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SLA-aware load balancing for cloud datacenters. 指導教授:王國禎 學生:黎中誠 國立交通大學資訊工程系 行動計算與寬頻網路實驗室. Problem Definition. Tree of Load Balancing. Related work. Proposed Architecture. Related work. Proposed Architecture. Delta Learning Rule. Load balancing method. Capacity index Weight.
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SLA-aware load balancing for cloud datacenters 指導教授:王國禎 學生:黎中誠 國立交通大學資訊工程系 行動計算與寬頻網路實驗室
Load balancing method Capacity index Weight
Artificial neural network • Supervised learning • Supervised learning is the machine learning task of inferring a function from supervised (labeled) training data • Unsupervised learning • Unsupervised learning also encompasses many other techniques that seek to summarize and explain key features of the data
Delta Learning Rule r = (0.8.di-oi)f’(neti) Δωi= η.r.x
Conclusions We propose architecture based on distributed load balancer which is different from general centralized balancer Combination of system performance monitoring and neural network This system can avoid SLA violations
References [1] V. Nae, A. Iosup, and R. Prodan, "A Scheduling Strategy on Load Balancing of Virtual Machine Resources in Cloud Computing Environment“, in Parallel and Distributed Systems, IEEE Transactions on , 2010, pp. 380 - 395. [2] R. Suselbeck, G. Schiele, and C. Becker, "Towards a Load Balancing in a Three-level Cloud Computing Network," in Network and Systems Support for Games (NetGames), 2009, pp. 1 - 2. [3] Shu-Ching Wang, Kuo-Qin Yan, Wen-Pin Liao, and Shun-Sheng Wang, "A Load Balancing Mechanism Based on Ant Colony and Complex Network Theory in Open Cloud Computing Federation," in IEEE ICCSIT, 2010, pp. 108 - 113. [4] RajkumarRajavel, "A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing," in IEEE INCOCCI, Erode, 2010, pp. 419 - 424.