Browsing by Author "Chao, H. Jonathan"

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Deep Packet Inspection: Algorithms, Hardware, and Applications
(2014-10-01)
Lin, Ying-Dar
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Lin, Po-Ching
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Prasanna, Viktor K.
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Chao, H. Jonathan
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Lockwood, John W.
Dynamic Switch Migration in Distributed Software-Defined Networks to Achieve Controller Load Balance
(2019-03-01)
Xu, Yang
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Cello, Marco
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Wang, I-Chih
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Walid, Anwar
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Wilfong, Gordon
Multiple distributed controllers have been used in software-defined networks (SDNs) to improve scalability and reliability, where each controller manages one static partition of the network. In this paper, we show that dynamic mapping between switches and controllers can improve efficiency in managing traffic load variations. In particular, we propose balanced controller (BalCon) and BalConPlus, two SDN switch migration schemes to achieve load balance among SDN controllers with small migration cost. BalCon is suitable for the scenarios where the network does not require a serial processing of switch requests. For other scenarios, BalConPlus is more suitable, as it is immune to the switch migration blackout and does not cause any service disruption. Simulations demonstrate that BalCon and BalConPlus significantly reduce the load imbalance among SDN controllers by migrating only a small number of switches with low computation overhead. We also build a prototype testbed based on the open-source SDN framework RYU to verify the practicality and effectiveness of BalCon and BalConPlus. Experiment confirms the results of the simulations. It also shows that BalConPlus is immune to switch migration blackout, an adverse effect in the baseline BalCon.
Improving Quality of Experience of Service-Chain Deployment for Multiple Users
(2018-01-01)
Wang, I-Chih
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Wen, Charles H-P
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Chao, H. Jonathan
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電機工程學系
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Department of Electrical and Computer Engineering
The fifth generation (5G) mobile communication network aims at providing high-rate, low-latency services. When a user subscribes a chain of service functions (a.k.a. service chain) from the telecom providers, a Service Level Agreement (SLA) is specified according to his requirement. Deploying service chains optimally has always been a big issue. Several previous works have presented various strategies of service-chain deployment for optimizing either latency or computational resources; however, over-optimization of latency or computational resource is not necessarily equivalent to improvement on quality of experience. Therefore, in this paper, we formally formulate this problem of optimizing quality of experience with the queuing theory and mixed-integer linear programming. In addition, we propose an efficient algorithm named "QoE-driven Service-Chain Deployment with Latency Prediction" for deploying a service chain for a user in practice. According to the experiments, our algorithm reduces >99% rejections and >99% waiting time, notably elevating the quality of experience for users.