BodyCloud: Integration of Cloud Computing and body sensor networks

Authors:
Giancarlo Fortino;Giuseppe Di Fatta;Mukaddim Pathan
Affiliations:
DEIS - University of Calabria 87036 Rende (CS), Italy;SSE - The University of Reading Reading, RG6 6AX, UK;Telstra Corporation Limited Melbourne, VIC 3000, Australia
Venue:
CLOUDCOM '12 Proceedings of the 2012 IEEE 4th International Conference on Cloud Computing Technology and Science (CloudCom)
Year:
2012

Citing 0
Cited 8

Modeling of WBAN and cloud integration for secure and reliable healthcare

BodyNets '13 Proceedings of the 8th International Conference on Body Area Networks
Toward sensor-cloud integration as a service: optimizing three-tier communication in cloud-integrated sensor networks

BodyNets '13 Proceedings of the 8th International Conference on Body Area Networks
Engineering large-scale body area networks applications
BodyCloud: A SaaS approach for community Body Sensor Networks

Future Generation Computer Systems
Cloud enabled fractal based ECG compression in wireless body sensor networks

Future Generation Computer Systems
A platform for secure monitoring and sharing of generic health data in the Cloud

Future Generation Computer Systems
CoCaMAAL: A cloud-oriented context-aware middleware in ambient assisted living

Future Generation Computer Systems
An energy-saving routing architecture with a uniform clustering algorithm for wireless body sensor networks

Future Generation Computer Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Spatially distributed sensor nodes can be used to monitor systems and humans conditions in a wide range of application domains. A network of body sensors in a community of people generates large amounts of contextual data that requires a scalable approach for storage and processing. Cloud computing can provide a powerful, scalable storage and processing infrastructure to perform both online and offline analysis and mining of body sensor data streams. This paper presents BodyCloud, a system architecture based on Cloud Computing for the management and monitoring of body sensor data streams. It incorporates key concepts such as scalability and flexibility of resources, sensor heterogeneity, and the dynamic deployment and management of user and community applications.