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Future Communications and Energy Management in the Internet of Vehicles: Toward Intelligent Energy-Harvesting

机译:车联网中的未来通信和能源管理:迈向智能能源收集

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摘要

As an emerging communication platform in the Internet of Things, IoV is promising to pave the way for the establishment of smart cities and provide support for various kinds of applications and services. Energy management in IoV has been attracting an upsurge of interest in both academia and industry. Currently, green IoV mainly focuses on two aspects: energy management of battery-enabled RSUs and EVs. However, these two issues are always resolved separately while ignoring their interactions. This standalone design may cause energy underutilization, a mismatch between traffic demands and energy supplies, as well as high deployment and sustainable costs for RSUs. Therefore, the integration of energy management between battery- enabled RSUs and EVs calls for comprehensive investigation. This article first provides an overview of several promising research fields for energy management in green IoV systems. Given the significance of efficient communications and energy management, we construct an intelligent energy-harvesting framework based on V2I communications in green IoV communication systems. Specifically, we develop a three-stage Stackelberg game to maximize the utilities of both RSUs and EVs in V2I communications. After that, a real-world trajectory-based performance evaluation is provided to demonstrate the effectiveness of our scheme. Finally, we identify and discuss some research challenges and open issues for energy management in green IoV systems.vehicular wireless networks and services have witnessed great advancements in both technology and management capabilities. Vehicular networks commenced as simple ad hoc networks with node-to-node communication capabilities. Today, vehicular networks not only provide sophisticated vehicle-to-vehicle communication, but also make use of state-of-the-art cloud and fog computing frameworks to deliver composite vehicular services and provide energy-efficient service delivery mechanisms. Fog and mobile edge computing spread communication, storage, and computing resources all over the wireless access network, thus providing greater resource and service access to resource- and energy-limited wireless and mobile devices such as smart vehicles. This article envisions a smart city solution that considers collaboration among vehicular and mobile nodes to provide a more energy-efficient service delivery mechanism. Different solutions are examined that consider cloud and fog entities used to deliver continuous and stable simple and complex services for both current and future vehicular node service requests. One of the considered energy-efficient solutions forms clusters of both vehicular and mobile nodes according to their service, energy, and movement characteristics. We show that this solution can further be enhanced using node collaboration to negotiate for optimal services according to users' quality of experience parameter configurations. We compare four different solutions using simulation tests to identify the ones with adequate service delivery guarantees and energy consumption.
机译:作为物联网中新兴的通信平台,IoV有望为建立智慧城市铺平道路,并为各种应用程序和服务提供支持。 IoV中的能源管理一直引起学术界和工业界的关注。目前,绿色IoV主要集中在两个方面:电池供电的RSU和EV的能量管理。但是,这两个问题总是在忽略它们的相互作用的同时单独解决。这种独立的设计可能会导致能源利用不足,交通需求与能源供应不匹配以及RSU的高部署和可持续成本。因此,将电池供电的RSU和EV之间的能源管理集成在一起需要进行全面的调查。本文首先概述了绿色IoV系统中能源管理的几个有前途的研究领域。考虑到有效通信和能源管理的重要性,我们在绿色IoV通信系统中构建了基于V2I通信的智能能源收集框架。具体来说,我们开发了一个三阶段Stackelberg游戏,以最大化V2I通信中RSU和EV的效用。此后,提供了基于真实轨迹的性能评估,以证明我们的方案的有效性。最后,我们确定并讨论了绿色IoV系统中能源管理的一些研究挑战和未解决的问题。车载无线网络和服务在技术和管理能力上都取得了长足的进步。车载网络起初是具有节点到节点通信功能的简单自组织网络。如今,车载网络不仅提供复杂的车对车通信,而且还利用最新的云和雾计算框架来交付复合车服务并提供节能服务交付机制。雾和移动边缘计算将通信,存储和计算资源分布在整个无线访问网络上,从而为资源和能源受限的无线和移动设备(例如智能车辆)提供更大的资源和服务访问权限。本文设想了一种智能城市解决方案,该解决方案考虑了车辆和移动节点之间的协作以提供更节能的服务交付机制。研究了考虑云和雾实体的不同解决方案,这些实体用于为当前和将来的车辆节点服务请求提供连续,稳定的简单和复杂服务。一种被认为是高能效的解决方案根据其服务,能量和运动特性形成了车辆和移动节点的集群。我们显示,可以根据用户的体验质量参数配置,使用节点协作来协商最佳服务,从而进一步增强此解决方案。我们使用模拟测试比较了四种不同的解决方案,以识别具有足够服务交付保证和能源消耗的解决方案。

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  • 来源
    《IEEE Wireless Communications》 |2019年第6期|87-93|共7页
  • 作者

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    Lanzhou Univ Lanzhou Gansu Peoples R China|Dalian Univ Technol Dalian Peoples R China;

    Lanzhou Univ Lanzhou Gansu Peoples R China|Dalian Univ Technol Dalian Peoples R China|Chongqing Univ Posts & Telecommun Chongqing Peoples R China;

    Lanzhou Univ Lanzhou Gansu Peoples R China|Chinese Acad Sci Beijing Peoples R China;

    Dalian Univ Technol Sch Software Dalian Peoples R China;

    Chongqing Univ Posts & Telecommun Chongqing Peoples R China;

    Lanzhou Univ Lanzhou Gansu Peoples R China;

    Chinese Acad Sci Beijing Peoples R China;

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