Paper Info
Title
OPRCP: approximate nearest neighbor binary search algorithm for hybrid data over WMSN blockchain
Abstract
In order to prevent sensitive data tampering in the application of security monitoring, intelligent traffic, and other sensitive Internet of Things, the research on WMSN (wireless multimedia sensor networks) application system based on blockchain and IPFS (InterPlanetary File System) is of great significance. However, WMSN data are characterized by high dimensionality, large scale, and multiple types, so it is challenging to search WMSN data efficiently over blockchain system. This paper proposed a novel One Permutation with Rotation and cross-polytope locality-sensitive hashing (OPRCP) method of approximate nearest neighbor binary query for querying binary hybrid data in the form of WMSN multimedia data (containing two hybrid types of data, such as image-text and image-audio). Firstly, a binary hybrid data index was built with the method of locality-sensitive hashing (LSH) to retain content similarity among original data objects for performing accurate queries. Secondly, the approximate nearest neighbor search strategy was used in place of the nearest neighbor strategy, to reduce querying time. Finally, a binary hybrid data model was employed to cope with multiple types of data in WMSN and carry out collaborative search of binary hybrid data. The experimental results show that compared with other mainstream methods, the proposed OPRCP method is widely adaptive to massive high-dimensional data in multiple types and can improve the accuracy of query results. The OPRCP method exhibits good performance, effectively saves resources, and reduces query time for a variety of datasets. It is an effective solution to the binary hybrid search of approximate neighbors, and it is applicable to the WMSN data search based on smart contracts in WMSN blockchain systems.
Year
DOI
Venue
2018
10.1186/s13638-018-1221-3
EURASIP Journal on Wireless Communications and Networking
Keywords
Field
DocType
WMSN hybrid data,Approximate nearest neighbor binary search,LSH,Blockchain,IPFS
k-nearest neighbors algorithm,Data mining,File system,Computer science,Curse of dimensionality,Real-time computing,Data type,Hash function,Binary search algorithm,Nearest neighbor search,Binary number
Journal
Volume
Issue
ISSN
2018
1
1687-1499
Citations 
PageRank 
References 
0
0.34
21
Authors
6
Name
Order
Citations
PageRank
Huakun Liu101.01
Xin Wei235.68
Ruliang Xiao3288.42
Lifei Chen429226.44
Xin Du512726.78
Shi Zhang6436.16