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

Fuente: arXiv
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Main Authors: Li, Xiang, Abdallah, Mustafa, Lou, Yuan-Yao, Chiang, Mung, Kim, Kwang Taik, Bagchi, Saurabh
Format: Preprint
Published: 2024
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author Li, Xiang
Abdallah, Mustafa
Lou, Yuan-Yao
Chiang, Mung
Kim, Kwang Taik
Bagchi, Saurabh
author_facet Li, Xiang
Abdallah, Mustafa
Lou, Yuan-Yao
Chiang, Mung
Kim, Kwang Taik
Bagchi, Saurabh
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2409_10839
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Dynamic DAG-Application Scheduling for Multi-Tier Edge Computing in Heterogeneous Networks
Li, Xiang
Abdallah, Mustafa
Lou, Yuan-Yao
Chiang, Mung
Kim, Kwang Taik
Bagchi, Saurabh
Networking and Internet Architecture
Distributed, Parallel, and Cluster Computing
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.
title Dynamic DAG-Application Scheduling for Multi-Tier Edge Computing in Heterogeneous Networks
topic Networking and Internet Architecture
Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2409.10839