A Hybrid Search Engine Framework for the Internet of Things

Zhiming Ding, Xu Gao, Limin Guo, Qi Yang
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引用次数: 24

Abstract

Efficient retrieval of dynamically generated, spatial-temporal, and heterogeneous sampling data in the Internet of Things is a key challenge in recent years. However, current search engine techniques are not suitable for such kind of data. To solve this problem, we propose a Hybrid Search Engine Technique for the Internet of Things based on Spatial-Temporal, Value-based, and Keyword-based Conditions ("IoT-SVK Search Engine"), in this paper. The IoT-SVK search engine has satisfactory performances in supporting multi-modal retrieval conditions, and thus provides a good solution for real-time searching of massive sampling data in the Internet of Things.
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物联网的混合搜索引擎框架
物联网中动态生成的、时空的、异构的采样数据的有效检索是近年来的一个关键挑战。然而,目前的搜索引擎技术并不适合这类数据。为了解决这一问题,本文提出了一种基于时空、价值和关键字条件的物联网混合搜索引擎技术(“IoT-SVK搜索引擎”)。IoT-SVK搜索引擎在支持多模态检索条件方面具有令人满意的性能,为物联网中海量采样数据的实时检索提供了很好的解决方案。
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