Online Energy-efficient Scheduling Algorithm for Renewable Energy-powered Roadside units in VANETs

Vivek Sethi, Sujata Pal, Avani Vyas
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引用次数: 3

Abstract

Road-side unit (RSU) plays an important role in providing connectivity among the vehicles on the road. In rural areas, RSUs are powered using renewable energy, such as solar or wind energy. Hence, the energy consumption across such RSUs should be efficient i.e., energy consumption at RSUs should be minimized and no RSU gets over-utilized while others are under-utilized. The amount of energy consumption depends upon the scheduling of different kinds of data requests at RSU. In this paper, we propose a scheduling architecture for minimizing energy consumption at RSU and attaining uniform energy consumption across neighboring RSUs. This, in turn, increases the request fulfillment percentage at RSUs. The proposed architecture categorizes the incoming request as a Traditional (less computation) or a Smart request (high computation). Two approaches- Hard-deadline Less Computation requirement Approach (HLCA) and Soft-deadline High Computation requirement Approach (SHCA) are proposed for addressing Traditional and Smart data requests, respectively. In HLCA approach, the receiving RSU uses the scheduling metric to select the servicing RSU for request fulfillment. We prove by analysis, how scheduling metric helps in minimizing and achieving uniform energy consumption across the RSUs. In SHCA approach, Fog computing is used for handling high computation requests. Energy consumption at RSUs is further optimized by using Auction game-based relay vehicle selection mechanism. Simulation results demonstrate that our proposed approaches achieve uniform energy consumption across multiple RSUs and 10% more efficient than scheduling algorithms for single RSU model such as Nearest Fastest Set Scheduler (NFS).
VANETs中可再生能源驱动的路边装置在线节能调度算法
道路侧单元(RSU)在提供道路上车辆之间的连接方面发挥着重要作用。在农村地区,rsu使用可再生能源供电,如太阳能或风能。因此,这些RSU之间的能量消耗应该是有效的,即RSU的能量消耗应该最小化,并且没有RSU被过度利用而其他RSU被充分利用。能源消耗的数量取决于RSU中不同类型数据请求的调度。在本文中,我们提出了一种最小化RSU能耗和实现相邻RSU能耗统一的调度架构。这反过来又增加了rsu的请求实现百分比。提出的体系结构将传入请求分为传统请求(计算量少)和智能请求(计算量高)。针对传统数据请求和智能数据请求,分别提出了两种解决方法——硬截止日期计算需求少方法(HLCA)和软截止日期计算需求高方法(SHCA)。在HLCA方法中,接收RSU使用调度度量来选择服务RSU来实现请求。通过分析,我们证明了调度度量如何帮助最小化和实现跨rsu的统一能耗。在SHCA方法中,雾计算用于处理高计算请求。采用基于Auction游戏的中继车辆选择机制,进一步优化了中继车辆的能耗。仿真结果表明,该方法实现了跨多个RSU的均匀能耗,比针对单个RSU模型的调度算法(如最近最快集调度算法(NFS))效率提高10%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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