A Cloud-based Interaction Management System Architecture for Mobile Devices

Abstract

The number of interruptions people experience on a daily basis has grown considerably over the last decade and this growth has not shown any signs of subsiding. In fact, with the exponential growth of mobile computing, interruptions are permeating the user experience. Systems must be developed to manage interruptions by reasoning about ideal timings of interactions and determining appropriate notification formats.In this work, an architecture for a cloud-based interruption management system for mobile device users is presented. The system draws from rich contextual information from the mobile device (i.e., user, task and environment dimensions) and real-time observations of the user's activities and then reasons about ideal times to interact with the user. The reasoning component (interruption algorithm) is situated in the cloud and implemented using a novel machine learning technique (an Adaptive Neuro Fuzzy Inference System). This research addresses the complex problem of determining the precise time to interact with a mobile device user and in so doing aims to reduce the negative aspects of interruptions. This paper also presents a new interruption taxonomy built on an existing framework, and a report on the current prototype developed.