a novel graph-based approach for the management of health data on cloud-based wsans

Nowadays, healthcare applications become among the most important services that help to improve the public safety through, for example, the prevention of the propagation of some epidemic diseases from patient to another or better from a location to another. wireless body area networks (wbans) are considered among the major sources that enable the collection of such kind of data that shares in most cases the properties of big data and that needs to be stored and managed in an efficient manner. regarding this need, wireless storage area networks (wsans) have been considered among the alternatives to store generated health data. even if these infrastructures enable the storage of huge volumes of data, there are some issues related to the efficient storage and processing of health data that still not resolved and that are of interest for the research communities. in this context, this paper proposes a cloud-based wsan approach that enables the storage and the management of health data in an efficient manner by representing the collected data and their dependencies using temporal conceptual graphs (tcgs). the validity of the generated graphs is verified by the proposed graph checker that enables the localization of semantic errors in such structure to prevent some threats to be realized for stored health data and to ensure the privacy of patients. the efficiency of the proposed approach is illustrated for different defined scenarios of diseases and their associated health data represented through generated tcgs.