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.

Nowadays, a variety of handheld 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 of providing 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 tele-monitoring of a patient equipped with a Body Area Network.

The network resources available on a mobile device may be better employed when taking into account the history of mobility patterns of the user. We propose an experience-based mechanism for network resource usage by applications on mobile hosts. It incorporates a machine learning component that adapts the network resource usage given a high-level metric, typically consisting of system as well as application related sub-metrics.

Many approaches exist today that address the issues that arise when a mobile node changes its point(s) of attachment to the Internet. Mobile IP takes care of host mobility at the IP layer; others at the transport layer (Mobile SCTP) or at the application layer (SIP with re-invite). In practice, most of these approaches rely on functionality residing on the mobile host that scans, detects and activates the networks available through one or more network interfaces. The mechanism proposed in this paper takes into account that multiple of these approaches may be applied at the same time. It provides the applications on the mobile host with information about the state of the lower-layer mobility management protocols (such as Mobile IP) as well as the state and characteristics of the available network resources. Applications may consecutively adapt their behavior depending on this mobility process information and thus accommodate to the changed network connectivity conditions, possibly in an application specific manner. In this paper, we present the architecture of our mobility management mechanism. We also describe the implementation of our prototype and the results of experiments with the mechanism, thereby addressing the complexities of an integrated applicationaware mobility management system.

We introduce a scalable application-level QoS adaptation service for roaming between wireless networks that are based on different technologies ('inter-tech' roaming). The service is part of a platform that supports the distribution of multimedia streams (e.g., a streamed TV channel) to mobile clients operating in a heterogeneous environment. Central to our approach is the notion of a service class, which is a domain-specific perceptual QoS level. Each domain in a wireless infrastructure must support a limited number of these service classes. Our adaptation service handles inter-tech roaming by handing a client off from one service class to another. We focus on the design of the adaptation service's client-side components. They combine the loss characteristics of the client's network interfaces with configurable policies to decide when to initiate a handoff to a target service class and when to complete it. We conclude with some experimental results.