SHS Web Conf.
Volume 139, 2022The 4th ETLTC International Conference on ICT Integration in Technical Education (ETLTC2022)
|Number of page(s)||10|
|Section||Topics in Computer Science|
|Published online||13 May 2022|
Suitability of self-organizing service composition approach for smart healthcare ecosystem: A study
1 Research Scholar, Department of Computer Science, CHRIST (Deemed to be University), India
2 Associate Professor, Department of Computer Science, CHRIST (Deemed to be University), India
* Correspondingauthor: email@example.com
Future IoT systems will be deployed in open environments where the functionality of millions of IoT devices that are heterogeneous will be abstracted. In such a large scale system manual service composition is not feasible and often erroneous. A self-organizing service composition is a well known approach to deal with the problems in IoT systems. In a self-organizing service composition, the service composition is a runtime and autonomous process and human intervention is minimal. The atomic components will interact among themselves in a decentralized manner to form complex composites according to a set of self-organizing rules. The features of a self-organizing software composition are aptly suitable for the IoT domain. Smart healthcare has provided affordable healthcare for patients and enables them to self manage emergencies. This paper aims to establish the suitability of a self-organizing service composition for the smart healthcare ecosystem with special focus on real time monitoring applications.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.