车辆-基础设施合作系统中的高能效自适应任务调度

IF 2.3 4区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Beipo Su, Liang Dai, Yongfeng Ju
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引用次数: 0

摘要

在车载基础设施协同系统(CVIS)中,由于计算能力的限制,车辆难以处理计算密集型的延迟敏感任务,因此将任务卸载到路侧单元(RSU)成为一种流行的做法。由于车辆任务的复杂性以及不同车辆产生的任务具有不同的延迟约束,在任务依赖性和延迟约束下最小化 RSU 的能耗具有挑战性。本文针对任务优先级划分问题,定义了任务优先级排队准则,提出了CVIS中RSU分布式任务调度问题下能量-包队列长度权衡(TSET)的任务调度策略,并建立了车速状态模型、任务模型、数据队列模型、任务计算模型和能耗模型。在李亚普诺夫优化理论对优化模型进行转换后,描述了一个knapsack问题。仿真结果验证了 TSET 降低了路侧装置的平均能耗,并确保了任务依赖性和截止日期条件下数据队列的稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Energy-efficient adaptive dependent task scheduling in cooperative vehicle-infrastructure system

Energy-efficient adaptive dependent task scheduling in cooperative vehicle-infrastructure system

In the cooperative vehicle-infrastructure system (CVIS), due to its computation limitation, vehicles are difficult to handle computing-intensive delay-sensitive tasks, so offload tasks to roadside unit (RSU) become popular. Due to the complexity of vehicles’ tasks and tasks generated by different vehicles have different delay constraints, minimize energy consumption of RSUs under task dependence and delay constraints is challenging. This paper defines the task priority queuing criterion for the task priority division problem, proposes a task scheduling strategy for energy-packet queue length tradeoff (TSET) in CVIS under RSUs distributed task scheduling problem and establishes the vehicle speed state model, task model, data queue model, task computing model and energy consumption model. After Lyapunov optimization theory transformed the optimization model, a knapsack problem was described. The simulation results verify that TSET reduces the average energy consumption of roadside units and ensures the stability of the data queue under task dependence and deadline conditions.

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来源期刊
IET Intelligent Transport Systems
IET Intelligent Transport Systems 工程技术-运输科技
CiteScore
6.50
自引率
7.40%
发文量
159
审稿时长
3 months
期刊介绍: IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf
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