High-Dimensional Distributed Indexing Based on Locality-Sensitive Hashing
Lin Chaohu · Jisuanji kexue yu tansuo · 2013
To overcome the problems of high memory consumption and computational overhead of high-dimensional indexing in content-based image search engine,the locality-sensitive hashing(LSH) index and Hadoop can be combined to improve the performance of the index architecture and computational model.According to the features of LSH index,the structure of LSH index is modified to a loosely coupled structure,and the index files are deployed in the distributed query nodes for high concurrency index-guery.The MapReduce distributed computational model is used in index constructing process to improve the efficiency of high-dimensional index creation.Besides,the distributed database is used to store large amounts of high-dimensional index data,which enhances the system's scalability.The experimental results show that the proposed methods are reasonable.