An Improved Subscription Classification Filtering Method Based on Multi-Index

The Internet of Things seamlessly integrates physical space and information space, and realizes dynamic interaction through the devices sensing of the state changes in the physical environment real-time, thereby providing more intelligent services. Against the problem that the underlying multi-device data source could generate massive sensor data, this article implements the system to distribute perceptual data according to user interests on demand based on the asynchronous communication mechanism of pub/sub, and proposes a multi-level index subscription classification filtering algorithm. The algorithm mainly classifies the subscription set of the system with subscription size and the subscription frequency of attribute as tags, and completes subscription filtering according to the nature of event matching, to a certain extent reducing the number of subscriptions searched during the event-subscription matching process, accelerating the search speed of subscription.