Concurrent linearizable nearest neighbour search in lockfree-kd-Tree

Paper in proceeding, 2018

The Nearest neighbour search (NNS) is a fundamental problem in many application domains dealing with multidimensional data. In a concurrent setting, where dynamic modi-fications are allowed, a linearizable implementation of NNS is highly desirable. This paper introduces the LockFree-kD-Tree (LFkD-Tree): A lock-free concurrent kD-Tree, which implements an abstract data type (ADT) that provides the operations Add, Remove, Contains, and NNS. Our implementation is linearizable. The operations in the LFkD-Tree use single-word read and compare-And-swap (CAS) atomic primitives, which are readily supported on available multi-core processors. We experimentally evaluate the LFkD-Tree using several benchmarks comprising real-world and synthetic datasets. The experiments show that the presented design is scalable and achieves signi cant speed-up compared to the implementations of an existing sequential kD-Tree and a recently proposed multidimensional indexing structure, PH-Tree. © 2018 Copyright held by the owner/author(s).