Davies, Mark Smith, and Pete Steggles. 1999. Towards a better understanding of context and context-awareness. In Proceedings of the 1st International Symposium on Handheld and Ubiquitous Computing. Springer-Verlag, London, UK, 304–307.

Digital Library

[4]

A. Ahmed, H. Arkian, D. Battulga, A. Fahs, M. Farhadi, D. Giouroukis, A. Gougeon, F. O. Gutierrez, Guillaume Pierre, P. Souza Jr., M. Tamiru, and L. Wu. 2019. Fog computing applications: Taxonomy and requirements. CoRR abs/1907.11621 (2019).

[5]

M. Al-khafajiy, T. Baker, M. Asim, Zehua Guo, R. Ranjan, A. Longo, Deepak Puthal, and M. Taylor. 2020. COMITMENT: A fog computing trust management approach. J. Parallel Distributed Comput. 137 (2020), 1–16.

Digital Library

[6]

A. Alavi, P. Jiao, W. Buttlar, and N. Lajnef. 2018. Internet of things-enabled smart cities: State-of-the-art and future trends. Measurement 129 (2018).

[7]

Badraddin Alturki, Stephan Reiff-Marganiec, Charith Perera, and Suparna De. 2019. Exploring the effectiveness of service decomposition in fog computing architecture for the internet of things. CoRR abs/1904.00381 (2019).

[8]

P. Arcaini, E. Riccobene, and P. Scandurra. 2015. Modeling and analyzing MAPE-K feedback loops for self-adaptation. In SEAMS@ICSE, Paola Inverardi and Bradley Schmerl (Eds.). IEEE Computer Society, 13–23.

[9]

H. Atlam, R. Walters, and G. Wills. 2018. Fog computing and the internet of things: A review. Big Data and Cognitive Computing 2, 2 (2018).

[10]

Luigi Atzori, Antonio Iera, and Giacomo Morabito. 2010. The internet of things: A survey. Computer Networks 54, 15 (2010), 2787–2805.

Digital Library

[11]

Hamza Baniata and Attila Kertesz. 2020. A survey on blockchain-fog integration approaches. IEEE Access 8 (2020), 102657–102668.

[12]

A. Baouya, S. Chehida, S. Bensalem, and M. Bozga. 2020. Fog computing and blockchain for massive IoT deployment. In 2020 9th Mediterranean Conf. on Embedded Computing (MECO). 1–4.

[13]

P. Bellavista, J. Berrocal, A. Corradi, S. Das, L. Foschini, and A. Zanni. 2019. A survey on fog computing for the internet of things. Pervasive Mob. Comput. 52 (2019), 71–99. http://dblp.uni-trier.de/db/journals/percom/percom52.html#BellavistaBCDFZ19.

[14]

R. Bosman, J. Lukkien, and R. Verhoeven. 2011. Gateway architectures for service oriented application-level gateways. IEEE Trans. on Consumer Electronics 57, 2 (2011), 453–461.

[15]

P. Bourque and R. Fairley (Eds.). 2014. SWEBOK: Guide to the Software Engineering Body of Knowledge (3.0 ed.). IEEE Computer Society, Los Alamitos.

[16]

A. Brogi, Stefano Forti, and Ahmad Ibrahim. 2018. Deploying fog applications: How much does it cost, by the way?. In CLOSER.

[17]

Ismail Butun, Alparslan Sari, and Patrik Österberg. 2019. Security implications of fog computing on the internet of things. In 2019 IEEE International Conference on Consumer Electronics (ICCE). 1–6.

[18]

Mung Chiang and Tao Zhang. 2016. Fog and IoT: An overview of research opportunities. IEEE Internet of Things Journal 3, 6 (2016), 854–864.

[19]

Edge Computing Consortium. 2016. White Paper of Edge Computing Consortium.

[20]

OpenFog Consortium. 2018. IEEE standard for adoption of OpenFog reference architecture for fog computing. IEEE Std 1934-2018 (2018), 1–176.

[21]

A. Dastjerdi, H. Gupta, R. Calheiros, S. Ghosh, and R. Buyya. 2016. Fog computing: Principles, architectures, and applications. CoRR abs/1601.02752 (2016).

[22]

S. Dirks, C. Gurdgiev, and M. Keeling. 2010. Smarter cities for smarter growth: How cities can optimize their systems for the talent-based economy. SSRN (52010).

[23]

F. Lingen, M. Yannuzzi, A. Jain, R. Mclean, O. Parellada, D. Carrera, J. Ordóñez, A. Gutierrez, D. Montero, J. Marti, R. Maso, and J. Rodriguez. 2017. The unavoidable convergence of NFV, 5G, and fog: A model-driven approach to bridge cloud and edge. IEEE Com. Magazine 55, 8 (2017), 28–35.

Digital Library

[24]

A. Gharaibeh, M. Salahuddin, S. Hussini, A. Khreishah, I. Khalil, M. Guizani, and A. Al-Fuqaha. 2017. Smart cities: A survey on data management, security, and enabling technologies. IEEE Communications Surveys Tutorials 19, 4 (2017), 2456–2501.

[25]

M. Ghobaei-Arani, A. Souri, and A. Rahmanian. 2020. Resource management approaches in fog computing: A comprehensive review. J. Grid Comput. 18, 1 (2020), 1–42.

[26]

Nam Ky Giang, Victor Leung, Makoto Kawano, Takuro Yonezawa, Jin Nakazawa, Rodger Lea, and Matt Broadbent. 2019. CityFlow: Exploiting edge computing for large scale smart city applications. In BigComp. IEEE, 1–4.

[27]

Judy Guevara, Ricardo da Silva Torres, and Nelson da Fonseca. 2020. On the classification of fog computing applications: A machine learning perspective. J. Netw. Comput. Appl. 159 (2020), 102596. http://dblp.uni-trier.de/db/journals/jnca/jnca159.html#GuevaraTF20.

[28]

Judy Guevara and Nelson Fonseca. 2021. Task scheduling in cloud-fog computing systems. Peer-to-Peer Networking and Applications 14 (032021).

[29]

P. Habibi, M. Farhoudi, S. Kazemian, S. Khorsandi, and A. Leon-Garcia. 2020. Fog computing: A comprehensive architectural survey. IEEE Access 8 (2020), 69105–69133.

[30]

Joseph Hellerstein, Jose Faleiro, Joseph Gonzalez, Johann Schleier-Smith, Vikram Sreekanti, Alexey Tumanov, and Chenggang Wu. 2018. Serverless computing: One step forward, two steps back. CoRR abs/1812.03651 (2018).

[31]

Cheol-Ho Hong and Blesson Varghese. 2018. Resource management in fog/edge computing: A survey. CoRR abs/1810.00305 (2018).

[32]

M. Iorga, L. Feldman, R. Barton, M. Martin, N. Goren, and C. Mahmoudi. 2018. Fog Computing Conceptual Model. Technical Report. NIST.

[33]

G. Javadzadeh and A. Rahmani. 2020. Fog computing applications in smart cities: A systematic survey. Wireless Networks 26, 2 (2020), 1433–1457.

Digital Library

[34]

A. Javed et al. 2020. Scalable IoT platform for heterogeneous devices in smart environments. IEEE Access 8 (2020), 211973–211985.

[35]

Y. Karim and R. Hasan. 2020. FogTestBed: A generic architecture for testbed for fog-based systems. In 2020 SoutheastCon. 1–7.

[36]

Jasleen Kaur, Alka Agrawal, and Prof. Raees Khan. 2020. Security issues in fog environment: A systematic literature review. International Journal of Wireless Information Networks 27 (92020).

[37]

Angelos Keromytis, Vishal Misra, and Daniel Rubenstein. 2002. Using overlays to improve network security. In Scalability and Traffic Control in IP Networks II, Vol. 4868. International Society for Optics and Photonics, 245–254.

[38]

Latif Khan, Ibrar Yaqoob, Nguyen Tran, Ahsan Kazmi, Nguyen Tri, and Choong Hong. 2020. Edge-computing-enabled smart cities: A comprehensive survey. IEEE Internet Things J. 7, 10 (2020), 10200–10232. http://dblp.uni-trier.de/db/journals/iotj/iotj7.html#KhanYTKTH20.

[39]

W. Khan, E. Ahmed, S. Hakak, I. Yaqoob, and A. Ahmed. 2019. Edge computing: A survey. Future Generation Computer Systems 97 (2019), 219–235.

Digital Library

[40]

F. Khodadadi, A. V. Dastjerdi, and R. Buyya. 2016. Chapter 1 - Internet of things: An overview. In Internet of Things, Rajkumar Buyya and Amir Vahid Dastjerdi (Eds.). Morgan Kaufmann, 3–27.

[41]

H. Kim, H. Choi, H. Kang, J. An, S. Yeom, and T. Hong. 2021. A systematic review of the smart energy conservation system: From smart homes to sustainable smart cities. Renewable and Sustainable Energy Reviews 140 (2021), 110755.

[42]

B. Kitchenham, T. Dyba, and M. Jorgensen. 2004. Evidence-based software engineering. In Proc. 26th Int. Conf. on Software Engineering. 273–281.

[43]

Arvind W. Kiwelekar, Pramod Patil, Laxman D. Netak, and Sanjay U. Waikar. 2021. Blockchain-based security services for fog computing. Advances in Information Security (2021), 271–290.

[44]

R. LaMothe. 2013. Edge computing. https://moam.info/edge-computing-pacific-northwest-national-laboratory_59d648481723dd08e35b7b77.html.

[45]

D. Lan, A. Taherkordi, F. Eliassen, Z. Chen, and L. Liu. 2020. Deep reinforcement learning for intelligent migration of fog services in smart cities. In ICA3PP (2)(Lecture Notes in Computer Science, Vol. 12453), Meikang Qiu (Ed.). Springer, 230–244.

[46]

D. Lan, A. Taherkordi, F. Eliassen, and G. Horn. 2019. A survey on fog programming: Concepts, state-of-the-art, and research challenges. In DFSD@Middleware. ACM, 1–6. http://dblp.uni-trier.de/db/conf/middleware/dfsd2019.html#LanTEH19.

[47]

C. Lim, K. Kim, and P. Maglio. 2018. Smart cities with big data: Reference models, challenges, and considerations. Cities 82 (2018), 86–99.

[48]

X. Liu, Y. Yang, K. Choo, and H. Wang. 2018. Security and privacy challenges for internet-of-things and fog computing. Wireless Communications and Mobile Computing 2018 (092018), 1–3.

[49]

M. Lopez, A. Lobato, and O. Duarte. 2016. A performance comparison of open-source stream processing platforms. In GLOBECOM. IEEE, 1–6.

[50]

R. Mahmud, R. Kotagiri, and R. Buyya. 2018. Fog Computing: A Taxonomy, Survey and Future Directions. Springer Singapore, 103–130.

[51]

J. McChesney, N. Wang, A. Tanwer, E. Lara, and B. Varghese. 2019. DeFog: Fog computing benchmarks. Proc. of the 4th ACM/IEEE Symposium on Edge Computing (2019).

Digital Library

[52]

M. Mohammadi and A. Al-Fuqaha. 2018. Enabling cognitive smart cities using big data and machine learning: Approaches and challenges. IEEE Communications Magazine 56, 2 (2018), 94–101. http://dblp.uni-trier.de/db/journals/cm/cm56.html#MohammadiA18.

Digital Library

[53]

M. Mohammadi, A. Al-Fuqaha, S. Sorour, and M. Guizani. 2018. Deep learning for IoT big data and streaming analytics: A survey. IEEE Commun. Surv. Tutorials 20, 4 (2018), 2923–2960. http://dblp.uni-trier.de/db/journals/comsur/comsur20.html#MohammadiASG18.

Digital Library

[54]

A. Monzon. 2015. Smart cities concept and challenges: Bases for the assessment of smart city projects. In Int. Conf. on Smart Cities and Green ICT Systems (SMARTGREENS). IEEE, 1–11.

[55]

C. Mouradian, D. Naboulsi, S. Yangui, R. Glitho, M. Morrow, and P. Polakos. 2017. A comprehensive survey on fog computing: State-of-the-art and research challenges. CoRR abs/1710.11001 (2017).

[56]

C. Badii, P. Bellini, D. Cenni, G. Martelli, P. Nesi, and M. Paolucci. 2016. Km4City smart city API: An integrated support for mobility services. In Proceeding of the IEEE International Conference on Smart Computing, SMARTCOMP. IEEE Computer Society, 1–8.

[57]

R. Naha, S. Garg, D. Georgakopoulos, P. Jayaraman, L. Gao, Y. Xiang, and R. Ranjan. 2018. Fog computing: Survey of trends, architectures, requirements, and research directions. IEEE Access 6 (2018), 47980–48009. http://dblp.uni-trier.de/db/journals/access/access6.html#NahaGGJGXR18.

[58]

E. Nakagawa, F. Oquendo, and J. Maldonado. 2014. Reference Architectures. John Wiley & Sons, Ltd, Chapter 2, 55–82.

[59]

S. Nath, H. Gupta, S. Chakraborty, and S. Ghosh. 2018. A survey of fog computing and communication: Current researches and future directions. CoRR abs/1804.04365 (2018). http://dblp.uni-trier.de/db/journals/corr/corr1804.html#abs-1804-04365.

[60]

R. Oma, S. Nakamura, D. Duolikun, T. Enokido, and M. Takizawa. 2018. An energy-efficient model for fog computing in the internet of things (IoT). Internet Things 1-2 (2018), 14–26. http://dblp.uni-trier.de/db/journals/iot/iot1.html#OmaNDE018.

[61]

C. Perera, Y. Qin, J. Estrella, S. Reiff-Marganiec, and A. Vasilakos. 2017. Fog computing for sustainable smart cities: A survey. CoRR (2017).

[62]

David Perez Abreu, Karima Velasquez, Marilia Curado, and Edmundo Monteiro. 2020. A comparative analysis of simulators for the cloud to fog continuum. Simulation Modelling Practice and Theory 101 (2020), 102029.

[63]

I. Petri, O. Rana, A. Zamani, and Y. Rezgui. 2019. Edge-cloud orchestration: Strategies for service placement and enactment. In IC2E. IEEE, 67–75.

[64]

Pawani Porambage, Jude Okwuibe, Madhusanka Liyanage, Mika Ylianttila, and Tarik Taleb. 2018. Survey on multi-access edge computing for internet of things realization. IEEE Communications Surveys Tutorials 20, 4 (2018), 2961–2991.

[65]

C. Puliafito, E. Mingozzi, and G. Anastasi. 2017. Fog computing for the internet of mobile things: Issues and challenges. In SMARTCOMP. IEEE Computer Society, 1–6.

[66]

C. Puliafito, E. Mingozzi, F. Longo, A. Puliafito, and O. Rana. 2019. Fog computing for the internet of things: A survey. ACM Trans. Internet Techn. 19, 2 (2019), 18:1–18:41. http://dblp.uni-trier.de/db/journals/toit/toit19.html#PuliafitoMLPR19.

Digital Library

[67]

E. Renart and D. Balouek. 2019. Challenges in designing edge-based middlewares for the internet of things: A survey. CoRR abs/1912.06567 (2019).

[68]

B. Rocha, L. Silva, T. Batista, E. Cavalcante, and P. Gomes. 2020. An ontology-based information model for multi-domain semantic modeling and analysis of smart city data. In Proc. of the Brazilian Symposium on Multimedia and the Web. 73–80.

[69]

O. Salman, I. Elhajj, A. Chehab, and A. Kayssi. 2018. IoT survey: An SDN and fog computing perspective. Computer Networks 143 (2018), 221–246.

Digital Library

[70]

E. Santana, A. Chaves, M. Gerosa, F. Kon, and D. Milojicic. 2016. Software platforms for smart cities: Concepts, requirements, challenges, and a unified reference architecture. CoRR abs/1609.08089 (2016).

Digital Library

[71]

S. Shaik and S. Baskiyar. 2018. Resource and service management for fog infrastructure as a service. In 2018 IEEE Int. Conf. on Smart Cloud (SmartCloud). 64–69.

[72]

M. Shaw and A. Wolf. 1996. Software Architecture: Perspectives on an Emerging Discipline. Prentice-Hall, Englewood Cliffs, NJ, USA.

Digital Library

[73]

Thiago Silva, Thais Batista, Frederico Lopes, Aluizio Rocha, Flavia Delicato, Paulo Pires, and Atslands Rocha. 2021. Fog Computing Platforms for Smart City Applications - A Survey. (2021). arXiv (to be published).

[74]

M. Sri Raghavendra and P. Chawla. 2018. A review on container-based lightweight virtualization for fog computing. In 2018 7th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). 378–384.

[75]

B. Tang, Z. Chen, G. Hefferman, S. Pei, T. Wei, H. He, and Q. Yang. 2017. Incorporating intelligence in fog computing for big data analysis in smart cities. IEEE Trans. Ind. Informatics 13, 5 (2017), 2140–2150. http://dblp.uni-trier.de/db/journals/tii/tii13.html#TangCHPWHY17.

[76]

B. Tang, Z. Chen, G. Hefferman, T. Wei, H. He, and Q. Yang. 2015. A hierarchical distributed fog computing architecture for big data analysis in smart cities. In ASE BigData & SocialInformatics 2015 (Kaohsiung, Taiwan). New York, NY, USA, Article 28, 6 pages.

[77]

K. Toczé and S. Nadjm-Tehrani. 2018. A taxonomy for management and optimization of multiple resources in edge computing. Wirel. Commun. Mob. Comput. 2018 (2018), 7476201:1–7476201:23.

Digital Library

[78]

Andreas Tolk, Saikou Y. Diallo, and Charles D. Turnitsa. 2007. Applying the levels of conceptual interoperability model in support of integratability, interoperability, and composability for system-of-systems engineering. Journal of Systems, Cybernetics, and Informatics 5, 5 (2007).

[79]

M. Yannuzzi, F. van Lingen, A. Jain, O. Lluch Parellada, M. Flores, D. Carrera, J. Pérez, D. Montero, P. Chacin, A. Corsaro, and A. Olive. 2017. A new era for cities with fog computing. IEEE Internet Computing 21, 2 (2017), 54–67.

[80]

D. Yu, Y. Jin, Y. Zhang, and X. Zheng. 2019. A survey on security issues in services communication of microservices-enabled fog applications. Concurr. Comput. Pract. Exp. 31, 22 (2019). http://dblp.uni-trier.de/db/journals/concurrency/concurrency31.html#YuJZZ19.

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Index Terms

Fog Computing Platforms for Smart City Applications: A Survey
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
2. General and reference
  1. Document types
    1. Surveys and overviews

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cover image ACM Transactions on Internet Technology

ACM Transactions on Internet Technology Volume 22, Issue 4

November 2022

642 pages

ISSN:1533-5399

EISSN:1557-6051

DOI:10.1145/3561988

Editor:
Ling Liu
TU Wien, Austria

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Publication History

Published: 22 December 2022

Online AM: 03 February 2022

Accepted: 27 September 2021

Revised: 20 August 2021

Received: 30 March 2021

Published in TOIT Volume 22, Issue 4

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