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Addressing the Node Discovery Problem in Fog Computing

Authors Vasileios Karagiannis , Nitin Desai , Stefan Schulte , Sasikumar Punnekkat

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Author Details

Vasileios Karagiannis
  • Distributed Systems Group, TU Wien, Austria
Nitin Desai
  • Mälardalen University, Västerås, Sweden
Stefan Schulte
  • Distributed Systems Group, TU Wien, Austria
Sasikumar Punnekkat
  • Mälardalen University, Västerås, Sweden

Funding

The research leading to this paper has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 764785, FORA - Fog Computing for Robotics and Industrial Automation.

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Vasileios Karagiannis, Nitin Desai, Stefan Schulte, and Sasikumar Punnekkat. Addressing the Node Discovery Problem in Fog Computing. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 5:1-5:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/OASIcs.Fog-IoT.2020.5

Abstract

In recent years, the Internet of Things (IoT) has gained a lot of attention due to connecting various sensor devices with the cloud, in order to enable smart applications such as: smart traffic management, smart houses, and smart grids, among others. Due to the growing popularity of the IoT, the number of Internet-connected devices has increased significantly. As a result, these devices generate a huge amount of network traffic which may lead to bottlenecks, and eventually increase the communication latency with the cloud. To cope with such issues, a new computing paradigm has emerged, namely: fog computing. Fog computing enables computing that spans from the cloud to the edge of the network in order to distribute the computations of the IoT data, and to reduce the communication latency. However, fog computing is still in its infancy, and there are still related open problems. In this paper, we focus on the node discovery problem, i.e., how to add new compute nodes to a fog computing system. Moreover, we discuss how addressing this problem can have a positive impact on various aspects of fog computing, such as fault tolerance, resource heterogeneity, proximity awareness, and scalability. Finally, based on the experimental results that we produce by simulating various distributed compute nodes, we show how addressing the node discovery problem can improve the fault tolerance of a fog computing system.

Subject Classification

ACM Subject Classification
  • Computer systems organization → Cloud computing
  • Computer systems organization → Fault-tolerant network topologies
Keywords
  • Fog computing
  • Edge computing
  • Internet of Things
  • Node discovery
  • Fault tolerance

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References

  1. Hamid Reza Arkian, Abolfazl Diyanat, and Atefe Pourkhalili. Mist: Fog-based data analytics scheme with cost-efficient resource provisioning for iot crowdsensing applications. Journal of Network and Computer Applications, 82:152-165, 2017. Google Scholar
  2. Paolo Bellavista, Alessandro Zanni, and Michele Solimando. A migration-enhanced edge computing support for mobile devices in hostile environments. In International Wireless Communications and Mobile Computing Conference (IWCMC), pages 957-962. IEEE, 2017. Google Scholar
  3. Flavio Bonomi, Rodolfo Milito, Jiang Zhu, and Sateesh Addepalli. Fog computing and its role in the internet of things. In Workshop on Mobile Cloud Computing (MCC), pages 13-16. ACM, 2012. Google Scholar
  4. Rustem Dautov, Salvatore Distefano, Dario Bruneo, Francesco Longo, Giovanni Merlino, Antonio Puliafito, and Rajkumar Buyya. Metropolitan intelligent surveillance systems for urban areas by harnessing iot and edge computing paradigms. Software: Practice and Experience, 48(8):1475-1492, 2018. Google Scholar
  5. Marcos Dias de Assuncao, Alexandre da Silva Veith, and Rajkumar Buyya. Distributed data stream processing and edge computing: A survey on resource elasticity and future directions. Journal of Network and Computer Applications, 103:1-17, 2018. Google Scholar
  6. Shuiguang Deng, Zhengzhe Xiang, Jianwei Yin, Javid Taheri, and Albert Y Zomaya. Composition-driven iot service provisioning in distributed edges. IEEE Access, 6:54258-54269, 2018. Google Scholar
  7. Nitin Desai and Sasikumar Punnekkat. Safety of fog-based industrial automation systems. In Workshop on Fog Computing and the IoT (IoT-Fog), pages 6-10. ACM, 2019. Google Scholar
  8. Radu Dobrin, Nitin Desai, and Sasikumar Punnekkat. On fault-tolerant scheduling of time sensitive networks. In Workshop on Security and Dependability of Critical Embedded Real-Time Systems (CERTS). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2019. Google Scholar
  9. Pedro Garcia Lopez, Alberto Montresor, Dick Epema, Anwitaman Datta, Teruo Higashino, Adriana Iamnitchi, Marinho Barcellos, Pascal Felber, and Etienne Riviere. Edge-centric computing: Vision and challenges. ACM SIGCOMM Computer Communication Review, 45(5):37-42, 2015. Google Scholar
  10. Harshit Gupta, Amir Vahid Dastjerdi, Soumya K Ghosh, and Rajkumar Buyya. ifogsim: A toolkit for modeling and simulation of resource management techniques in the internet of things, edge and fog computing environments. Software: Practice and Experience, 47(9):1275-1296, 2017. Google Scholar
  11. Cheol-Ho Hong and Blesson Varghese. Resource management in fog/edge computing: a survey on architectures, infrastructure, and algorithms. ACM Computing Surveys (CSUR), 52(5):1-37, 2019. Google Scholar
  12. Vasileios Karagiannis. Building a Testbed for the Internet of Things. Alexander Technological Educational Institute of Thessaloniki, pages 1-92, 2014. Google Scholar
  13. Vasileios Karagiannis. Compute node communication in the fog: Survey and research challenges. In Workshop on Fog Computing and the IoT (IoT-Fog), pages 1-5. ACM, 2019. Google Scholar
  14. Vasileios Karagiannis, Periklis Chatzimisios, Francisco Vazquez-Gallego, and Jesus Alonso-Zarate. A survey on application layer protocols for the internet of things. ICAS Transaction on IoT and Cloud Computing, 3(1):11-17, 2015. Google Scholar
  15. Vasileios Karagiannis and Apostolos Papageorgiou. Network-integrated edge computing orchestrator for application placement. In International Conference on Network and Service Management (CNSM), pages 1-5. IEEE, 2017. Google Scholar
  16. Vasileios Karagiannis, Stefan Schulte, Joao Leitao, et al. Enabling fog computing using self-organizing compute nodes. In International Conference on Fog and Edge Computing (ICFEC), pages 1-10. IEEE, 2019. Google Scholar
  17. Vasileios Karagiannis, Alexandre Venito, Rodrigo Coelho, Michael Borkowski, and Gerhard Fohler. Edge computing with peer to peer interactions: Use cases and impact. In Workshop on Fog Computing and the IoT (IoT-Fog), pages 1-5. ACM, 2019. Google Scholar
  18. Roman Kolcun, David Boyle, and Julie A McCann. Optimal processing node discovery algorithm for distributed computing in iot. In 2015 5th International Conference on the Internet of Things (IOT), pages 72-79. IEEE, 2015. Google Scholar
  19. Yang Liu, Jonathan E Fieldsend, and Geyong Min. A framework of fog computing: Architecture, challenges, and optimization. IEEE Access, 5:25445-25454, 2017. Google Scholar
  20. Rongxing Lu, Kevin Heung, Arash Habibi Lashkari, and Ali Akbar Ghorbani. A lightweight privacy-preserving data aggregation scheme for fog computing-enhanced iot. IEEE Access, 5:3302-3312, 2017. Google Scholar
  21. Ivan Lujic, Vincenzo De Maio, and Ivona Brandic. Efficient edge storage management based on near real-time forecasts. In International Conference on Fog and Edge Computing (ICFEC), pages 21-30. IEEE, 2017. Google Scholar
  22. Carla Mouradian, Diala Naboulsi, Sami Yangui, Roch H. Glitho, Monique J. Morrow, and Paul A. Polakos. A comprehensive survey on fog computing: State-of-the-art and research challenges. IEEE Communications Surveys & Tutorials, 20(1):416-464, 2017. Google Scholar
  23. Ilir Murturi, Cosmin Avasalcai, Christos Tsigkanos, and Schahram Dustdar. Edge-to-edge resource discovery using metadata replication. In International Conference on Fog and Edge Computing (ICFEC), pages 1-6. IEEE, 2019. Google Scholar
  24. Carlo Puliafito, Enzo Mingozzi, Francesco Longo, Antonio Puliafito, and Omer Rana. Fog computing for the internet of things: A survey. ACM Transactions on Internet Technology, 19(2):18, 2019. Google Scholar
  25. Mahadev Satyanarayanan. The emergence of edge computing. Computer, 50(1):30-39, 2017. Google Scholar
  26. Vitor Barbosa Souza, Xavi Masip-Bruin, Eva Marín-Tordera, Sergi Sànchez-López, Jordi Garcia, Guang-Jie Ren, Admela Jukan, and Ana Juan Ferrer. Towards a proper service placement in combined fog-to-cloud (F2C) architectures. Future Generation Computer Systems, 87:1-15, 2018. Google Scholar
  27. Nitendra Tomar and Rakesh Matam. Optimal query-processing-node discovery in iot-fog computing environment. In 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pages 237-241. IEEE, 2018. Google Scholar
  28. Luis M Vaquero and Luis Rodero-Merino. Finding your way in the fog: Towards a comprehensive definition of fog computing. ACM SIGCOMM Computer Communication Review, 44(5):27-32, 2014. Google Scholar
  29. Blesson Varghese, Nan Wang, Sakil Barbhuiya, Peter Kilpatrick, and Dimitrios S Nikolopoulos. Challenges and opportunities in edge computing. In International Conference on Smart Cloud (SmartCloud), pages 20-26. IEEE, 2016. Google Scholar
  30. Prateeksha Varshney and Yogesh Simmhan. Demystifying fog computing: Characterizing architectures, applications and abstractions. In International Conference on Fog and Edge Computing (ICFEC), pages 115-124. IEEE, 2017. Google Scholar
  31. Riccardo Venanzi, Burak Kantarci, Luca Foschini, and Paolo Bellavista. MQTT-driven node discovery for integrated IoT-fog settings revisited: The impact of advertiser dynamicity. In Symposium on Service-Oriented System Engineering (SOSE), pages 31-39. IEEE, 2018. Google Scholar
  32. Zhenyu Wen, Renyu Yang, Peter Garraghan, Tao Lin, Jie Xu, and Michael Rovatsos. Fog orchestration for internet of things services. IEEE Internet Computing, 21(2):16-24, 2017. Google Scholar
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