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학술대회 Centralized ARP Proxy Server over SDN Controller to Cut Down ARP Broadcast in Large-Scale Data Center Networks
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저자
조현정, 강세훈, 이영희
발행일
201501
출처
International Conference on Information Networking (ICOIN) 2015, pp.301-306
DOI
https://dx.doi.org/10.1109/ICOIN.2015.7057900
협약과제
14MI9200, (통합)스마트 네트워킹 핵심 기술 개발, 이병선
초록
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.
키워드
Address Resolution Protocol, Data Center Network, Software-Defined Networking
KSP 제안 키워드
Address Resolution Protocol(ARP), Broadcast messages, Centralized control, Challenging issues, Cloud service, Control characteristics, Controller architecture, Data Center Networks, Distributed cache, Dynamic allocation, Large-scale data