  Network function virtualization is a promising technology to simultaneously
support multiple services with diverse characteristics and requirements in the
fifth generation and beyond networks. In practice, each service consists of a
predetermined sequence of functions, called service function chain (SFC),
running on a cloud environment. To make different service slices work properly
in harmony, it is crucial to select the cloud nodes to deploy the functions in
the SFC and flexibly route the flow of the services such that these functions
are processed in sequence, the end-to-end (E2E) latency constraints of all
services are guaranteed, and all resource constraints are respected. In this
paper, we propose a new (mixed binary linear program) formulation of the above
network slicing problem that optimizes the system energy efficiency while
jointly considers the resource budget, functional instantiation, flow routing,
and E2E latency requirement. Numerical results show the advantage of the
proposed formulation compared to the existing ones.
