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Content addressable network(can)
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Content addressable network(can)


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  • 1. Amit Singh Dahal g5638545 Content Addressable Network(CAN) Structured P2P Network
  • 2. Outline  Introduction  Overview  Construction  Routing  Maintenance  Evaluation  Future Improvements
  • 3. Introduction  one of the original four distributed hash table proposals, introduced concurrently with Chords, Pastry, and Tapestry.  developed at UC Berkeley  CANs overlay routing easy to understand  scalable indexing system for large-scale decentralized storage applications  has a good performance
  • 4. Overview  distributed, decentralized P2P infrastructure system that maps keys onto values  keys hashed into d dimensional Cartesian space  Interface:  insert(key, value)  retrieve(key)  associate to each node and item a unique coordinate in an d-dimensional Cartesian space
  • 5. Overview  entire space is partitioned amongst all the nodes  every node “owns” a zone in the overall space  can store data at “points” in the space  can route from one “point” to another  point  node that owns the enclosing zone
  • 6. Overview y x State of the system at time t Node Resource Zone Fig:2 dimensional space with a key mapped to a point (x,y)
  • 7. Construction Bootstrap node new node
  • 8. Construction I Bootstrap node new node 1) Discover some node “I” already in CAN
  • 9. Construction 2) Pick random point in space I (x,y) new node
  • 10. Construction (x,y) 3) I routes to (x,y), discovers node J I J new node
  • 11. Construction newJ 4) split J’s zone in half… new owns one half
  • 12. Routing  data stored in the CAN is addressed by name (i.e. key), not location (i.e. IP address)  have some routing mechanism  A node only maintains state for its immediate neighboring nodes
  • 13. Routing y Node M(x,y) N(x,y)  d-dimensional space with n zones where d=2 and n=8 2 zones are neighbor if d-1 dim overlap Algorithm: Choose the neighbor nearest to the destination M(x,y) Query/ Resource key
  • 14. Maintenance  Use zone takeover in case of failure or leaving of a node  Send your neighbor table update to neighbors to inform that you are alive at discrete time interval t  If your neighbor does not send alive in time t, takeover its zone  Zone reassignment is needed
  • 15. Evaluation  Scalability -For a uniformly partitioned space with n nodes and d dimensions: * per node, number of neighbors is 2d *average routing path is (d*n1/d)/3 hops (due to Manhattan distance routing, expected hops in each dimension is dimension length * 1/3) *Can scale the network without increasing per node state  Robustness -no single point of failure
  • 16. Future Improvements  Multi-dimension -increase in dimension reduces path length  Caching and replication techniques for better performance  Overloading the zone -increases availability, reduces path length, reduces per hop latency  Uniform partitioning -compare the volume of the zone with its neighbors -partition the zone having largest volume
  • 17. THANK YOU!!! 