An Implementation of a Framework for Integrating Churn Managements among Structured Overlay Networks

• Kimihiro Mizutani

  Graduate School of Information Science, Nara Institute of Science and Technology

• Satoshi Matsuura

  Graduate School of Information Science, Nara Institute of Science and Technology

• Shinichi Doi

  Graduate School of Information Science, Nara Institute of Science and Technology

• Kazutoshi Fujikawa

  Graduate School of Information Science, Nara Institute of Science and Technology

• Hideki Sunahara

  Graduate School of Information Science, Nara Institute of Science and Technology

抄録

In this paper, we propose a framework which can share states of the nodes and spread churn information to neighbor nodes among different overlay networks. Using our framework, we achieve maintaining each overlay network effectively and improve the reachability of messages under churn. We evaluate our framework with Chord, Kademlia, and Pastry. Our framework improves by approximately 30% in the detection speed of churn and decreases the stabilization messages by approximately 30-40%. We discuss the relationship between improvement of detection time and the reachability of messages.In this paper, we propose a framework which can share states of the nodes and spread churn information to neighbor nodes among different overlay networks. Using our framework, we achieve maintaining each overlay network effectively and improve the reachability of messages under churn. We evaluate our framework with Chord, Kademlia, and Pastry. Our framework improves by approximately 30% in the detection speed of churn and decreases the stabilization messages by approximately 30-40%. We discuss the relationship between improvement of detection time and the reachability of messages.

収録刊行物

• 情報処理学会研究報告. MBL, [モバイルコンピューティングとユビキタス通信研究会研究報告] = IPSJ SIG technical reports

  情報処理学会研究報告. MBL, [モバイルコンピューティングとユビキタス通信研究会研究報告] = IPSJ SIG technical reports 52 O1-O8, 2010-01-28

詳細情報

• CRID: 1572824502411633408
• NII論文ID: 110007993727
• NII書誌ID: AA11851388
• ISSN: 09196072
• 本文言語コード: en
• データソース種別:
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