Publication
Event processing in web of things
| datacite.subject.fos | Engenharia e Tecnologia::Outras Engenharias e Tecnologias | pt_PT |
| dc.contributor.advisor | Correia, N. | |
| dc.contributor.author | Mazayev, Andriy | |
| dc.date.accessioned | 2022-10-26T09:59:53Z | |
| dc.date.available | 2022-10-26T09:59:53Z | |
| dc.date.issued | 2022-05-30 | |
| dc.description.abstract | The incoming digital revolution has the potential to drastically improve our productivity, reduce operational costs and improve the quality of the products. However, the realization of these promises requires the convergence of technologies — from edge computing to cloud, artificial intelligence, and the Internet of Things — blurring the lines between the physical and digital worlds. Although these technologies evolved independently over time, they are increasingly becoming intertwined. Their convergence will create an unprecedented level of automation, achieved via massive machine-to-machine interactions whose cornerstone are event processing tasks. This thesis explores the intersection of these technologies by making an in-depth analysis of their role in the life-cycle of event processing tasks, including their creation, placement and execution. First, it surveys currently existing Web standards, Internet drafts, and design patterns that are used in the creation of cloud-based event processing. Then, it investigates the reasons for event processing to start shifting towards the edge, alongside with the standards that are necessary for a smooth transition to occur. Finally, this work proposes the use of deep reinforcement learning methods for the placement and distribution of event processing tasks at the edge. Obtained results show that the proposed neural-based event placement method is capable of obtaining (near) optimal solutions in several scenarios and provide hints about future research directions. | pt_PT |
| dc.description.abstract | A nova revolução digital promete melhorar drasticamente a nossa produtividade, reduzir os custos operacionais e melhorar a qualidade dos produtos. A concretizac¸ ˜ao dessas promessas requer a convergˆencia de tecnologias – desde edge computing à cloud, inteligência artificial e Internet das coisas (IoT) – atenuando a linha que separa o mundo físico do digital. Embora as quatro tecnologias mencionadas tenham evoluído de forma independente ao longo do tempo, atualmente elas estão cada vez mais interligadas. A convergência destas tecnologias irá criar um nível de automatização sem precedentes. | pt_PT |
| dc.description.sponsorship | The research published in this work was supported by the Portuguese Foundation for Science and Technology (FCT) through CEOT (Center for Electronic, Optoelectronic and Telecommunications) funding (UID/MULTI/00631/2020) and by FCT Ph.D grant to Andriy Mazayev (SFRH/BD/138836/2018). | pt_PT |
| dc.identifier.tid | 101707169 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.1/18431 | |
| dc.language.iso | eng | pt_PT |
| dc.relation | Edge assisted IoT orchestration | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Padrões da web | pt_PT |
| dc.subject | Internet das coisas | pt_PT |
| dc.subject | Web das coisas | pt_PT |
| dc.subject | Processamento de eventos | pt_PT |
| dc.subject | Edge computing | pt_PT |
| dc.subject | Balanceamento de carga | pt_PT |
| dc.subject | Colocação de recursos | pt_PT |
| dc.subject | Rede neuronais | pt_PT |
| dc.subject | Deep reinforcement learning | pt_PT |
| dc.title | Event processing in web of things | pt_PT |
| dc.type | doctoral thesis | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Edge assisted IoT orchestration | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F138836%2F2018/PT | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | doctoralThesis | pt_PT |
| relation.isProjectOfPublication | 57ea9449-62b9-420c-bdf2-ddb4a2ae270e | |
| relation.isProjectOfPublication.latestForDiscovery | 57ea9449-62b9-420c-bdf2-ddb4a2ae270e | |
| thesis.degree.grantor | Universidade do Algarve. Faculdade de Ciências e Tecnologia | |
| thesis.degree.level | Doutor | |
| thesis.degree.name | Doutoramento em Engenharia Informática | pt_PT |