Automated decision making algorithms are expected to play a key role in
management and orchestration of network slices in 5G and beyond networks.
State-of-the-art algorithms for automated orchestration and management tend to
rely on data-driven methods which require a timely and accurate view of the
network. Accurately monitoring an end-to-end (E2E) network slice requires a
scalable monitoring architecture that facilitates collection and correlation of
data from various network segments comprising the slice. The state-of-the-art
on 5G monitoring mostly focuses on scalability, falling short in providing
explicit support for network slicing and computing network slice key
performance indicators (KPIs). To fill this gap, in this paper, we present
MonArch, a scalable monitoring architecture for 5G, which focuses on network
slice monitoring, slice KPI computation, and an application programming
interface (API) for specifying slice monitoring requests. We validate the
proposed architecture by implementing MonArch on a 5G testbed, and demonstrate
its capability to compute a network slice KPI (e.g., slice throughput). Our
evaluations show that MonArch does not significantly increase data ingestion
time when scaling the number of slices and that a 5-second monitoring interval
offers a good balance between monitoring overhead and accuracy.Comment: Accepted at IEEE/IFIP NOMS 202