Supporting Ranked Search in Parallel Search Cluster Networks

1
Supporting Ranked Search in Parallel Search
Cluster Networks

• Fang Xiong Qiong Luo Dyce Jing Zhao
• xfang, luo, zhaojing_at_cs.ust.hk
• Hong Kong University of Science and Technology

2
Introduction

• Environment P2P
• Unstructured, super-peer, Parallel Search Cluster
  Network (PSCN)
• Task search
• Data object ID
• filename
• Content ranked keyword search
• Previous work on ranked search in P2P
• PlanetP in the unstructured P2P network
• Shen et al. in the super-peer network

3
Both are unstructured P2P networks
FSL Forwarding Search Link NIL Non-forwarding
Index Link FIL Forwarding Index Link
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The Process of Ranked Search in a PSCN

• Indexing time
• Build the local indexes
• Transmit the local indexes across clusters
  through NILs
• Querying time
• Forward the query within a cluster through FSLs
• Collect the Local Aggregate Information (LAI),
  and merge into the Global Aggregate Information
  (GAI)
• The document-level index vs. the peer-level index
• In the case of using the document-level index,
  additional steps include calculating the Local
  Ranking (LR), and merging into the Global Ranking
  (GR)
• In the case of using the peer-level index,
  additional steps include calculating the Local
  Peer Ranking (LPR), merging into the Global Peer
  Ranking (GPR), calculating the Local Document
  Ranking (LDR) and merging into the Global
  Document Ranking (GDR)
• Merge the locally ranked query results into
  globally ranked ones and return all or top-K of
  them to the user

5

• Average processing time spent on each step, using
  the document-level index
• The majority of processing time is spent on
  local processing
• This suggests that it is necessary to distribute
  the search workload evenly over multiple peers
• Average processing time spent on each step, using
  the peer-level index

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• Average processing time in three overlays, using
  the document-level index
• The processing time in the unstructured network
  is much larger than in the other two
• The processing time in the super-peer network is
  about 30 larger than that in the PSCN
• The processing time is slightly more when using
  the document-level index than that using the
  peer-level index
• Average processing time in three overlays, using
  the peer-level index

7
2231less
4147 less
4.57.7 times higher
2225 lower
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Summary

• The majority of processing time is spent on local
  processing. Therefore, it is beneficial to
  distribute the search workload over peers
  otherwise, the bottleneck will be at the
  super-peers in a super-peer network or at the
  querying peer in an unstructured network.
• The processing time and the storage cost per peer
  in a PSCN is the lowest among the three overlays.
• The downside of a PSCN is the flooding
  communication within a cluster and the index
  replication cost across clusters. The super-peer
  network wins on the network bandwidth usage and
  the total storage cost.
• Compared with document-level indexes, peer-level
  indexes save 70 of the processing time, 30 of
  the network bandwidth usage and 30 of the
  storage space, with a slight decrease in
  precision.