https://home.wp.itec.aau.at/wp-content/uploads/sites/2/2018/09/Josef_Hammer.jpg 1525 1525 Rudolf Messner https://home.wp.itec.aau.at/wp-content/uploads/sites/2/2022/11/ITEC-Webheader-06-1030x94.png Rudolf Messner2023-06-26 12:26:572023-06-26 12:26:57Josef Hammer presented at CCGRID + ICFEC 2023
Josef Hammer presented the poster “Unique Prefix vs. Unique Mask for Minimizing SDN Flows with Transparent Edge Access” at the 23rd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2023) and the paper “Scalable Transparent Access to 5G Edge Services” at the 7th IEEE International Conference on Fog and Edge Computing (ICFEC 2023), both in Bangalore, India.
Authors: Josef Hammer and Hermann Hellwagner – Alpen-Adria-Universität Klagenfurt
Abstract: The challenging demands for the next generation of the Internet of Things have led to a massive increase in edge computing and network virtualization technologies. One significant technology is Multi-access Edge Computing (MEC), a central piece of 5G telecommunication systems. MEC provides a cloud computing platform at the edge of the radio access network and is particularly essential to satisfy the challenging low-latency demands of future applications. Our previous publications argue that edge computing should be transparent to clients. We introduced an efficient solution to implement such a transparent approach, leveraging Software-Defined Networking (SDN) and virtual IP+port addresses for registered edge services. Building on our already efficient approach, in this work, we propose significant improvements to scale our transparent solution to large-scale real-world access networks. First, by improving the modularity of our SDN controller design, we enable various options to distribute both the SDN controller’s load and the switches’ flows. Second, we introduce the Unique Mask, a solution superior to the Unique Prefix presented in our previous work that considerably reduces the number of required flows in the switches. Our evaluations show that both algorithms perform very well, with the Unique Mask capable of reducing the number of flows by up to 98 %.
For more information about the research, visit the website: https://edge.itec.aau.at/.