Abstract

Unstructured overlays such as P2P networks and social networks stimulate many research areas. This kind of overlays is composed of a set of self-manageable entities which share objects between them in a spontaneous way. Getting a global knowledge such as popularity of shared objects or reputation of the entity is a challenging task because in such overlays, entities have only partial knowledge about the overlay state. In this paper, the authors focus on the file popularity measurement because this parameter can be efficiently used to improve object replication and object search performances. Some research works are proposed to measure this parameter, but these measurements are only based on local knowledge of peers. The authors propose Gpop, a global file popularity measurement for unstructured P2P networks which considers both local knowledge of the peer and knowledge of the other peers participating in the network to gain a global-like knowledge. Simulation results reinforce the authors' theoretical propositions and show that our measurement is closer to the real file popularity.

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