Exploiting Computation Replication for Mobile Edge Computing: A Fundamental Computation-Communication Tradeoff Study
Kuikui Li, Meixia Tao, Zhiyong Chen

TL;DR
This paper studies the fundamental tradeoff between computation replication and communication latency in mobile edge computing, proposing an asymptotic characterization of optimal upload and download times for different offloading strategies.
Contribution
It introduces an asymptotic analysis of the computation-communication tradeoff in MEC networks with replication, providing order-optimal latency pairs for various computation loads.
Findings
Increasing computation load reduces download latency inversely or linearly.
Replication creates multiple result copies enabling cooperative transmission.
Tradeoff analysis guides optimal offloading strategies for MEC systems.
Abstract
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…
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Taxonomy
TopicsIoT and Edge/Fog Computing · Age of Information Optimization · Molecular Communication and Nanonetworks
