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A Scalable Content- Addressable Network Sections: 3.1 and 3.2 Καραγιάννης Αναστάσιος Α.Μ. 74.

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Presentation on theme: "A Scalable Content- Addressable Network Sections: 3.1 and 3.2 Καραγιάννης Αναστάσιος Α.Μ. 74."— Presentation transcript:

1 A Scalable Content- Addressable Network Sections: 3.1 and 3.2 Καραγιάννης Αναστάσιος Α.Μ. 74

2 Multi-dimensioned Coordinate Spaces  The design of the algorithm does not restrict the dimensionality of the coordinate space  While increasing the dimensions of the CAN coordinate spaces, the routing path is reduced  There is a small increase of the routing table

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4 Multi-dimensioned Coordinate Spaces  For a system with n nodes and d dimension, the path length scales as O(d(n 1/d ))  The increase of the dimension implies the increase of neighbors of each node  This improves the fault tolerance Every node has many potential next hop nodes In case of a crash, which messages can be routed among the neighbors

5 Realities: Multiple Coordinate Spaces  We can maintain multiple independent coordinate spaces  Every node is assigned in a different zone in each coordinate space  Each coordinate space is called a “reality”  In a CAN with r realities, a node is assigned r coordinate zones, one on every reality  Every node holds r independent sets of neighbor sets

6 Realities: Multiple Coordinate Spaces  A pointer to a file is stored at the coordinate location (x, y, z)  With 4 independent realities this pointer is stored at 4 different nodes  This file is unavailable only when all four nodes are unavailable  Routing fault tolerance is also improved  In the case of a routing breakdown on one reality, messages can continue to be routed using the remaining realities

7 Realities: Multiple Coordinate Spaces  The contents of the hash table are replicated on each reality This improves data availability  Routing to location (x, y, z) is equal to reaching (x, y, z) on any reality  An individual node can reach distant portions of the coordinate space with a single hop This reduces greatly the average path length

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9 Mult. Dimensions Vs. Mult. Realities  Increasing either the number of dimensions or the number of realities results in: Shorter path length Higher per-node neighbor state Increase of maintenance traffic  We will now compare these two improvements

10 Mult. Dimensions Vs. Mult. Realities  Multiple dimensions comparing to multiple realities give shorter path length  Multiple realities though, give bigger data availability and better fault tolerance  If the size of per-node neighbor state is not important and the primary purpose is improving routing efficiency, multiple dimensions are more suitable

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12 The End


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