Martín Pérez, JorgeMalandrino, FrancescoChiasserini, C. F.Bernardos Cano, Carlos Jesús2020-11-052020-11-052020-07-01Martín-Peréz, J., Malandrino,F., Chiasserini,C. F., Bernardos, C. J.(2020). OKpi: All-KPI Network Slicing Through Efficient Resource Allocation. In IEEE INFOCOM 2020 - IEEE Conference on Computer Communications, pp. 804-813.978-1-7281-6412-0https://hdl.handle.net/10016/31337This paper has been presented at INFOCOM 2020: IEEE International Conference on Computer CommunicationsNetworks can now process data as well as transporting it; it follows that they can support multiple services, each requiring different key performance indicators (KPIs). Because of the former, it is critical to efficiently allocate network and computing resources to provide the required services, and, because of the latter, such decisions must jointly consider all KPIs targeted by a service. Accounting for newly introduced KPIs (e.g., availability and reliability) requires tailored models and solution strategies, and has been conspicuously neglected by existing works, which are instead built around traditional metrics like throughput and latency. We fill this gap by presenting a novel methodology and resource allocation scheme, named OKpi, which enables high-quality selection of radio points of access as well as VNF (Virtual Network Function) placement and data routing, with polynomial computational complexity. OKpi accounts for all relevant KPIs required by each service, and for any available resource from the fog to the cloud. We prove several important properties of OKpi and evaluate its performance in two real-world scenarios, finding it to closely match the optimum.10eng© 2020 IEEE.conference paperTelecomunicacioneshttps://doi.org/10.1109/INFOCOM41043.2020.9155263open access804813Proceedings of IEEE INFOCOM 2020 - IEEE Conference on Computer CommunicationsCC/0000031095