### Abstract

Original language | English |
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Title of host publication | 4th International ICST Conference on Performance Evaluation Methodologies and Tools |

Number of pages | 10 |

DOIs | |

Publication status | Published - 2009 |

MoE publication type | A4 Article in a conference publication |

Event | 4th International ICST Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2009 - Pisa, Italy Duration: 20 Oct 2009 → 22 Oct 2009 |

### Conference

Conference | 4th International ICST Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2009 |
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Abbreviated title | VALUETOOLS 2009 |

Country | Italy |

City | Pisa |

Period | 20/10/09 → 22/10/09 |

### Fingerprint

### Keywords

- peer to peer network
- distributed hash tables
- power-law graphs

### Cite this

*4th International ICST Conference on Performance Evaluation Methodologies and Tools*https://doi.org/10.4108/ICST.VALUETOOLS2009.7724

}

*4th International ICST Conference on Performance Evaluation Methodologies and Tools.*4th International ICST Conference on Performance Evaluation Methodologies and Tools, VALUETOOLS 2009, Pisa, Italy, 20/10/09. https://doi.org/10.4108/ICST.VALUETOOLS2009.7724

**A power-law graph as a distributed hash table with quick search and small tables.** / Reittu, Hannu; Norros, Illkka.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - A power-law graph as a distributed hash table with quick search and small tables

AU - Reittu, Hannu

AU - Norros, Illkka

PY - 2009

Y1 - 2009

N2 - We analyze the possibility of using an 'Internet-like' power-law graph as a basis for peer-to-peer distributed hash table applications. Our work is based on previous studies of power-law random graph models that showed emergence of a spontaneous hierarchy of nodes based on their degrees, called the 'soft hierarchy'. The soft hierarchy indicates very short paths, leading to the top of the hierarchy, where the top consists of a clique of highest degree nodes. Such paths have lengths that scale as log log N, with number of nodes N. Further, such paths can be found by a heuristic rule: 'the next hop to highest degree neighbor'. We suggest that these circumstances could be used as a basis of an efficient distributed hash table. The idea is that the hash-entries, needed to locate content, are stored at the periphery of the hierarchy, consisting of large enough set of nodes to guarantee small tables. It is required that any node, say, i in the hierarchy is aware which nodes are below it in the hierarchy, provided it is not in the periphery. The node i places its 'down-hill' neighbors in the hash-ring with equal intervals between them. When node i gets a request to store or search a given hash-entry, it uses some locally defined function that places the hash value on this ring and forwards it to the down-hill neighbor closest to this value. Our main result is a probabilistic estimate of the number of hash-values stored in a periphery node. It appears to be sub log log N and super log log log N, with N -> infinity, and with probability tending to 1. Another contribution is a sketch of a novel algorithm that would create such topologies in a self-organizing manner.

AB - We analyze the possibility of using an 'Internet-like' power-law graph as a basis for peer-to-peer distributed hash table applications. Our work is based on previous studies of power-law random graph models that showed emergence of a spontaneous hierarchy of nodes based on their degrees, called the 'soft hierarchy'. The soft hierarchy indicates very short paths, leading to the top of the hierarchy, where the top consists of a clique of highest degree nodes. Such paths have lengths that scale as log log N, with number of nodes N. Further, such paths can be found by a heuristic rule: 'the next hop to highest degree neighbor'. We suggest that these circumstances could be used as a basis of an efficient distributed hash table. The idea is that the hash-entries, needed to locate content, are stored at the periphery of the hierarchy, consisting of large enough set of nodes to guarantee small tables. It is required that any node, say, i in the hierarchy is aware which nodes are below it in the hierarchy, provided it is not in the periphery. The node i places its 'down-hill' neighbors in the hash-ring with equal intervals between them. When node i gets a request to store or search a given hash-entry, it uses some locally defined function that places the hash value on this ring and forwards it to the down-hill neighbor closest to this value. Our main result is a probabilistic estimate of the number of hash-values stored in a periphery node. It appears to be sub log log N and super log log log N, with N -> infinity, and with probability tending to 1. Another contribution is a sketch of a novel algorithm that would create such topologies in a self-organizing manner.

KW - peer to peer network

KW - distributed hash tables

KW - power-law graphs

U2 - 10.4108/ICST.VALUETOOLS2009.7724

DO - 10.4108/ICST.VALUETOOLS2009.7724

M3 - Conference article in proceedings

BT - 4th International ICST Conference on Performance Evaluation Methodologies and Tools

ER -