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Energy Efficient Software Matching in Vehicular Fog

机译:车辆雾中的节能软件匹配

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Along with the development of Internet of Things (IoT) and the rise of fog computing, more new joint technologies have been proposed. Vehicular Ad-hoc Networks (VANET) are one of the emergent technologies that come with a very promising role, where the spare processing capabilities of vehicles can be exploited. In this paper, we propose a fog architecture to provide services for end users based on a cluster of static vehicles in a parking lot referred to as a vehicular fog. The proposed vehicular fog architecture is connected to the central data center through an optical infrastructure. As the processing requests from users require specific software packages that may not be available in all vehicles, we study the software matching problem of task assignments in vehicular fog. The goal of this paper is to examine the effect of software packages variety in vehicles on the assignment decision and the overall power consumption. A mixed integer linear programming (MILP) model was utilized to optimize the power consumption of the overall architecture, considering different numbers of software packages in the vehicular fog. The results reveal a power saving of up to 27% when vehicles are uploaded with four or more different software packages out of a library of ten software packages in this example. Keywords: vehicular fog; software matching, power consumption; Mixed Integer Linear Programming (MILP).
机译:随着物联网(IoT)的发展和雾计算的兴起,提出了更多新的联合技术。车载自组织网络(VANET)是一种新兴技术,具有非常有前途的作用,可以利用车辆的备用处理能力。在本文中,我们提出了一种雾化架构,该雾化架构基于称为停车场雾化的停车场中的一组静态车辆,为最终用户提供服务。拟议的车辆雾架构通过光学基础架构连接到中央数据中心。由于用户的处理要求需要特定的软件包,而某些软件包可能无法在所有车辆中使用,因此我们研究了车辆雾中任务分配的软件匹配问题。本文的目的是研究车辆中各种软件包对分配决策和总体功耗的影响。考虑到车辆雾中不同数量的软件包,使用了混合整数线性规划(MILP)模型来优化整个体系结构的功耗。结果显示,在此示例中,使用包含十个软件包的库中的四个或更多个不同的软件包上载车辆时,可节省多达27%的电能。关键词:车辆雾软件配套,功耗低;混合整数线性规划(MILP)。

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