Ewya: an interoperable fog computing infrastructure with RDF stream processing
Ewya: an interoperable fog computing infrastructure with RDF stream processing
Fog computing is an emerging technology for the Internet of Things (IoT) that aims to support processing on resource-constrained distributed nodes in between the sensors and actuators on the ground and compute clusters in the cloud. Fog Computing benefits from low latency, location awareness, mobility, wide-spread deployment and geographical distribution at the edge of the network. However, there is a need to investigate, optimise for and measure the performance, scalability and interoperability of resource-constrained Fog nodes running real-time applications and queries on streaming IoT data before we can realise these benefits. With Eywa, a novel Fog Computing infrastructure, we (1) formally define and implement a means of distribution and control of query workload with an inverse publish-subscribe and push mechanism, (2) show how data can be integrated and made interoperable through organising data as Linked Data in the Resource Description Format (RDF), (3) test if we can improve RDF Stream Processing query performance and scalability over state-of-the-art engines with our approach to query translation and distribution for a published IoT benchmark on resource-constrained nodes and (4) position Fog Computing within the Internet of the Future.
245-265
Siow, Boon Lin Eugene
01f33f70-e412-467c-aab2-5509d58d1b94
Tiropanis, Athanassios
d06654bd-5513-407b-9acd-6f9b9c5009d8
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
22 November 2017
Siow, Boon Lin Eugene
01f33f70-e412-467c-aab2-5509d58d1b94
Tiropanis, Athanassios
d06654bd-5513-407b-9acd-6f9b9c5009d8
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
Siow, Boon Lin Eugene, Tiropanis, Athanassios and Hall, Wendy
(2017)
Ewya: an interoperable fog computing infrastructure with RDF stream processing.
Kompatsiaris, I.
(ed.)
In Internet Science. INSCI 2017.
vol. 10673,
Springer.
.
(doi:10.1007/978-3-319-70284-1_20).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Fog computing is an emerging technology for the Internet of Things (IoT) that aims to support processing on resource-constrained distributed nodes in between the sensors and actuators on the ground and compute clusters in the cloud. Fog Computing benefits from low latency, location awareness, mobility, wide-spread deployment and geographical distribution at the edge of the network. However, there is a need to investigate, optimise for and measure the performance, scalability and interoperability of resource-constrained Fog nodes running real-time applications and queries on streaming IoT data before we can realise these benefits. With Eywa, a novel Fog Computing infrastructure, we (1) formally define and implement a means of distribution and control of query workload with an inverse publish-subscribe and push mechanism, (2) show how data can be integrated and made interoperable through organising data as Linked Data in the Resource Description Format (RDF), (3) test if we can improve RDF Stream Processing query performance and scalability over state-of-the-art engines with our approach to query translation and distribution for a published IoT benchmark on resource-constrained nodes and (4) position Fog Computing within the Internet of the Future.
Text
eywa
- Accepted Manuscript
Text
eywa
- Accepted Manuscript
More information
Accepted/In Press date: 17 July 2017
e-pub ahead of print date: 2 November 2017
Published date: 22 November 2017
Venue - Dates:
INSCI 2017, The 4th International Conference on Internet Science, , Thessaloniki, Greece, 2017-11-22 - 2017-11-24
Identifiers
Local EPrints ID: 412749
URI: http://eprints.soton.ac.uk/id/eprint/412749
PURE UUID: 42b0d32b-316b-450d-ba5b-63752b468eda
Catalogue record
Date deposited: 31 Jul 2017 16:31
Last modified: 15 Sep 2021 05:41
Export record
Altmetrics
Contributors
Author:
Boon Lin Eugene Siow
Author:
Athanassios Tiropanis
Editor:
I. Kompatsiaris
University divisions
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics