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Cognitive load balancing approach for 6G MEC serving IoT mashups

2021-12-28Journal article Open Access
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dc.contributor.authorAttanasio, Barbara
dc.contributor.authorMazayev, Andriy
dc.contributor.authordu Plessis, Shani
dc.contributor.authorCorreia, Noélia
dc.date.accessioned2022-01-13T11:08:06Z
dc.date.available2022-01-13T11:08:06Z
dc.date.issued2021-12-28
dc.date.updated2022-01-10T14:38:03Z
dc.description.abstractThe sixth generation (6G) of communication networks represents more of a revolution than an evolution of the previous generations, providing new directions and innovative approaches to face the network challenges of the future. A crucial aspect is to make the best use of available resources for the support of an entirely new generation of services. From this viewpoint, the Web of Things (WoT), which enables Things to become Web Things to chain, use and re-use in IoT mashups, allows interoperability among IoT platforms. At the same time, Multi-access Edge Computing (MEC) brings computing and data storage to the edge of the network, which creates the so-called distributed and collective edge intelligence. Such intelligence is created in order to deal with the huge amount of data to be collected, analyzed and processed, from real word contexts, such as smart cities, which are evolving into dynamic and networked systems of people and things. To better exploit this architecture, it is crucial to break monolithic applications into modular microservices, which can be executed independently. Here, we propose an approach based on complex network theory and two weighted and interdependent multiplex networks to address the Microservices-compliant Load Balancing (McLB) problem in MEC infrastructure. Our findings show that the multiplex network representation represents an extra dimension of analysis, allowing to capture the complexity in WoT mashup organization and its impact on the organizational aspect of MEC servers. The impact of this extracted knowledge on the cognitive organization of MEC is quantified, through the use of heuristics that are engineered to guarantee load balancing and, consequently, QoS.pt_PT
dc.description.sponsorship(MIUR)—PON REC 2014–2020
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationMathematics 10 (1): 101 (2022)pt_PT
dc.identifier.doi10.3390/math10010101pt_PT
dc.identifier.issn2227-7390
dc.identifier.urihttp://hdl.handle.net/10400.1/17474
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationCenter for Electronics, Optoelectronics and Telecommunications
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subject6Gpt_PT
dc.subjectComplex network theorypt_PT
dc.subjectMicroservicespt_PT
dc.subjectMulti access edge computingpt_PT
dc.subjectMultiplex networkspt_PT
dc.subjectQoSpt_PT
dc.subjectTask offloadingpt_PT
dc.subjectWeb of thingspt_PT
dc.titleCognitive load balancing approach for 6G MEC serving IoT mashupspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCenter for Electronics, Optoelectronics and Telecommunications
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00631%2F2020/PT
oaire.citation.issue1pt_PT
oaire.citation.startPage101pt_PT
oaire.citation.titleMathematicspt_PT
oaire.citation.volume10pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameMazayev
person.familyNamedu Plessis
person.familyNameCorreia
person.givenNameAndriy
person.givenNameShani
person.givenNameNoélia
person.identifierR-00G-XFD
person.identifierR-000-DJV
person.identifier.ciencia-idD91F-F08D-5380
person.identifier.ciencia-idBC19-C592-9FA7
person.identifier.ciencia-idDD19-1F35-B804
person.identifier.orcid0000-0003-0495-9801
person.identifier.orcid0000-0001-7051-7193
person.identifier.ridM-3554-2013
person.identifier.scopus-author-id56565451000
person.identifier.scopus-author-id8411596100
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication5bc05e4c-cb79-4954-87e8-ebacb4473268
relation.isAuthorOfPublicationbb8795fe-de73-415b-91c0-2a9d3f6db7ab
relation.isAuthorOfPublicationfdbe5057-0478-46cd-9506-caa73ea79d9f
relation.isAuthorOfPublication.latestForDiscoveryfdbe5057-0478-46cd-9506-caa73ea79d9f
relation.isProjectOfPublication6c1217d9-1340-45e8-91d8-e75348854f62
relation.isProjectOfPublication.latestForDiscovery6c1217d9-1340-45e8-91d8-e75348854f62

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