dc.contributor.author | Wu, Y | |
dc.date.accessioned | 2020-08-25T09:38:39Z | |
dc.date.issued | 2020-08-07 | |
dc.description.abstract | The Internet-of-Things (IoT) has been deeply penetrated into a wide range of important and critical sectors, including smart city, water, transportation, manufacturing and smart factory. Massive data are being acquired from a fast growing number of IoT devices. Efficient data processing is a necessity to meet diversified and stringent requirements of many emerging IoT applications. Due to the constrained computation and storage resources, IoT devices have resorted to the powerful cloud computing to process their data. However, centralised and remote cloud computing may introduce unacceptable communication delay since its physical location is far away from IoT devices. Edge cloud has been introduced to overcome this issue by moving the cloud in closer proximity to IoT devices. The orchestration and cooperation between the cloud and the edge provides a crucial computing architecture for IoT applications. Artificial intelligence (AI) is a powerful tool to enable the intelligent orchestration in this architecture. This paper first introduces such a kind of computing architecture from the perspective of IoT applications. It then investigates the state-of-the-art proposals on AI-powered cloud-edge orchestration for the IoT. Finally, a list of potential research challenges and open issues is provided and discussed, which can provide useful resources for carrying out future research in this area. | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.identifier.citation | Published online 7 August 2020 | en_GB |
dc.identifier.doi | 10.1109/jiot.2020.3014845 | |
dc.identifier.grantnumber | EP/R030863/1 | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/122628 | |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_GB |
dc.rights | © 2020 IEEE. Personal use of this material is permitted.
However, permission to use this material for any other purposes must be
obtained from the IEEE by sending a request to pubs-permissions@ieee.org. | en_GB |
dc.subject | Cloud Computing | en_GB |
dc.subject | Edge Computing | en_GB |
dc.subject | Internet-of-Things | en_GB |
dc.subject | Artificial Intelligence | en_GB |
dc.subject | Offloading | en_GB |
dc.title | Cloud-Edge Orchestration for the Internet-of-Things: Architecture and AI-Powered Data Processing | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2020-08-25T09:38:39Z | |
dc.description | This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record | en_GB |
dc.identifier.eissn | 2327-4662 | |
dc.identifier.journal | IEEE Internet of Things | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
exeter.funder | ::Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2020-08-07 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2020-08-25T08:59:35Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2020-08-25T09:38:44Z | |
refterms.panel | B | en_GB |