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.
Highlights
The wireless multimedia sensor network (WMSN) is a new wireless sensor network developed based on wireless sensor networks (WSN) with multimedia data such as videos, audios, and images
In view of the above problems in WMSN blockchain InterPlanetary File System (IPFS) systems, we proposed a novel hybrid data query method named OPRCP (One Permutation with Rotation and Cross-Polytope locality-sensitive hashing) in this paper, in which we used a kind of approximate nearest neighbor binary search of WMSN binary hybrid data, such as image-text and image-audio
6 Conclusions In view of preventing sensitive data of WMSN Internet of Things (IoT) to be tampered, it is a feasible solution to build a blockchain application of WMSN IoT based on Ethereum and IPFS
Summary
The wireless multimedia sensor network (WMSN) is a new wireless sensor network developed based on wireless sensor networks (WSN) with multimedia data such as videos, audios, and images. People usually construct a WMSN blockchain application solution based on Ethereum and IPFS [7]. Previous work [8] indicates that query of massive multimedia data is composed of three procedures: (1) extraction of multimedia data features, (2) creation of query indexes on feature data in datasets, and (3) mapping query objects into the query index structure. With regard to multimedia data search on WMSN blockchain, existing methods are challenged in three aspects as follows: Problem 1 (curse of space): massive data storage on WMSN blockchain and IPFS need a large space for data themselves, but existing methods tend to consume space several times larger than that for datasets when creating index structures on the premise of ensuring accuracy, which is undoubtedly a “curse of space” to massive datasets
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