Dynamic DAG-Application Scheduling for Multi-Tier Edge Computing in Heterogeneous Networks

TL;DR

This paper introduces M-TEC, a multi-tier edge computing framework that optimizes latency, failure probability, and cost by considering the sporadic failure of personal devices and dynamic network conditions, demonstrated through real-world experiments.

Contribution

The paper presents a novel multi-tier edge computing framework, M-TEC, that accounts for device failures and network variability to improve application performance and reliability.

Findings

M-TEC reduces end-to-end latency by at least 8% compared to baselines.

M-TEC maintains reliable performance under diverse network conditions.

The framework effectively balances latency, failure probability, and cost.

Abstract

Edge computing is deemed a promising technique to execute latency-sensitive applications by offloading computation-intensive tasks to edge servers. Extensive research has been conducted in the field of end-device to edge server task offloading for several goals, including latency minimization, energy optimization, and resource optimization. However, few of them consider our mobile computing devices (smartphones, tablets, and laptops) to be edge devices. In this paper, we propose a novel multi-tier edge computing framework, which we refer to as M-TEC, that aims to optimize latency, reduce the probability of failure, and optimize cost while accounting for the sporadic failure of personally owned devices and the changing network conditions. We conduct experiments with a real testbed and a real commercial CBRS 4G network, and the results indicate that M-TEC is capable of reducing the end-to-end latency of applications by at least 8\% compared to the best baseline under a variety of network conditions, while providing reliable performance at an affordable cost.