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.
- [1] . 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.Google Scholar
Cross Ref
- [2] . 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.Google Scholar
Cross Ref
- [3] . 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. Google Scholar
Digital Library
- [4] . 2019. Fog computing applications: Taxonomy and requirements. CoRR abs/1907.11621 (2019).Google Scholar
- [5] . 2020. COMITMENT: A fog computing trust management approach. J. Parallel Distributed Comput. 137 (2020), 1–16.Google Scholar
Digital Library
- [6] . 2018. Internet of things-enabled smart cities: State-of-the-art and future trends. Measurement 129 (2018). Google Scholar
Cross Ref
- [7] . 2019. Exploring the effectiveness of service decomposition in fog computing architecture for the internet of things. CoRR abs/1904.00381 (2019).Google Scholar
- [8] . 2015. Modeling and analyzing MAPE-K feedback loops for self-adaptation. In [email protected], and (Eds.). IEEE Computer Society, 13–23. Google Scholar
- [9] . 2018. Fog computing and the internet of things: A review. Big Data and Cognitive Computing 2, 2 (2018). Google Scholar
Cross Ref
- [10] . 2010. The internet of things: A survey. Computer Networks 54, 15 (2010), 2787–2805. Google Scholar
Digital Library
- [11] . 2020. A survey on blockchain-fog integration approaches. IEEE Access 8 (2020), 102657–102668.Google Scholar
Cross Ref
- [12] . 2020. Fog computing and blockchain for massive IoT deployment. In 2020 9th Mediterranean Conf. on Embedded Computing (MECO). 1–4. Google Scholar
Cross Ref
- [13] . 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.Google Scholar
Cross Ref
- [14] . 2011. Gateway architectures for service oriented application-level gateways. IEEE Trans. on Consumer Electronics 57, 2 (2011), 453–461. Google Scholar
Cross Ref
- [15] and (Eds.). 2014. SWEBOK: Guide to the Software Engineering Body of Knowledge (3.0 ed.). IEEE Computer Society, Los Alamitos. Google Scholar
- [16] . 2018. Deploying fog applications: How much does it cost, by the way?. In CLOSER.Google Scholar
- [17] . 2019. Security implications of fog computing on the internet of things. In 2019 IEEE International Conference on Consumer Electronics (ICCE). 1–6. Google Scholar
Cross Ref
- [18] . 2016. Fog and IoT: An overview of research opportunities. IEEE Internet of Things Journal 3, 6 (2016), 854–864.Google Scholar
Cross Ref
- [19] . 2016. White Paper of Edge Computing Consortium.Google Scholar
- [20] . 2018. IEEE standard for adoption of OpenFog reference architecture for fog computing. IEEE Std 1934-2018 (2018), 1–176.Google Scholar
- [21] . 2016. Fog computing: Principles, architectures, and applications. CoRR abs/1601.02752 (2016).Google Scholar
- [22] . 2010. Smarter cities for smarter growth: How cities can optimize their systems for the talent-based economy. SSRN (
5 2010).Google Scholar - [23] . 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.Google Scholar
Digital Library
- [24] . 2017. Smart cities: A survey on data management, security, and enabling technologies. IEEE Communications Surveys Tutorials 19, 4 (2017), 2456–2501. Google Scholar
Cross Ref
- [25] . 2020. Resource management approaches in fog computing: A comprehensive review. J. Grid Comput. 18, 1 (2020), 1–42. Google Scholar
Cross Ref
- [26] . 2019. CityFlow: Exploiting edge computing for large scale smart city applications. In BigComp. IEEE, 1–4. Google Scholar
- [27] . 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.Google Scholar
Cross Ref
- [28] . 2021. Task scheduling in cloud-fog computing systems. Peer-to-Peer Networking and Applications 14 (
03 2021).Google ScholarCross Ref
- [29] . 2020. Fog computing: A comprehensive architectural survey. IEEE Access 8 (2020), 69105–69133.Google Scholar
Cross Ref
- [30] . 2018. Serverless computing: One step forward, two steps back. CoRR abs/1812.03651 (2018).Google Scholar
- [31] . 2018. Resource management in fog/edge computing: A survey. CoRR abs/1810.00305 (2018).Google Scholar
- [32] . 2018. Fog Computing Conceptual Model.
Technical Report . NIST.Google ScholarCross Ref
- [33] . 2020. Fog computing applications in smart cities: A systematic survey. Wireless Networks 26, 2 (2020), 1433–1457.Google Scholar
Digital Library
- [34] . 2020. Scalable IoT platform for heterogeneous devices in smart environments. IEEE Access 8 (2020), 211973–211985.Google Scholar
Cross Ref
- [35] . 2020. FogTestBed: A generic architecture for testbed for fog-based systems. In 2020 SoutheastCon. 1–7.Google Scholar
- [36] . 2020. Security issues in fog environment: A systematic literature review. International Journal of Wireless Information Networks 27 (
9 2020). Google ScholarCross Ref
- [37] . 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.Google Scholar
- [38] . 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.Google Scholar
Cross Ref
- [39] . 2019. Edge computing: A survey. Future Generation Computer Systems 97 (2019), 219–235. Google Scholar
Digital Library
- [40] . 2016. Chapter 1 - Internet of things: An overview. In Internet of Things, and (Eds.). Morgan Kaufmann, 3–27. Google Scholar
Cross Ref
- [41] . 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. Google Scholar
Cross Ref
- [42] . 2004. Evidence-based software engineering. In Proc. 26th Int. Conf. on Software Engineering. 273–281.Google Scholar
Cross Ref
- [43] . 2021. Blockchain-based security services for fog computing. Advances in Information Security (2021), 271–290. Google Scholar
Cross Ref
- [44] . 2013. Edge computing. https://moam.info/edge-computing-pacific-northwest-national-laboratory_59d648481723dd08e35b7b77.html.Google Scholar
- [45] . 2020. Deep reinforcement learning for intelligent migration of fog services in smart cities. In ICA3PP (2)(
Lecture Notes in Computer Science , Vol. 12453), (Ed.). Springer, 230–244. Google Scholar - [46] . 2019. A survey on fog programming: Concepts, state-of-the-art, and research challenges. In [email protected]. ACM, 1–6. http://dblp.uni-trier.de/db/conf/middleware/dfsd2019.html#LanTEH19.Google Scholar
- [47] . 2018. Smart cities with big data: Reference models, challenges, and considerations. Cities 82 (2018), 86–99. Google Scholar
Cross Ref
- [48] . 2018. Security and privacy challenges for internet-of-things and fog computing. Wireless Communications and Mobile Computing 2018 (
09 2018), 1–3. Google ScholarCross Ref
- [49] . 2016. A performance comparison of open-source stream processing platforms. In GLOBECOM. IEEE, 1–6. Google Scholar
- [50] . 2018. Fog Computing: A Taxonomy, Survey and Future Directions. Springer Singapore, 103–130. Google Scholar
- [51] . 2019. DeFog: Fog computing benchmarks. Proc. of the 4th ACM/IEEE Symposium on Edge Computing (2019).Google Scholar
Digital Library
- [52] . 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.Google Scholar
Digital Library
- [53] . 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.Google Scholar
Digital Library
- [54] . 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.Google Scholar
- [55] . 2017. A comprehensive survey on fog computing: State-of-the-art and research challenges. CoRR abs/1710.11001 (2017). Google Scholar
Cross Ref
- [56] . 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.Google Scholar
- [57] . 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.Google Scholar
Cross Ref
- [58] . 2014. Reference Architectures. John Wiley & Sons, Ltd, Chapter 2, 55–82. Google Scholar
- [59] . 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.Google Scholar
- [60] . 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.Google Scholar
Cross Ref
- [61] . 2017. Fog computing for sustainable smart cities: A survey. CoRR (2017).Google Scholar
- [62] . 2020. A comparative analysis of simulators for the cloud to fog continuum. Simulation Modelling Practice and Theory 101 (2020), 102029. Google Scholar
Cross Ref
- [63] . 2019. Edge-cloud orchestration: Strategies for service placement and enactment. In IC2E. IEEE, 67–75. Google Scholar
- [64] . 2018. Survey on multi-access edge computing for internet of things realization. IEEE Communications Surveys Tutorials 20, 4 (2018), 2961–2991. Google Scholar
Cross Ref
- [65] . 2017. Fog computing for the internet of mobile things: Issues and challenges. In SMARTCOMP. IEEE Computer Society, 1–6. Google Scholar
- [66] . 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.Google Scholar
Digital Library
- [67] . 2019. Challenges in designing edge-based middlewares for the internet of things: A survey. CoRR abs/1912.06567 (2019).Google Scholar
- [68] . 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.Google Scholar
- [69] . 2018. IoT survey: An SDN and fog computing perspective. Computer Networks 143 (2018), 221–246. Google Scholar
Digital Library
- [70] . 2016. Software platforms for smart cities: Concepts, requirements, challenges, and a unified reference architecture. CoRR abs/1609.08089 (2016). Google Scholar
Digital Library
- [71] . 2018. Resource and service management for fog infrastructure as a service. In 2018 IEEE Int. Conf. on Smart Cloud (SmartCloud). 64–69.Google Scholar
- [72] . 1996. Software Architecture: Perspectives on an Emerging Discipline. Prentice-Hall, Englewood Cliffs, NJ, USA.Google Scholar
Digital Library
- [73] . 2021. Fog Computing Platforms for Smart City Applications - A Survey. (2021).
arXiv (to be published). Google Scholar - [74] . 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.Google Scholar
Cross Ref
- [75] . 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.Google Scholar
Cross Ref
- [76] . 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. Google Scholar - [77] . 2018. A taxonomy for management and optimization of multiple resources in edge computing. Wirel. Commun. Mob. Comput. 2018 (2018), 7476201:1–7476201:23.Google Scholar
Digital Library
- [78] . 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).Google Scholar
- [79] . 2017. A new era for cities with fog computing. IEEE Internet Computing 21, 2 (2017), 54–67. Google Scholar
Cross Ref
- [80] . 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.Google Scholar
Cross Ref
Index Terms
Fog Computing Platforms for Smart City Applications: A Survey
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