Provenance based checkpointing method for dynamic health care smart system*

Eszter Kail, Krisztián Karóczkai, Péter Kacsuk, Miklós Kozlovszky

Research output: Article

4 Citations (Scopus)

Abstract

Smart systems in telemedicine frequently use intelligent sensor devices at large scale. Practitioners can monitor non-stop the vital parameters of hundreds of patients in real-time. The most important pillars of remote patient monitoring services are communication and data processing. Large scale data processing is done mainly using workflows. Some workflows are working in real-time, more complex ones are running for days or even for weeks on parallel and distributed infrastructures such as HPC systems and cloud. In HPC environment high number of failures can arise during health care smart systems workflow enactment, so the use of fault tolerance techniques is unavoidable. The most frequently used fault tolerance technique is checkpointing. The effectiveness of the checkpointing method depends on the checkpointing interval. In this work we give a brief overview of the different checkpointing techniques and propose two new provenance based checkpointing algorithms which uses the information stored in the workflow structure to dynamically change the frequency of checkpointing and can be efficiently used for dynamic health care smart systems.

Original languageEnglish
Pages (from-to)143-153
Number of pages11
JournalScalable Computing
Volume17
Issue number2
DOIs
Publication statusPublished - 2016

ASJC Scopus subject areas

  • Computer Science(all)

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