OASIcs.Fog-IoT.2020.9.pdf
- Filesize: 2.24 MB
- 8 pages
Document
Next-Generation SDN and Fog Computing: A New Paradigm for SDN-Based Edge Computing
Authors
Eder Ollora Zaballa 
,
David Franco ,
Marina Aguado ,
Michael Stübert Berger
-
Part of:
Volume:
2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)
Series: Open Access Series in Informatics (OASIcs)
Conference: Workshop on Fog Computing and the IoT (Fog-IoT) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2020-04-08
File
Document Identifiers
Author Details
- Department of Communications Engineering, University of the Basque Country UPV/EHU, Bilbao, Spain
- Department of Communications Engineering, University of the Basque Country UPV/EHU, San Bilbao, Spain
Cite As Get BibTex
Eder Ollora Zaballa, David Franco, Marina Aguado, and Michael Stübert Berger. Next-Generation SDN and Fog Computing: A New Paradigm for SDN-Based Edge Computing. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 9:1-9:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/OASIcs.Fog-IoT.2020.9
Abstract
In the last few years, we have been able to see how terms like Mobile Edge Computing, Cloudlets, and Fog computing have arisen as concepts that reach a level of popularity to express computing towards network Edge. Shifting some processing tasks from the Cloud to the Edge brings challenges to the table that might have been non-considered before in next-generation Software-Defined Networking (SDN). Efficient routing mechanisms, Edge Computing, and SDN applications are challenging to deploy as controllers are expected to have different distributions. In particular, with the advances of SDN and the P4 language, there are new opportunities and challenges that next-generation SDN has for Fog computing. The development of new pipelines along with the progress regarding control-to-data plane programming protocols can also promote data and control plane function offloading. We propose a new mechanism of deploying SDN control planes both locally and remotely to attend different challenges. We encourage researchers to develop new ways to functionally deploying Fog and Cloud control planes that let cross-layer planes interact by deploying specific control and data plane applications. With our proposal, the control and data plane distribution can provide a lower response time for locally deployed applications (local control plane). Besides, it can still be beneficial for a centralized and remotely placed control plane, for applications such as path computation within the same network and between separated networks (remote control plane).
Subject Classification
ACM Subject Classification
- Networks → Programmable networks
Keywords
- SDN
- P4
- P4Runtime
- control planes
- Fog
- Edge
Metrics
- Access Statistics
-
Total Accesses (updated on a weekly basis)
0PDF Downloads
References
- Ahmet Cihat Baktir, Atay Ozgovde, and Cem Ersoy. How can edge computing benefit from software-defined networking: A survey, use cases & future directions. IEEE Communications Surveys & Tutorials, PP:1-1, June 2017. URL: https://doi.org/10.1109/COMST.2017.2717482.
- Pat Bosshart, Dan Daly, Glen Gibb, Martin Izzard, Nick McKeown, Jennifer Rexford, Cole Schlesinger, Dan Talayco, Amin Vahdat, George Varghese, and David Walker. P4: Programming protocol-independent packet processors. SIGCOMM Comput. Commun. Rev., 44(3):87-95, July 2014. URL: https://doi.org/10.1145/2656877.2656890.
- P4 Language Consortium. P4. https://p4.org/. (Accessed on 02/27/2020). URL: https://p4.org/.
- The P4.org API Working Group. Specification documents for the P4Runtime control-plane API. https://github.com/p4lang/p4runtime, 2020. URL: https://github.com/p4lang/p4runtime.
- Xin Jin, Xiaozhou Li, Haoyu Zhang, Robert Soulé, Jeongkeun Lee, Nate Foster, Changhoon Kim, and Ion Stoica. Netcache: Balancing key-value stores with fast in-network caching. In Proceedings of the 26th Symposium on Operating Systems Principles, SOSP ’17, page 121–136, New York, NY, USA, 2017. Association for Computing Machinery. URL: https://doi.org/10.1145/3132747.3132764.
- A. A. Khan, M. Abolhasan, and W. Ni. 5g next generation vanets using sdn and fog computing framework. In 2018 15th IEEE Annual Consumer Communications Networking Conference (CCNC), pages 1-6, January 2018. URL: https://doi.org/10.1109/CCNC.2018.8319192.
- Nick McKeown, Tom Anderson, Hari Balakrishnan, Guru Parulkar, Larry Peterson, Jennifer Rexford, Scott Shenker, and Jonathan Turner. Openflow: Enabling innovation in campus networks. SIGCOMM Comput. Commun. Rev., 38(2):69–74, March 2008. URL: https://doi.org/10.1145/1355734.1355746.
- Jéferson Campos Nobre, Allan M. de Souza, Denis Rosário, Cristiano Both, Leandro A. Villas, Eduardo Cerqueira, Torsten Braun, and Mario Gerla. Vehicular software-defined networking and fog computing: Integration and design principles. Ad Hoc Networks, 82:172-181, 2019. URL: https://doi.org/10.1016/j.adhoc.2018.07.016.
- F. Paolucci, F. Civerchia, A. Sgambelluri, A. Giorgetti, F. Cugini, and P. Castoldi. P4 edge node enabling stateful traffic engineering and cyber security. IEEE/OSA Journal of Optical Communications and Networking, 11(1):A84-A95, January 2019. URL: https://doi.org/10.1364/JOCN.11.000A84.
- J. Pushpa and Pethuru Raj. Performance Enhancement of Fog Computing Using SDN and NFV Technologies, pages 107-130. Springer International Publishing, Cham, 2018. URL: https://doi.org/10.1007/978-3-319-94890-4_6.
-
Rob Sherwood, Glen Gibb, Kok-Kiong Yap, Guido Appenzeller, Martin Casado, Nick McKeown, and Guru Parulkar. Flowvisor: A network virtualization layer. OpenFlow Switch Consortium, Tech. Rep, 1:132, 2009.
- Shie-Yuan Wang, Chia-Ming Wu, Yi-Bing Lin, and Ching-Chun Huang. High-speed data-plane packet aggregation and disaggregation by p4 switches. Journal of Network and Computer Applications, 142:98-110, 2019. URL: https://doi.org/10.1016/j.jnca.2019.05.008.