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Nowadays, a variety ofhandheld mobile devices are capable of connecting to the Internet using multiple network interfaces. This is referred to as multi-homing. In addition to this, enriched computation resources allow them to host nomadic mobile services and provide these services to the clients located anywhere in the Internet. Potential advantages of multi-homing for nomadic mobile services typically includes: an increased service availability and improved service performance. However, applications running on the handheld mobile devices either do not, or cannot, exploit multi-homing. In this paper we address the problem ofproviding infrastructural support to the nomadic mobile services that can fully exploit multi-homing. To this end we propose to incorporate multi-homing functionality and support in a middleware layer to reduce the complexity of the design and maintenance of these services. The proposed solution uses a context-aware computing approach to realize this functionality. We report the initial experimental results in the remote telemonitoring of a patient equipped with a Body Area Network.

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Emerging healthcare applications rely on personal mobile devices to monitor and transmit patient vital signs to hospital-backend servers for further analysis. However, these devices have limited resources that must be used optimally in order to meet the application user requirements (e.g. safety, usability, reliability, performance). This paper reports on a case study of a Chronic Obstructive Pulmonary Disease telemonitoring application delivered by the MobiHealth system. This system relies on a commercial mobile device with multiple (wireless) Network Interfaces (NI). Our study focuses on how NI activation strategies affect the application end-to-end data delay (important in case of an emergency situation) and the energy consumption of the device (important for device sustainability while a patient is mobile). Our results show the trade-off between end-to-end delay and battery life-time achieved by various NI activation strategies, in combination with application-data flow adaptation for realtime and near real-time data transmission. For a given mobile device, our study shows an increase in battery life-time of 40- 90 %, traded against higher end-to-end data delay. The insights of our studies can be used for application-data flow adaptation aiming to increase battery life-time and device sustainability for mobile patients; which effectively increases the healthcare application usability

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