Browsing by Author "Minh-Tuan Thai"

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A Joint Network and Server Load Balancing Algorithm for Chaining Virtualized Network Functions
(2016)
Minh-Tuan Thai
;
Lin, Ying-Dar
;
Lai, Yuan-Cheng
;
交大名義發表
;
National Chiao Tung University
Chaining virtualized network functions (VNF) is an effective practice to deploy network services in network operator\'s data centers. Two common concerns arise in such a deployment arc network load balancing and server load balancing. In this study, motivated by the argument that such two concerns should be jointly addressed for efficiently chaining VNFs in a data center environment, we propose a 2-phase algorithm, Nearest First and Local-Global Transformation (NF-LGT), which concurrently supports network and service load balancing. The algorithm firstly constructs service chains by a greedy strategy which both considers network latency and server latency. Then a searching technique is applied to improve the solutions. We have implemented the algorithm using Software-defined networking (SDN)/OpenFlow concept. The experimental results indicate that, compared with a sequential approach, NF-LGT improves the system bandwidth utilization up to 45%.
Joint server and network optimization toward load-balanced service chaining
(2018-07-10)
Minh-Tuan Thai
;
Lin, Ying-Dar
;
Lai, Yuan-Cheng
;
交大名義發表
;
資訊工程學系
Prior service chaining systems address server and network load balancing issues individually, which may not ensure efficient system performance. To this end, in this paper, we study the design, implementation, complexity analysis, and evaluation of Nearest First and Local-Global Transformation algorithm, which jointly supports server and network load balancing for chaining virtualized network functions (VNFs) in data center environment. The algorithm firstly constructs service chains by a greedy strategy, which both considers server and network latency. Then a searching technique, which replaces a selected VNF with another candidate and swaps the order of VNFs in service chains, is applied to improve the solutions. We have implemented the algorithm using Software-defined networking and OpenFlow concepts. The numerical results indicate that, compared with a sequential approach, Nearest First and Local-Global Transformation increases the system bandwidth utilization up to 45%. The results also show that it is worth applying the second phase of our algorithm since it considerably enhances the system performance by 20%.