A Unified Knowledge Representation and Context-aware Recommender System in Internet of Things

TL;DR

This paper introduces a unified data model and a context-aware recommendation system for IoT, enabling efficient knowledge representation, acquisition, and dynamic application reconfiguration across heterogeneous devices and infrastructures.

Contribution

It presents a novel unified data model and IoT-CANE system for incremental knowledge acquisition and context-driven recommendations in IoT environments.

Findings

Unified data model for IoT resource configuration

IoT-CANE enables dynamic, context-aware knowledge recommendations

Improves IoT application development and reconfiguration efficiency

Abstract

Within the rapidly developing Internet of Things (IoT), numerous and diverse physical devices, Edge devices, Cloud infrastructure, and their quality of service requirements (QoS), need to be represented within a unified specification in order to enable rapid IoT application development, monitoring, and dynamic reconfiguration. But heterogeneities among different configuration knowledge representation models pose limitations for acquisition, discovery and curation of configuration knowledge for coordinated IoT applications. This paper proposes a unified data model to represent IoT resource configuration knowledge artifacts. It also proposes IoT-CANE (Context-Aware recommendatioN systEm) to facilitate incremental knowledge acquisition and declarative context driven knowledge recommendation.