Abstract
Due to the fast evolution of wireless access networks and
high-performance mobile devices together with the
spreading of wearable medical sensors, electronic
healthcare (eHealth) services have recently started to
receive more and more attention, especially in the mobile
Health (mHealth) domain. The vast majority of mHealth
services require strict medical level Quality of Service
(QoS) and Quality of Experience (QoE) provision.
Emergency use-cases, remote patient monitoring,
tele-consultation and guided surgical intervention
require real-time communication and appropriate
connection quality. The increasing significance of
different overlapping wireless accesses makes possible to
provide the required network resources for ubiquitous and
pervasive mHealth applications. Aiming to support such
use-cases in a heterogeneous network environment, we
propose a network-assisted intelligent access point
selection scheme for ubiquitous applications of Future
Internet architectures focusing on real-time mobile
telemedicine services. Our solution is able to discover
nearby base stations that cover the current location of
the mobile device efficiently and to trigger
heterogeneous handovers based on the state and quality of
the current access network. The solution is empirically
evaluated in Wi-Fi networks used by real-life Android
mobile devices and we observed that the scheme can
improve the quality of mHealth applications and enhance
traffic load balancing capabilities of wireless
architectures.
Original language | English |
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Pages (from-to) | 317-324 |
Journal | Procedia Computer Science |
Volume | 63 |
DOIs | |
Publication status | Published - 2015 |
MoE publication type | A1 Journal article-refereed |
Event | 5th International Conference on Current and Future Trends of Information andCommunication Technologies in Healthcare, ICTH 2015, 27 - 30 September 2015, Berlin, Germany - Duration: 1 Jan 2015 → … |
Keywords
- network-assisted handover
- context-awareness
- multi-criteria decision engine
- DDE
- NIS
- Android
- real-time mHealth services
- multi-sensor based patient monitoring
- ubiquitous tele-consultation
- Body Area Network