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dc.contributor.authorKalafatidis, Sarantis-
dc.contributor.authorMamatas, Lefteris-
dc.description.abstractAlthough 5G networks achieve impressive improvements in terms of latency, data rates and network capacity, their evolution requires the synergy of networks, clouds and applications. For example, targeted challenging applications require efficient end-to-end performance, impacted by emerging technologies beyond radio, including: (i) Software-Defined Networks (SDNs) enabling programmability in the network environment from a centralized viewpoint; (ii) cloud orchestrators dynamically adapting server resource allocation to dynamic workloads; and (iii) microservice-based applications consisting of minimal, single-purpose service functions communicating with each other, individually implemented and scaled towards efficient resource allocation and fault-tolerance. In this context, we propose an SDN load balancing solution for a specific class of services consisting of microservices with heterogeneous but simpler network and server resource requirements, compared to the resource-demands of the whole service. Our proposal adapts to the estimated resource demands of individual microservices, balances resource utilization among cloud servers and improves service operation in terms of response times, throughput and fairness. We validate experimentally the proposed platform and its mechanisms with a particular 5G and beyond use-case with the above characteristics.en_US
dc.sourceIEEE Networken_US
dc.subjectFRASCATI::Engineering and technologyen_US
dc.subjectFRASCATI::Engineering and technology::Other engineering and technologiesen_US
dc.subject.otherMicroservice architecturesen_US
dc.subject.otherLoad managementen_US
dc.subject.otherCloud computingen_US
dc.subject.otherResource managementen_US
dc.subject.other5G mobile communicationen_US
dc.titleMicroservices-Adaptive Software-Defined Load Balancing for 5G and Beyond Ecosystemsen_US
dc.contributor.departmentΤμήμα Εφαρμοσμένης Πληροφορικήςen_US
Appears in Collections:Department of Applied Informatics

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