CAOS: A Context Acquisition and Offloading System

Citations Over TimeTop 11% of 2017 papers

Abstract

Currently, mobile applications have become increasingly complex. One trend is the usage of contextual information gathered from device sensors and external data sources, which are used to improve the user experience when using mobile applications. As the amount of sensing data increases as well as the complexity of context inference procedures, it leads to an undesirable situation where the mobile device has not enough resources (e.g., memory capacity, processing speed, and battery power) to perform some computation tasks. This paper addresses this issue by proposing CAOS, a software platform that employs the offloading approach to enhance mobile context-aware applications. CAOS allows mobile application developers to offload rocesses and data into cloud and cloudlets infrastructures, aiming at improving the overall application performance and saving battery power. In order to assess our proposal, a reference implementation was built, and experiments were performed in order to evaluate performance and energy consumption of our proposal. Results showed gains in both aspects in most of scenarios, which denote the feasibility of the proposed solution.

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