  Existing works on task offloading in mobile edge computing (MEC) networks
often assume a task is executed once at a single edge node (EN). Downloading
the computed result from the EN back to the mobile user may suffer long delay
if the downlink channel experiences strong interference or deep fading. This
paper exploits the idea of computation replication in MEC networks to speed up
the downloading phase. Computation replication allows each user to offload its
task to multiple ENs for repetitive execution so as to create multiple copies
of the computed result at different ENs which can then enable transmission
cooperation and hence reduce the communication latency for result downloading.
Yet, computation replication may also increase the communication latency for
task uploading, despite the obvious increase in computation load. The main
contribution of this work is to characterize asymptotically an order-optimal
upload-download communication latency pair for a given computation load in a
multi-user multi-server MEC network. Analysis shows when the computation load
increases within a certain range, the downloading time decreases in an
inversely proportional way if it is binary offloading or decreases linearly if
it is partial offloading, both at the expense of linear increase in the
uploading time.
