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Algorithms and Stability Analysis for Content Distribution over Multiple Multicast Trees
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- Authors
- Xiaoying Zheng, Chunglae Cho, Ye Xia
- Issue Date
- 2015-05
- Citation
- IEEE Transactions on Parallel and Distributed Systems, v.26, no.5, pp.1217-1227
- ISSN
- 1045-9219
- Publisher
- IEEE
- Language
- English
- Type
- Journal Article
- Abstract
- The paper investigates theoretical issues in applying the universal swarming technique to efficient content distribution. In a swarming session, a file is distributed to all the receivers by having all the nodes in the session exchange file chunks. By universal swarming, not only all the nodes in the session, but also some nodes outside the session may participate in the chunk exchange to improve the distribution performance. We present a universal swarming model where the chunks are distributed along different Steiner trees rooted at the source and covering all the receivers. We assume chunks arrive dynamically at the sources and focus on finding stable universal swarming algorithms. To achieve the throughput region, universal swarming usually involves a tree-selection subproblem of finding a min-cost Steiner tree, which is NP-hard. We propose a universal swarming scheme that employs an approximate tree-selection algorithm. We show that it achieves network stability for a reduced throughput region, where the reduction ratio is no more than the approximation ratio of the tree-selection algorithm. We propose a second universal swarming scheme that employs a randomized tree-selection algorithm. It achieves the throughput region, but with a weaker stability result. Comprehensive simulation results support the stability analysis of the algorithms. The proposed schemes and their variants are expected to be useful for infrastructure-based content distribution networks with massive content and relatively stable network environment.
- KSP Keywords
- Approximation ratio, Content Distribution Network, Distribution network(DN), Distribution performance, File chunks, Multicast tree, Network Environment, Randomized Tree, Stability analysis, Steiner trees, multiple multicast