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 work
flows. Some work
flows 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 work
ow 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 work
ow structure to dynamically change the frequency of checkpointing and can be efficiently used for dynamic health care smart systems.