CISS: An efficient object clustering framework for DHT-based peer-to-peer applications

  • Authors:
  • Jinwon Lee;Hyonik Lee;Seungwoo Kang;Su Myeon Kim;Junehwa Song

  • Affiliations:
  • Korea Advanced Institute of Science and Technology (KAIST), Division of Computer Science, Department of EECS, Network Computing Laboratory, 373-1 Guseong-dong Yuseong-gu, Daejeon, Republic of Kore ...;Korea Advanced Institute of Science and Technology (KAIST), Division of Computer Science, Department of EECS, Network Computing Laboratory, 373-1 Guseong-dong Yuseong-gu, Daejeon, Republic of Kore ...;Korea Advanced Institute of Science and Technology (KAIST), Division of Computer Science, Department of EECS, Network Computing Laboratory, 373-1 Guseong-dong Yuseong-gu, Daejeon, Republic of Kore ...;Korea Advanced Institute of Science and Technology (KAIST), Division of Computer Science, Department of EECS, Network Computing Laboratory, 373-1 Guseong-dong Yuseong-gu, Daejeon, Republic of Kore ...;Korea Advanced Institute of Science and Technology (KAIST), Division of Computer Science, Department of EECS, Network Computing Laboratory, 373-1 Guseong-dong Yuseong-gu, Daejeon, Republic of Kore ...

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking
  • Year:
  • 2007

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Abstract

In most DHT-based peer-to-peer systems, objects are totally declustered since such systems use a hash function to distribute objects evenly. However, such an object de-clustering can result in significant inefficiencies in advanced access operations such as multi-dimensional range queries, continuous updates, etc, which are common in many emerging peer-to-peer applications. In this paper, we propose CISS (Cooperative Information Sharing System), a framework that supports efficient object clustering for DHT-based peer-to-peer applications. CISS uses a Locality Preserving Function (LPF) instead of a hash function, thereby achieving a high level of clustering without requiring any changes to existing DHT implementations. To maximize the benefit of object clustering, CISS provides efficient routing protocols for multi-dimensional range queries and continuous updates. Furthermore, our cluster-preserving load balancing schemes distribute loads without hotspots while preserving the object clustering property. We demonstrate the performance benefits of CISS through extensive simulation.