Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/2570
Full metadata record
DC FieldValueLanguage
dc.contributor.authorJingle, I Diana Jeba-
dc.contributor.authorPaul, P Mano-
dc.date.accessioned2023-12-19T05:08:54Z-
dc.date.available2023-12-19T05:08:54Z-
dc.date.issued2021-
dc.identifier.citationVol. 1333 AISC; pp. 155-160en_US
dc.identifier.isbn9789813369658-
dc.identifier.isbn9789813369665-
dc.identifier.issn2194-5357-
dc.identifier.issn2194-5365-
dc.identifier.urihttps://doi.org/10.1007/978-981-33-6966-5_16-
dc.identifier.urihttp://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/2570-
dc.description.abstractFog computing is an emerging technology that offers high-quality cloud services by providing high bandwidth, low latency, and efficient computational power and storage capacity. Although cloud computing is an efficient solution so far to store and retrieve the huge data of IoT devices, it is expected to limit its performance due to low latency and storage capacity. Fog computing addresses these limitations by extending its services to the cloud at the edge of the network. In this paper, we use a fog computing network approach for efficiently retrieving the real-time patient data. The performance of our proposed approach has been compared with the cloud computing approach in terms of retrieval time of real-time data. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.en_US
dc.language.isoenen_US
dc.publisherAdvances in Intelligent Systems and Computing: ISSIP 2020en_US
dc.subjectAdafruiten_US
dc.subjectFog computingen_US
dc.subjectInternet of thingsen_US
dc.subjectRaspberry Pien_US
dc.titleA Fog-Based Retrieval of Real-Time Data For Health Applicationsen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.