Linear Network Coded Computation in Mobile Edge Computing

Abstract

Mobile edge computing (MEC) enables feasible and scalable computation services for delay-sensitive and delay-tolerant tasks from mobile users. This paper considers an MEC network that consists of multiple users, multiple edge nodes (ENs), and a remote cloud computing server, where the ENs and the cloud server execute the delay-sensitive and delay-tolerant tasks respectively. First, we propose a unified linear network coded (NC) task offloading policy at the ENs to either execute the delay-sensitive tasks or assist the cloud server in the execution of delay-tolerant tasks. For the delay-sensitive task, the users jointly precode their task input messages according to a signal space alignment pattern, such that each EN can compute the linear NC messages for its intended user. For the delay-tolerant task, we put forth a compute-and-upload strategy for the ENs to upload their computed NC messages to the cloud server, such that the cloud server can first recover the input messages from all users and then execute the computation. Second, we develop the EN computation rules for different types of tasks. Finally, we characterize the computation load and normalized uploading time for the proposed task offloading. Our analytical results show that the proposed task offloading scheme is applicable to different NC computation with flexible requirements on computation load and uploading time.