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Distributed Nearest Neighbor Search (DNNS) locates service nodes that haveshortest interactive delay towards requesting hosts. DNNS provides an importantservice for large-scale latency sensitive networked applications, such as VoIP,online network games, or interactive network services on the cloud. Existingwork assumes the delay to be symmetric, which does not generalize toapplications that are sensitive to one-way delays, such as the multimedia videodelivery from the servers to the hosts. We propose a relaxed inframetric modelfor the network delay space that does not assume the triangle inequality anddelay symmetry to hold. We prove that the DNNS requests can be completedefficiently if the delay space exhibits modest inframetric dimensions, which wecan observe empirically. Finally, we propose a DNNS method named HybridNN(\textit{Hybrid} \textit{N}earest \textit{N}eighbor search) based on theinframetric model for fast and accurate DNNS. For DNNS requests, HybridNNchooses closest neighbors accurately via the inframetric modelling, andscalably by combining delay predictions with direct probes to a pruned set ofneighbors. Simulation results show that HybridNN locates nearly optimally thenearest neighbor. Experiments on PlanetLab show that HybridNN can provideaccurate nearest neighbors that are close to optimal with modest query overheadand maintenance traffic.

HybridNN: Supporting Network Location Service on Generalized Delay Metrics