A Progressive Search Paradigm for the Internet of Things

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Abstract
With the proliferation of Internet of Things (IoT), the IoT search, whose primary tasks are facilitating users to instantly acquire their required knowledge in IoT, has tremendous potential applications. In this paper, we firstly analyze the service patterns in the IoT, and summarize the main characters and challenges of IoT search. To solve the challenges, we propose a progressive search paradigm, which contains three important search strategies: 1) coarse-to-fine search in feature space; 2) near-to-distant search in spatial-temporal space; and 3) low-to-high permission search in the security space. The strategies all utilize the simple features and computation to instantly reduce the search space, in which complex matching process can be efficiently exploited to finely find the matched objects. Finally, we present case studies in the multimedia sensors based urban sensing network, which demonstrate the proposed progressive search paradigm can significantly improve the IoT search speed and accuracy.

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