Mobility and Deadline-Aware Task Scheduling Mechanism for Vehicular Edge Computing

被引：14

作者：

da Costa, Joahannes B. D. ^{[1
,2
]}

de Souza, Allan M. ^{[1
]}

Meneguette, Rodolfo I. ^{[3
]}

Cerqueira, Eduardo ^{[4
]}

Rosario, Denis ^{[4
]}

Sommer, Christoph ^{[2
]}

Villas, Leandro ^{[1
]}

机构：

[1] Univ Campinas UNICAMP, Inst Comp, BR-13083852 Campinas, Brazil

[2] Tech Univ Dresden, Fac Comp Sci, D-01187 Dresden, Germany

[3] Univ Sao Paulo, Inst Math & Comp Sci, BR-13566590 Sao Carlos, Brazil

[4] Fed Univ UFPA, Inst Technol, BR-66075110 Belem, Para, Brazil

来源：

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS | 2023年 / 24卷 / 10期

基金：

巴西圣保罗研究基金会;

关键词：

Task analysis; Processor scheduling; Costs; Edge computing; Cloud computing; Vehicle dynamics; Schedules; Vehicular edge computing; task scheduling; resource prediction; recurrent neural network; RESOURCE-ALLOCATION; NETWORKS;

D O I：

10.1109/TITS.2023.3276823

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Vehicular Edge Computing (VEC) is a promising paradigm that provides cloud computing services closer to vehicular users. In VEC, vehicles and communication infrastructures can form pools with computational resources to meet vehicular services with low-latency constraints. These resource pools are known as Vehicular Cloud (VC). The usage of VC resources requires a task scheduling process. In this case, depending on its complexity, a vehicular service can be divided into different tasks. An efficient task scheduling needs to orchestrate where and for how long such tasks will run, considering the available pools, the mobility of nodes, and the tasks deadline constraints. Thus, this article proposes an efficient VC task scheduler based on an approximation heuristic and resources prediction to select the best VC for each task, called MARINA. MARINA aims to analyze the behavior of vehicles that share their computational resources with the VC and make scheduling decisions based on the mobility (VC availability) of these vehicles. Simulation results under a realistic scenario demonstrate the efficiency of MARINA compared to existing state-of-the-art mechanisms in terms of the number of tasks scheduled, monetary cost, system latency, and Central Processing Unit (CPU) utilization.

引用

页码：11345 / 11359

页数：15

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