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

TL;DR

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.

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.

Figures (14)

• Figure 1: A system overview of classical cloud computing (red), edge computing (yellow), and multi-tier edge computing with peer-to-peer offloading (green).
• Figure 2: An overview of M-TEC. Components in dashed boxes represent profiled data or user-supplied applications in DAG form (e.g. Lightgbm as shown in the graph). The components in the solid boxes represent the orchestration framework, in which DAG preprocessing, latency reduction, failure reduction, and ($) cost reduction are carried out.
• Figure 3: A brief overview of the offloading network. Note that there isn't a fixed initiator in the network and the role of initiator and participator can be switched. There can be multiple initiators in the offloading network.
• Figure 4: The overview of testbed setup with the TCP background traffic flow and the physical view of testbed at the cell site..
• Figure 5: DAG-based applications used in the experiments.