A flabellate overlay network for multi-attribute search

Peer-to-peer (P2P) technology provides a popular way of distributing resources, sharing, and locating in a large-scale distributed environment. However, most of the current existing P2P systems only support queries over a single resource attribute, such as file name. The current multiple resource attribute search methods often encounter high maintenance cost and lack of resilience to the highly dynamic environment of P2P networks. In this paper, we propose a Flabellate overlAy Network (FAN), a scalable and structured underlying P2P overlay supporting resource queries over multi-dimensional attributes. In FAN, the resources are mapped into a multi-dimensional Cartesian space based on the consistent hash values of the resource attributes. The mapping space is divided into non-overlapping and continuous subspaces based on the peer’s distance. This paper presents strategies formanaging the extended adjacent subspaces, which is crucial to networkmaintenance and resource search in FAN. The algorithms of a basic resource search and range query over FAN are also presented in this paper. To alleviate the load of the hot nodes, a virtual replica network (VRN) consisting of the nodes with the same replicates is proposed for replicating popular resources adaptively. The queries can be forwarded from the heavily loaded nodes to the lightly loaded ones through VRN. Theoretical analysis and experimental results show that FAN has a higher routing efficiency and lower network maintenance cost over the existing multi-attribute search methods. Also, VRN efficiently balances the network load and reduces the querying delay in FAN while invoking a relatively low overhead. © 2010 Elsevier Inc. All rights reserved.