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Existing works on task offloading in mobile edge computing (MEC) networksoften assume a task is executed once at a single edge node (EN). Downloadingthe computed result from the EN back to the mobile user may suffer long delayif the downlink channel experiences strong interference or deep fading. Thispaper exploits the idea of computation replication in MEC networks to speed upthe downloading phase. Computation replication allows each user to offload itstask to multiple ENs for repetitive execution so as to create multiple copiesof the computed result at different ENs which can then enable transmissioncooperation and hence reduce the communication latency for result downloading.Yet, computation replication may also increase the communication latency fortask uploading, despite the obvious increase in computation load. The maincontribution of this work is to characterize asymptotically an order-optimalupload-download communication latency pair for a given computation load in amulti-user multi-server MEC network. Analysis shows when the computation loadincreases within a certain range, the downloading time decreases in aninversely proportional way if it is binary offloading or decreases linearly ifit is partial offloading, both at the expense of linear increase in theuploading time.

Exploiting Computation Replication for Mobile Edge Computing: A Fundamental Computation-Communication Tradeoff Study