FutureWare: Designing a Middleware for Anticipatory Mobile Computing

• Published in: IEEE transactions on software engineering Vol. 47; no. 10; pp. 2107 - 2124
• Main Authors: Mehrotra, Abhinav, Pejovic, Veljko, Musolesi, Mirco
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2021; IEEE Computer Society
• Subjects: Anticipatory computing; Applications programs; Context; Context modeling; Machine learning; Middleware; Mobile applications; Mobile computing; mobile middleware; mobile sensing; Modelling; prediction; Prediction models; Predictive models; Sensors; Servers; Systems developers; Ubiquitous computing
• ISSN: 0098-5589; 1939-3520
• DOI: 10.1109/TSE.2019.2943554

Ubiquitous computing is moving from context-awareness to context-prediction. In order to build truly anticipatory systems developers have to deal with many challenges, from multimodal sensing to modeling context from sensed data, and, when necessary, coordinating multiple predictive models across devices. Novel expressive programming interfaces and paradigms are needed for this new class of mobile and ubiquitous applications. In this paper we present FutureWare, a middleware for seamless development of mobile applications that rely on context prediction. FutureWare exposes an expressive API to lift the burden of mobile sensing, individual and group behavior modeling, and future context querying, from an application developer. We implement FutureWare as an Android library, and through a scenario-based testing and a demo app we show that it represents an efficient way of supporting anticipatory applications, reducing the necessary coding effort by two orders of magnitude.