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Conference Paper Centralized ARP Proxy Server over SDN Controller to Cut Down ARP Broadcast in Large-Scale Data Center Networks
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Authors
Hyunjeong Cho, Saehoon Kang, Younghee Lee
Issue Date
2015-01
Citation
International Conference on Information Networking (ICOIN) 2015, pp.301-306
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICOIN.2015.7057900
Abstract
Today's cloud services are driving the wide-spread deployment of multi-tenant large-scale data centers. These data centers must have agility in order to provide diverse services to users in an efficient way, via dynamic allocation of the virtual machines (VMs) to the servers. However, as the complexity and the size of the data centers have increased, the tremendous address resolution traffic among the massive numbers of VMs has become a significant problem. Some approaches have tried to reduce the ARP broadcast traffic via distributed cache on the switches, or location specific addresses, but this has resulted in unavoidable challenging issues, such as the inconsistency problem between caches and/or address re-allocation to the VM and network reconfiguration whenever the VM migrates. In this paper, we propose a new centralized ARP proxy model that utilizes the Software Defined Networking (SDN) controller architecture, in which we can leverage the SDN's centralized control characteristics. In this approach, the SDN controller performs the ARP proxy function, and can significantly reduce the number of ARP broadcast messages over the networks. We prototyped the centralized ARP proxy module on an open-source SDN controller and performed experiments on the Mininet based virtual testbed to evaluate our approach. The experiments show that our approach efficiently processes address resolution while reducing ARP broadcast traffic by dozens of times to hundreds of times.
KSP Keywords
Address resolution, Broadcast messages, Centralized control, Challenging issues, Cloud service, Control characteristics, Controller architecture, Data Center Networks, Distributed cache, Dynamic allocation, Large-scale Data