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[Author] Tzung-Shi CHEN(2hit)

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  • An Improvement of Tree-Based Multicasting for Irregular Switch-Based Networks with Wormhole Routing

    Nen-Chung WANG  Tzung-Shi CHEN  Chih-Ping CHU  

     
    PAPER-Computer Systems

      Vol:
    E85-D No:5
      Page(s):
    812-823

    In this paper, we propose an efficient dual-tree-based multicasting scheme with three destination-switch partition strategies on irregular switch-based networks. The dual-tree-based routing scheme supports adaptive, distributed, and deadlock-free multicast on irregular networks with double channels. We first describe a dual-tree structure constructed from the irregular networks and prove that the multicasting based on such a structure is deadlock-free. Then, an efficient multicast routing algorithm with three destination-switch partition strategies: source-switch-based partition, destination-switch-based partition, and all-switches-based partition, is proposed. Finally, we perform simulations to evaluate our proposed algorithm under various impact parameters: system size, message length, and startup time. The experimental results show that the improved tree-based multicasting scheme outperforms the usual tree-based multicasting scheme. The dual-tree-based multicasting scheme with destination-switch-based partition is shown to be the best for all situations.

  • Mining Traversal Patterns on the Internet

    Tzung-Shi CHEN  

     
    PAPER-Databases

      Vol:
    E86-D No:12
      Page(s):
    2722-2730

    Mining traversal patterns on the Internet is one of critical issues for exploring the user access behaviors. In this paper, we propose a new data mining scheme for mining frequent trip traversal patterns on the Internet. First, we define a trip traversal as a historical contiguous sequence of web sites or web pages, which were surfed or visited on an information-providing system by one user. Next, we derive all of the maximal trip traversals by analyzing and filtering these collected trip traversals. For mining the large trip traversals from the maximal trip traversals, we present a data mining scheme integrated with the schemes presented in. Here, the extracted large trip traversals can be thought of as the realistic frequent browsed behaviors for most of users either on a web site or on an information-providing system, such as a proxy server. Finally, we implement and design a data mining system to explore the large trip traversal patterns in order to capture user access patterns to some proxy server.