# HetMEC: Latency-optimal Task Assignment and Resource Allocation for Heterogeneous Mobile Edge Computing

## TL;DR

This paper introduces HetMEC, a multi-layer mobile edge computing framework that optimizes task assignment and resource allocation to minimize latency and improve processing efficiency for computation-intensive tasks.

## Contribution

The paper proposes a novel HetMEC architecture with joint task and resource management algorithms to reduce latency in heterogeneous MEC environments.

## Key findings

- Achieves lower latency compared to conventional MEC schemes.
- Increases processing rate for computation-intensive tasks.
- Demonstrates effectiveness through simulation results.

## Abstract

Driven by great demands on low-latency services of the edge devices (EDs), mobile edge computing (MEC) has been proposed to enable the computing capacities at the edge of the radio access network. However, conventional MEC servers suffer disadvantages such as limited computing capacity, preventing the computation-intensive tasks to be processed in time. To relief this issue, we propose the heterogeneous MEC (HetMEC) where the data that cannot be timely processed at the edge are allowed be offloaded to the upper-layer MEC servers, and finally to the cloud center (CC) with more powerful computing capacity. We design the latency minimization algorithm by jointly coordinating the task assignment, computing and transmission resources among the EDs, multi-layer MEC servers, and the CC. Simulation results indicate that our proposed algorithm can achieve a lower latency and higher processing rate than the conventional MEC scheme.