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- Xiang Cheng
- Beijing University of Posts and Telecommunications, Beijing, China
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- Sen Su
- Beijing University of Posts and Telecommunications, Beijing, China
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- Zhongbao Zhang
- Beijing University of Posts and Telecommunications, Beijing, China
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- Hanchi Wang
- Beijing University of Posts and Telecommunications, Beijing, China
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- Fangchun Yang
- Beijing University of Posts and Telecommunications, Beijing, China
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- Yan Luo
- University of Massachusetts Lowell, Lowell, USA
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- Jie Wang
- University of Massachusetts Lowell, Lowell, USA
説明
<jats:p>Virtualizing and sharing networked resources have become a growing trend that reshapes the computing and networking architectures. Embedding multiple virtual networks (VNs) on a shared substrate is a challenging problem on cloud computing platforms and large-scale sliceable network testbeds. In this paper we apply the Markov Random Walk (RW) model to rank a network node based on its resource and topological attributes. This novel topology-aware node ranking measure reflects the relative importance of the node. Using node ranking we devise two VN embedding algorithms. The first algorithm maps virtual nodes to substrate nodes according to their ranks, then embeds the virtual links between the mapped nodes by finding shortest paths with unsplittable paths and solving the multi-commodity flow problem with splittable paths. The second algorithm is a backtracking VN embedding algorithm based on breadth-first search, which embeds the virtual nodes and links during the same stage using node ranks. Extensive simulation experiments show that the topology-aware node rank is a better resource measure and the proposed RW-based algorithms increase the long-term average revenue and acceptance ratio compared to the existing embedding algorithms.</jats:p>
収録刊行物
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- ACM SIGCOMM Computer Communication Review
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ACM SIGCOMM Computer Communication Review 41 (2), 38-47, 2011-04-15
Association for Computing Machinery (ACM)