  Network function Virtualization (NFV) and Mobile Edge Computing (MEC) are
promising 5G technologies to support resource-demanding mobile applications. In
NFV, one must process the service function chain (SFC) in which a set of
network functions must be executed in a specific order. Moreover, the MEC
technology enables computation offloading of service requests from mobile users
to remote servers to potentially reduce energy consumption and processing delay
for the mobile application. This paper considers the optimization of the
computation offloading, resource allocation, and SFC placement in the
multi-site MEC system. Our design objective is to minimize the weighted
normalized energy consumption and computing cost subject to the maximum
tolerable delay constraint. To solve the underlying mixed integer and
non-linear optimization problem, we employ the decomposition approach where we
iteratively optimize the computation offloading, SFC placement and computing
resource allocation to obtain an efficient solution. Numerical results show the
impacts of different parameters on the system performance and the superior
performance of the proposed algorithm compared to benchmarking algorithms.
