Browsing by Author "Kuo, Kuan-Tsen"

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(DENDIST)-E-2-FM: Flow Migration in Routing of OpenFlow-based Cloud Networks
(2013-01-01)
Lin, Wei-Chu
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Liu, Gen-Hen
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Kuo, Kuan-Tsen
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Wen, Charles H. -P.
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電機資訊學士班
A prior layer-2 routing algorithm-(DENDIST)-E-2 demonstrates advantages in throughput improvement, reroute period and failure recovery. Moreover, with the invention of software-defined networking (SDN), a revolutionary networking concept, dynamic routing protocols can embrace more flexible policy on per-flow basis. However, due to runtime complexity of dynamic routing, many issues on the practicality emerge and await to be resolved. Therefore, in this paper, we first apply (DENDIST)-E-2 to a SDN architecture and compare performances between dynamic-routing and flow-control mechanisms in a OpenFlow-based cloud network. Then, the flow-migration (FM) scheme, showing a better flow-control management, can be combined with (DENDIST)-E-2, and evolved into (DENDIST)-E-2-FM. At last, experimental results demonstrate that (DENDIST)-E-2-FM enables better feasibility in real-world applications, throughput improvement, sensitivity to reroute period and reduction in failure recovery time.
Flow-and-VM Migration for Optmizing Throughput and Energy in SDN-based Cloud Datacenter
(2013-01-01)
Lin, Wei-Chu
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Liao, Chien-Hui
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Kuo, Kuan-Tsen
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Wen, Charles H-P.
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電機資訊學士班
Minimizing energy consumption and improving performance in datacenters are critical to cost-saving for cloud operators, but traditionally, these two optimization objectives are treated separately. Therefore, this paper presents an unified solution combining two strategies, flow migration and VM migration, to maximize throughput and minimize energy, simultaneously. Traffic-aware flow migration (FM) is first incorporated in dynamic reroute (DENDIST), evolving into DENDIST-FM, in a software-defined network (SDN) for improving throughput and avoiding congestion. Second, given energy and topology information, VM migration (ETA-VMM) can help reduce traffic loads and meanwhile save energy. Our experimental result indicates that compared to previous works, the proposed method can improve throughput by 42.5% on average with only 2.2% energy overhead. Accordingly, the unified flow-and-VM migration solution has been proven effective for optimizing throughput and energy in SDN-based cloud datacenters.
SWF: Segmented Wildcard Forwarding for Flow Migration in OpenFlow Datacenter Networks
(2015)
Kuo, Kuan-Tsen
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Wen, Charles H. -P.
;
Suo, Cheng
;
Tsai, I-Chen
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電機學院
Networking and performance become major issues in cloud computing. Software Defined Networking (SDN) enables flow -level management and makes routing more effective and flexible for datacenter networks (DCNs). A prior dynamic routing algorithm named Flow Migration shows good results in improving throughput and avoiding congestion through simulation. However, as Flow Migration is applied to a SDN-based DCN, tremendous overhead occurs in modifying flow tables of switches. Therefore, a novel Segmented Wildcard Forwarding (SWF) scheme is proposed to facilitate Flow Migration. SWF leverages the symmetry of a Portland topology and applies wildcard matching for balancing network loading and lowering table -modification cost for flows. Experimental results show that on a Portland 4-8-8 datacenter network, the proposed SWF scheme achieves higher throughput over than the traditional SPB does, and even reduces 70% modification cost used by the original implementation of Flow Migration. As a result, Segmented Wildcard Forwarding (SWF) is proven a mechanism that practically realizes dynamic routing of SDN but also improves network performance as well as cost for flow migration, simultaneously.