Similarity Discovery in Structured P2P Overlays

Peer-to-peer (P2P) overlays are appealing, since they can aggregate resources of end systems without relying on sophisticated infrastructures. Services can thus be rapidly deployed over such overlays. Primitive P2P overlays only support searches with single keywords. For queries with multiple keywords, presently only unstructured P2P systems can support by extensively employing message flooding. In this study, we propose a similarity information retrieval system called Meteorograph for structured P2P overlays without relying on message flooding. Meteorograph is faultresilient, scalable, responsive and self-administrative, which is particularly suitable for an environment with an explosion of information and a large number of dynamic entities. An information item stored in Meteorograph is represented as a vector. A small angle between two vectors means that the corresponding items are characterized by some identical keywords. Meteorograph further stores similar items at nearby locations in the P2P overlay. To retrieve similar items, only nodes in nearby locations are located and consulted. Meteorograph is evaluated with simulation. The results show that Meteorograph can effectively distribute loads to the nodes. Discovering a single item and a set (in size k) of similar items takes ( ) N O log and ( ) N O c k log ) ( ⋅ messages and hops respectively, where N is the number of nodes in the overlay and c is the storage capacity of a node.