Journal
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
Volume 38, Issue 7, Pages 1542-1554Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSAC.2020.2986898
Keywords
5G mobile communication; Substrates; Data centers; Bandwidth; Network slicing; Virtual machining; 5G mobile communication; network slicing; Network Function Virtualization (NFV); Virtual Machine (VM) migration; network reconfiguration
Funding
- Nokia Bell Labs
- Nokia Center for Advanced Research (NCAR)
- 5G FORCE research project
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The virtual resources of 5G networks are expected to scale and support migration to other locations within the substrate. In this context, a configuration for 5G network slices details the instantaneous mapping of the virtual resources across all slices on the substrate, and a feasible configuration satisfies the Service-Level Objectives (SLOs) without overloading the substrate. Reconfiguring a network from a given source configuration to the desired target configuration involves identifying an ordered sequence of feasible configurations from the source to the target. The proposed solutions for finding such a sequence are optimized for data centers and cannot be used as-is for reconfiguring 5G network slices. We present Matryoshka, our divide-and-conquer approach for finding a sequence of feasible configurations that can be used to reconfigure 5G network slices. Unlike previous approaches, Matryoshka also considers the bandwidth and latency constraints between the network functions of network slices. Evaluating Matryoshka required a dataset of pairs of source and target configurations. Because such a dataset is currently unavailable, we analyze proof of concept roll-outs, trends in standardization bodies, and research sources to compile an input dataset. On using Matryoshka on our dataset, we observe that it yields close-to-optimal reconfiguration sequences 10X faster than existing approaches.
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