000133248 001__ 133248
000133248 005__ 20240410085328.0
000133248 0247_ $$2doi$$a10.1109/TNSM.2022.3147146
000133248 0248_ $$2sideral$$a137878
000133248 037__ $$aART-2022-137878
000133248 041__ $$aeng
000133248 100__ $$0(orcid)0000-0001-9052-9554$$aOrtin, Jorge
000133248 245__ $$aAnalysis of Scaling Policies for NFV Providing 5G/6G Reliability Levels With Fallible Servers
000133248 260__ $$c2022
000133248 5060_ $$aAccess copy available to the general public$$fUnrestricted
000133248 5203_ $$aThe softwarization of mobile networks enables an efficient use of resources, by dynamically scaling and re-assigning them following variations in demand. Given that the activation of additional servers is not immediate, scaling up resources should anticipate traffic demands to prevent service disruption. At the same time, the activation of more servers than strictly necessary results in a waste of resources, and thus should be avoided. Given the stringent reliability requirements of 5G applications (up to 6 nines) and the fallible nature of servers, finding the right trade-off between efficiency and service disruption is particularly critical. In this paper, we analyze a generic auto-scaling mechanism for communication services, used to de(activate) servers in a cluster, based on occupation thresholds. We model the impact of the activation delay and the finite lifetime of the servers on performance, in terms of power consumption and failure probability. Based on this model, we derive an algorithm to optimally configure the thresholds. Simulation results confirm the accuracy of the model both under synthetic and realistic traffic patterns as well as the effectiveness of the configuration algorithm. We also provide some insights on the best strategy to support an energy-efficient highly-reliable service: deploying a few powerful and reliable machines versus deploying many machines, but less powerful and reliable.
000133248 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T31-20R$$9info:eu-repo/grantAgreement/ES/MCIU-ERDF/RTI2018-099063-B-I00$$9info:eu-repo/grantAgreement/ES/UZ/CUD2021-11
000133248 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000133248 590__ $$a5.3$$b2022
000133248 591__ $$aCOMPUTER SCIENCE, INFORMATION SYSTEMS$$b49 / 158 = 0.31$$c2022$$dQ2$$eT1
000133248 592__ $$a1.693$$b2022
000133248 593__ $$aElectrical and Electronic Engineering$$c2022$$dQ1
000133248 593__ $$aComputer Networks and Communications$$c2022$$dQ1
000133248 594__ $$a7.6$$b2022
000133248 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000133248 700__ $$aSerrano, Pablo
000133248 700__ $$aGarcia-Reinoso, Jaime
000133248 700__ $$aBanchs, Albert
000133248 773__ $$g19, 2 (2022), 1287-1305$$pIEEE Transactions on Network and Service Management$$tIEEE Transactions on Network and Service Management$$x1932-4537
000133248 8564_ $$s12908827$$uhttps://zaguan.unizar.es/record/133248/files/texto_completo.pdf$$yPostprint
000133248 8564_ $$s3381226$$uhttps://zaguan.unizar.es/record/133248/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000133248 909CO $$ooai:zaguan.unizar.es:133248$$particulos$$pdriver
000133248 951__ $$a2024-04-10-08:37:15
000133248 980__ $$aARTICLE