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dc.creatorFernández Cerero, Damiánes
dc.creatorFernández Montes González, Alejandroes
dc.creatorOrtega Rodríguez, Francisco Javieres
dc.creatorJakóbik, Agnieszkaes
dc.creatorWidlak, Adrianes
dc.date.accessioned2022-03-14T11:48:09Z
dc.date.available2022-03-14T11:48:09Z
dc.date.issued2020
dc.identifier.citationFernández Cerero, D., Fernández Montes González, A., Ortega Rodríguez, F.J., Jakóbik, A. y Widlak, A. (2020). Sphere: Simulator of edge infrastructures for the optimization of performance and resources energy consumption. Simulation Modelling Practice and Theory, 101 (May 2020, nº101966)
dc.identifier.issn1569-190Xes
dc.identifier.urihttps://hdl.handle.net/11441/130751
dc.description.abstractEdge computing constitutes a key paradigm to address the new requirements of areas such as smart cars, industry 4.0, and health care, where massive amounts of heterogeneous data from continuous geographically-distributed sources have to be processed and computed near real-time. To this end, new distributed infrastructures consisting on small computing clusters close to data sources, also known as Cloudlets have emerged. In order to evaluate the performance of these solutions we present Sphere, a simulation tool that enables researchers to establish various scenarios, including: (a) topology and orchestration model of the infrastructure; (b) incoming workload patterns; (c) resource-managing models; and (d) scheduling policies. Moreover, Sphere allows researchers to apply efficiency and performance policies both at infrastructure and cluster levels. The simulator presents the following benefits: (a) Evaluation of various orchestration models; (b) Analysis of resource-efficiency and performance strategies at Edge-infrastructure and cluster (Cloudlet/Cloud) level; (c) Execution of diverse workload generation patterns; (d) Evaluation of strategies for the infrastructure communication, as well as the impact on tasks completion time (makespan); and (e) Simulation of each cluster (Cloudlet/Cloud) independently, including resource-managing, scheduling and resource-efficiency models. Finally, we performed a deep evaluation based on realistic Edge-Computing use cases. The results of the experiments confirm that it is a performant and reliable tool for the analysis of orchestration, graph-resolving, energy-efficiency, resource-managing and scheduling strategies in Edge-computing environments.es
dc.description.sponsorshipMinisterio de Ciencia, Innovación y Universidades RTI2018-098062-A-I00es
dc.formatapplication/pdfes
dc.format.extent17es
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofSimulation Modelling Practice and Theory, 101 (May 2020, nº101966)
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectEdge computinges
dc.subjectFog computinges
dc.subjectCloudlet computinges
dc.subjectCloud computinges
dc.subjectEnergy-aware schedulinges
dc.titleSphere: Simulator of edge infrastructures for the optimization of performance and resources energy consumptiones
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticoses
dc.relation.projectIDRTI2018-098062-A-I00es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S1569190X19300991es
dc.identifier.doi10.1016/j.simpat.2019.101966es
dc.contributor.groupUniversidad de Sevilla. TIC134: Sistemas Informáticoses
dc.journaltitleSimulation Modelling Practice and Theoryes
dc.publication.volumen101es
dc.publication.issueMay 2020, nº101966es
dc.identifier.sisius21886857es
dc.contributor.funderMinisterio de Ciencia, Innovación y Universidades (MICINN). Españaes

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