  A fog-aided wireless network architecture is studied in which edge-nodes
(ENs), such as base stations, are connected to a cloud processor via dedicated
fronthaul links, while also being endowed with caches. Cloud processing enables
the centralized implementation of cooperative transmission strategies at the
ENs, albeit at the cost of an increased latency due to fronthaul transfer. In
contrast, the proactive caching of popular content at the ENs allows for the
low-latency delivery of the cached files, but with generally limited
opportunities for cooperative transmission among the ENs. The interplay between
cloud processing and edge caching is addressed from an information-theoretic
viewpoint by investigating the fundamental limits of a high
Signal-to-Noise-Ratio (SNR) metric, termed normalized delivery time (NDT),
which captures the worst-case coding latency for delivering any requested
content to the users. The NDT is defined under the assumptions of either serial
or pipelined fronthaul-edge transmission, and is studied as a function of
fronthaul and cache capacity constraints. Placement and delivery strategies
across both fronthaul and wireless, or edge, segments are proposed with the aim
of minimizing the NDT. Information-theoretic lower bounds on the NDT are also
derived. Achievability arguments and lower bounds are leveraged to characterize
the minimal NDT in a number of important special cases, including systems with
no caching capabilities, as well as to prove that the proposed schemes achieve
optimality within a constant multiplicative factor of 2 for all values of the
problem parameters.
