Fine-grained Conflict Detection of IoT Services
Dipankar Chaki, Athman Bouguettaya
Abstract
We propose a novel conflict detection framework for IoT services in multi-resident smart homes. A fine-grained conflict model is developed considering the functional and non-functional properties of IoT services. The proposed conflict model is designed using the concept of entropy and information gain from information theory. We use a novel algorithm based on temporal proximity to detect conflicts. A set of experiments on real-world datasets are conducted to show the efficiency of the proposed approach.
Topics & Concepts
Computer scienceInternet of ThingsEntropy (arrow of time)Set (abstract data type)Conflict analysisDistributed computingComputer securityConflict resolutionProgramming languagePolitical scienceLawQuantum mechanicsPhysicsIoT and Edge/Fog ComputingContext-Aware Activity Recognition SystemsData Stream Mining Techniques