  The commercialization of Cloud-RAN, and Open-RAN in particular, is a key
factor to enable 5G cell densification, by providing lower cost and more agile
deployment of small cells. In addition, the adoption of MEC is important to
support ultra-low latency and high reliability required by mission-critical
applications, which constitute a milestone of the 5G and beyond vision of a
fully connected society. However, connecting antenna site, C-RAN processing and
MEC at low cost is challenging, as it requires high-capacity, low latency
connectivity delivered through a highly inter-connected topology. While PON is
being considered as a solution for providing low-cost connectivity to C-RAN,
they only allow data transmission from the endpoints (for example hosting RU at
the antenna site) towards a central node (e.g., the central office, hosting
computing equipment), thus cannot support traffic from RU towards MEC end nodes
that could host DU and possibly CU and network core. This led to research into
the evolution of PON architectures with the ability to provide direct
communications between endpoints, thus supporting mesh traffic patterns
required by MEC installations. In this context, virtualization plays a key role
in enabling efficient resource allocation (i.e. optical transmission capacity)
to endpoints, according to their communication patterns. In this article, we
address the challenge of dynamic allocation of virtual PON slices over mesh-PON
architectures to support C-RAN and MEC nodes. We make use of a mixed
analytical-iterative model to compute optimal virtual PON slice allocation,
with the objective of minimizing the use of MEC node resources, while meeting a
target latency threshold (100 $\mu s$ in our scenario). Our method is
particularly effective in reducing computation time, enabling virtual PON slice
allocation in timescales compatible with real-time or near real-time
operations.
