  Next-generation wireless networks will provide users ubiquitous low-latency
computing services using devices at the network edge, called mobile edge
computing (MEC). The key operation of MEC, mobile computation offloading (MCO),
is to offload computation intensive tasks from users. Since each edge device
comprises an access point (AP) and a computer server (CS), a MEC network can be
decomposed as a radio access network (RAN) cascaded with a CS network (CSN).
Based on the architecture, we investigate network constrained latency
performance, namely communication latency (comm-latency) and computation
latency (comp-latency) under the constraints of RAN coverage and CSN stability.
To this end, a spatial random network is modeled featuring random node
distribution, parallel computing, non-orthogonal multiple access, and random
computation-task generation. Given the model and the said network constraints,
we derive the scaling laws of comm-latency and comp-latency with respect to
network-load parameters (density of mobiles and their task-generation rates)
and network-resource parameters (bandwidth, density of APs/CSs, CS computation
rate). Essentially, the analysis involves the interplay of theories of
stochastic geometry, queueing, and parallel computing. Combining the derived
scaling laws quantifies the tradeoffs between the latencies, network coverage
and network stability. The results provide useful guidelines for MEC-network
provisioning and planning by avoiding either of the cascaded RAN or CSN being a
performance bottleneck.
