Search and Replication in Unstructured Peer-to-Peer Networks

1
Search and Replication in Unstructured
Peer-to-Peer Networks

• Pei Cao, Christine Lv., Edith Cohen, Kai Li and
  Scott Shenker
• ICS 2002

2
Outline

• Brief survey of P2P architectures
• Evaluation Methodology
• Search Methods
• Replication
• Conclusions

3
Peer-to-Peer Networks

• Peers are connected by an overlay network.
• Users cooperate to share files (e.g., music,
  videos, etc.)
• Dynamic nodes join or leave frequently

4
P2P Network Architectures I

• Centralized
• Use of central directory server (CDS)
• Peers query to the CSD to find other peers that
  hold the desired object
• Pros very efficient
• Cons poorly scales
• single point of failure

5
P2P Network Architectures II

• Decentralized No central directory server
• But structured
• P2P network topology is tightly controlled
• Files are placed at specified locations
• Unstructured
• No control in Network topology or file placement

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P2P Network Architectures III

• Decentralized but Structured
• loose structured
• Placement of files is based on hints
• tight structure
• Precisely declare
• structure of P2P network and
• file placement
• Use of distributed hash table
• Pros Efficient satisfaction of queries
• Good scaling
• Cons No proof it works

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P2P Network Architectures IV

• Decentralized and Unstructured
• Placement of files not based on topology
  knowledge
• Finding files
• Node queries neighbors (usually using flooding)
• Pros extremely resilient to network changes
• Cons extremely unscalable
• generates large loads

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Evaluation Methodology I

• Terminology
• Network Topology
• instant graph formed by nodes in the network
• Query Distribution
• frequency of lookups to files
• Replication Distribution
• percentage of nodes that have a particular file

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Evaluation Methodology II

• Network Topologies
• Powel-Law Random Graph (PLRG)
• Max node degree 1746, median 1 average 4.46
• Normal Random Graph (Random)
• Average and median node degree is 4
• Gnutella graph (Gnutella)
• Oct 2000 snapshot
• Max degree 136, median 2, average 5.5
• Two-dimensional Grid
• 100x100 ? 10000 nodes

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Evaluation Methodology III

• Object query distribution qi
• Uniform
• Zipf-like
• Object replication density distribution ri
• Uniform
• Proportional ri ? qi
• Square-Root ri ? ? qi

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Evaluation Methodology IV

• Metrics
• User aspects
• Pr(success)
• hops
• Load aspects
• Average messages per node
• nodes visited
• Peak messages

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Limitation of Flooding I

• Gnutella uses TTL to check hops queries travel
• Problem
• Hard to choose TTL
• For objects that are widely present in the
  network, small TTLs suffice
• For objects that are rare in the network, large
  TTLs are necessary
• Number of query messages grow exponentially as
  TTL grows

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Limitation of Flooding II

• Node may receive the same messages more than once
• Need for duplication detection mechanisms
• Still duplication increases as TTL increases in
  flooding

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Limitation of Flooding Conclusion

• Flooding increases per-node overhead
• Need for more scalable search methods
• Expanding Ring
• Random Walks

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Expanding Ring

• Adaptively Adjust TTL
• Multiple floods start with TTL1 increment TTL
  by 2 each time until search succeeds

Still have duplicate messages
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Random Walk

• Simple random walk
• Takes too long to find anything
• Multiple-walker random walk
• K walkers after each walking T steps visits as
  many nodes as 1 walker walking KT steps
• More messages ? more overhead
• When to terminate the search
• TTL
• Checking check back with query originator once
  every C steps

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Search Traffic Comparison
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Search Delay Comparison
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Lessons Learned about Search Methods

• Key Cover the right number of nodes as quickly
  as possible and with as little overhead as
  possible
• Pay Attention to
• Adaptive termination
• Minimize message duplication
• Small expansion in each step

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Replication

• In unstructured P2P systems, search success is
  essentially about coverage visiting enough nodes
  to find the object gt replication density matters
• Goal minimize average search size (number of
  probes till query is satisfied)
• Theoretical Optimal copy everything everywhere
• Limited node storage

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Replication Strategies

• Uniform Replication
• pi 1/m
• Simple, resources are divided equally
• Proportional Replication
• pi qi
• Fair, resources per item proportional to demand
• Reflects current P2P practices

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Square-Root Replication

• pi is proportional to square-root(qi)
• Lies In-between Uniform and Proportional

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Achieving Square-Root Replication I

• Assuming that each query keeps track the number
  of probes needed
• Store an object at a number of nodes that is
  proportional to the number of probes
• Two implementations
• Path replication store the object along the path
  of a successful walk
• Random replication store the object randomly
  among nodes visited by the agents

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Achieving Square-Root Replication II
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Evaluation of Replication Methods I

• Metrics
• Overall message traffic
• Search delay
• Dynamic simulation
• Assume Zipf-like object query probability
• 5 query/sec Poisson arrival
• Results are during 5000sec-9000sec
• Search method 32-walkers random walk with state
  keeping and check every 4 steps

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Evaluation of Replication Methods II
Square-Root Replication reduces search traffic
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Evaluation of Replication Methods III
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Conclusions

• Multi-walker random walk scales much better than
  flooding
• Can find data more quickly
• Reduces the traffic overload
• Square-root replication distribution is desirable
• Minimizes search delay
• Minimizes the overall search traffic