Adaptive failure detection and correction in dynamic patient-networks

Wireless sensors have been studied over recent years for different promising applications with high value for individuals and society. A good example are wireless sensor networks for patients allowing for better and more efficient monitoring of patients in hospitals or even early discharge form hospital and monitoring at home. These visions have hardly led research as reliability is and issue with wireless networks to be known error-prone. In life critical applications like health care this is not an aspect to be handled carelessly. Fail-safety is an important property for patient monitoring systems. The Ambient Assistance for Recovery (AA4R) project of the Hamburg University of Technology researches on a fail-safe patient monitoring system. Our vision is a dynamically distributed system using suitable devices in the area of a patient. The data in the network is stored with redundancy on several nodes. Patient data is analyzed in the network and uploaded to a medical server. As devices appear, disappear and fail, so do the services being executed on those devices. This article focuses on a Reincarnation Service (RS) to track the functionality of the processes. The RS takes suitable actions when a failure is detected to correct or isolate the failure. Checking of the nodes is done adaptively to achieve a good response time to failures and reduce the power consumption. © Martin Ringwelski, Andreas Timm-Giel, and Volker Turau.

Subjects

Distributed systems

Fail-safety

Failure masking

Health monitoring

Wireless sensor networks

DDC Class

380: Handel, Kommunikation, Verkehr

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publishedVersion

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https://creativecommons.org/licenses/by/3.0/

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6-1.pdf

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672.59 KB

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Adaptive failure detection and correction in dynamic patient-networks