Abstract:
The Internet of Things (IoT) has become the infrastructure to widely support ubiquitous applications. Due to the highly dynamic context setting, IoT search engines have attracted increasing attention from both industrial and academic field to crawl and search heterogeneous data sources. Today, a large amount of work on IoT search engines is devoted to finding a particular mobile object device, or a group of object devices satisfying the constraint on query terms description. However, it still lacks studies on enabling so-called spatial-temporal-keyword-aware query. Only a few research work simply applies a keyword or spatial-temporal matching to identify object devices. In this case, it is insufficient to simultaneously consider the spatial-temporal-keyword aspect in order to satisfy the user request. To address this challenge, we develop a new search mechanism over PKR-tree (denoted SMPKR), in which PKR-tree unifiedly integrates spatial-temporal-keyword proximity with the help of a coding enabled index. Efficient algorithms are developed for answering range and (enhanced) KNN queries. Extensive experimental results demonstrate that our SMPKR search engine promotes the efficiency of searching for object devices with spatial-temporal-keyword constraints in comparison with the state of arts.