2023/04/27 by Anousheh Gholami, Gholami, Anousheh, Nariman Torkzaban +3 · 1 citation
Computer Science · #FOS: Electrical engineering #Network Security and Intrusion Detection #Software System Performance and Reliability #Software-Defined Networks and 5G #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2304.14556
openalex publication_date 2023/04/27 · openalex created_date 2023/05/02 · openalex updated_date 2026/07/28
Network slicing enables the deployment of multiple dedicated virtual sub-networks, i.e. slices on a shared physical infrastructure. Unlike traditional one-size-fits-all resource provisioning schemes, each network slice (NS) in 5G is tailored to the specific service requirements of a group of customers. An end-to-end (E2E) mobile NS orchestration requires the simultaneous provisioning of computing, storage, and networking resources across the core network (CN) and the radio access network (RAN). Constant temporospatial changes in mobile user demand profiles further complicate the E2E NSs resource provisioning beyond the limits of the existing best-effort schemes that are only effective under accurate demand forecasts for all slices. This paper proposes a practical two-time-scale resource provisioning framework for E2E network slicing under demand uncertainty. At each macro-scale instance, we assume that only the spatial probability distribution of the NS demands is available. We formulate the NSs resource allocation problem as a stochastic mixed integer program (SMIP) with the objective of minimizing the total resource cost at the CN and the RAN. At each microscale instance, utilizing the exact slice demand profiles, a linear program is solved to jointly minimize the unsupported traffic and the resource cost at the RAN. We verify the effectiveness of our resource allocation scheme through numerical experiments.