Stochastic programming methods applied to network optimization |
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| Affiliation: | 1. State Key Laboratory of Software Engineering, Computer School, Wuhan University, Wuhan, China;2. Department of Computer Science, Western Michigan University, MI, USA;3. School of Information Technology, Deakin University, Melbourne, Australia;1. School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China;2. Key Laboratory of Image Processing and Intelligent Control, Ministry of Education, Huazhong University of Science and Technology, Wuhan 430074, China;3. Department of Mathematics, Texas A&M University at Qatar, Doha 23874, Qatar;4. School of electrical engineering and telecommunications, University of New South Wales, Sydney, NSW 2052, Australia;5. Information engineering school of Nanchang university, Nanchang 2052 China |
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| Abstract: | As communication technologies evolve, it becomes necessary to incorporate the stochastic effect of traffic flows into network models. This paper introduces the stochastic programming (SP) methodology for characterizing traffic. Two SP approaches, here-and-now (HN) and scenario tracking (ST), are described through case studies for a prototype network. A numerical optimization procedure is used to perform the simulation. It is clearly demonstrated that when the probability distributions can be estimated analytically, the HN approach can be attractive. Otherwise, the ST approach may be more appropriate. |
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