Provenance Based Checkpointing Method for Dynamic Health Care Smart System
Author(s) -
Eszter Kail,
Krisztián Karóczkai,
Péter Kacsuk,
Miklós Kozlovszky
Publication year - 2016
Publication title -
scalable computing practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.192
H-Index - 18
ISSN - 1895-1767
DOI - 10.12694/scpe.v17i2.1162
Subject(s) - computer science , fault tolerance , cloud computing , distributed computing , scale (ratio) , work (physics) , supercomputer , real time computing , operating system , engineering , quantum mechanics , mechanical engineering , physics
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 workow 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 workow structure to dynamically change the frequency of checkpointing and can be efficiently used for dynamic health care smart systems.
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