A Service Mining Scheme Based on Semantic for Internet of Things

As the development of Internet of things (IOT), massive sensors have been deployed as the public infrastructure. With the development of in-depth applications in IOT, service discovery and composition are challenges to the end users. To handle this challenge, we develop a service mining scheme based on semantic for IOT to provide users with interesting composite services. In this scheme, services can be combined and recommended to users actively according to the calculation of service similarity and an updatable semantic database. By the results of service similarity, useless compositions can be filtered out so that energy consumption on service flooding will be reduced. The update strategy of semantic database is also given out, by which the composite services can keep up with time and be more applicative. The benefits of the proposed method are that all operations such as calculating, filtering, and updating are simple enough to be performed in sensor networks.