2 research outputs found
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Όλ¬Έ (λ°μ¬)-- μμΈλνκ΅ λνμ : μ κΈ°Β·μ»΄ν¨ν°κ³΅νλΆ, 2013. 8. μμΉμ°.λ€νΈμν¬ κ°μνλ 물리μ λ€νΈμν¬μ 곡μ μμλ€μ 볡μ κ°μ κ°μ λ€νΈμν¬λ€μ λμ μΌλ‘ ν λΉν μ μκ² ν΄μ£Όλ κΈ°μ μ΄λ€. μμ ν λΉμ μ μ°μ±κ³Ό κ°μ λ€νΈμν¬λ€ μ¬μ΄μ λ
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μ²λ₯Ό μ€κ³νκΈ° μν μ μ©ν μ§μΉ¨μ μ 곡ν κ²μ΄λ€.Network virtualization is an emerging technology that enables the dynamic partitioning of a shared physical network infrastructure into multiple virtual networks. Because of its flexibility in resource allocation and independency among virtual networks, the network virtualization technology has not only been mainly deployed to build a testbed network, but also has come to be regarded as a cost-effective solution for diversifying the Internet. As a means of building the multi-layered Internet, network virtualization still faces a number of challenging issues that need to be addressed. This dissertation deals with several important research topics and provides effective solutions in network virtualization environment.
First, I focus on the optimal partitioning of finite substrate resources for satisfying the diverse QoS requirements of virtual networks. I formulate virtual network partitioning problem as a mixed integer multi-commodity flow problem. Then, to tackle the structural complexity of the problem, I propose a simple heuristic based on shortest path routing algorithm. By conducting large-scale network experiments, I verify the efficiency and scalability of the heuristic.
Next, I propose an economic model for tiered access service in virtual networks in order to remedy the deficiency of the existing tiered service schemes. I first derive a sufficient condition for stability of user subscription dynamics, and find the optimal pricing and capacity partitioning by addressing the revenue maximization problem of the tiered access service in a network virtualization environment. Numerical results show that the tiered service can be more profitable than the non-tiered service under proper pricing and capacity partitioning conditions.
Last, I develop a fast and effective failure recovery mechanism through inter-virtual network traffic switching in virtual networks. The proposed failure recovery mechanism neither has topological constraints for the existence of backup paths, nor requires the pre-computation of them, but nevertheless guarantees as fast recovery as the existing failure recovery methods.
This dissertation aims to address important issues in the virtual network-based Internet. I believe that the analysis and results in this dissertation will provide useful guidelines to improve the Internet.1 Introduction
1.1 Background and Motivation
1.2 Contributions and Outline of the Dissertation
2 Effective Partitioning for Service Level Differentiation in Virtual Networks
2.1 Introduction
2.2 Related Work
2.3 Model and Assumption
2.3.1 Business Model
2.3.2 Network Model
2.3.3 Traffic Demands
2.3.4 QoS Metric
2.4 Formulation
2.4.1 Objective
2.4.2 Substrate Partitioning Problem
2.4.3 Decomposition
2.5 Heuristic
2.6 Evaluation
2.6.1 Small Network Experiment
2.6.2 Large Network Experiment
2.7 Summary
3 Optimal Pricing and Capacity Partitioning for Tiered Access Service in Virtual Networks
3.1 Introduction
3.2 Motivating Example
3.3 A Tiered Service Model
3.3.1 Network Virtualization Environment
3.3.2 Effective Access Rate
3.3.3 Valuation Parameter and User Utility
3.3.4 User Subscription and the ISP Revenue
3.4 Non-tiered Service Analysis
3.4.1 User Subscription Dynamics
3.4.2 Optimal Pricing for Maximizing the ISP Revenue
3.5 Tiered Service Analysis
3.5.1 User Subscription Dynamics
3.5.2 Convergence of the User Subscription Dynamics
3.5.3 Optimal Pricing for Maximizing the ISP Revenue
3.6 Numerical Results
3.6.1 Non-tiered Service Example
3.6.2 Tiered Service Example
3.7 Related Work and Discussion
3.8 Summary
4 Inter-Virtual Network Traffic Switching for Fast Failure Recovery
4.1 Introduction
4.2 Background
4.3 Preliminaries
4.3.1 Virtual Network Model
4.3.2 Design Goals
4.3.3 Business Models and Switching Policy Agreement
4.3.4 Other Considerations
4.4 Failure Recovery based on Traffic Switching
4.4.1 Inter-VN Traffic Switching
4.4.2 Failure Recovery Process
4.5 Numerical Analysis
4.5.1 Delay
4.5.2 Congestion probability
4.6 Summary
5 Conclusion
A Proofs of Lemmas
A.1 Proof of Lemma 2
A.2 Proof of Lemma 3Docto