Grid Computing: A Practical Guide to Technology and Applications
Grid Computing: A Practical Guide to Technology and Applications
TOSSIM: accurate and scalable simulation of entire TinyOS applications
Proceedings of the 1st international conference on Embedded networked sensor systems
The Anatomy of the Grid: Enabling Scalable Virtual Organizations
International Journal of High Performance Computing Applications
A survey and analysis of Electronic Healthcare Record standards
ACM Computing Surveys (CSUR)
Supporting scientific discovery processes in Discovery Net: Research Articles
Concurrency and Computation: Practice & Experience - Selected Papers from the 2004 U.K. e-Science All Hands Meeting (AHM 2004)
On Smart-Care Services: Studies of Visually Impaired Users in Living Contexts
ICDS '07 Proceedings of the First International Conference on the Digital Society
LGDI '05 Proceedings of the 2005 IEEE International Symposium on Mass Storage Systems and Technology
IEEE Communications Magazine
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Wireless Sensor Network (WSN) can be deployed to monitor the health of patients suffering from critical diseases. Also a wireless network consisting of biomedical sensors can be implanted into the patient's body and can monitor the patients' conditions. These sensor devices, apart from having an enormous capability of collecting data from their physical surroundings, are also resource constraint in nature with a limited processing and communication ability. Therefore we have to integrate them with the Grid technology in order to process and store the collected data by the sensor nodes. In this paper, we proposed the SEnsor Grid Enhancement Data Management system, called SEGEDMA ensuring the integration of different network technologies and the continuous data access to system users. The main contribution of this work is to achieve the interoperability of both technologies through a novel network architecture ensuring also the interoperability of Open Geospatial Consortium (OGC) and HL7 standards. According to the results, SEGEDMA can be applied successfully in a decentralized healthcare environment.