...
首页> 外文期刊>IEEE Transactions on Intelligent Transportation Systems >An Energy Aware Offloading Scheme for Interdependent Applications in Software-Defined IoV With Fog Computing Architecture
【24h】

An Energy Aware Offloading Scheme for Interdependent Applications in Software-Defined IoV With Fog Computing Architecture

机译:具有雾计算架构软件定义IOV中的相互依存应用的能量识别卸载方案

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

The Internet of Vehicles (IoV) is one important application scenarios for the development of the Internet of things. The software-defined network (SDN) and fog computing could effectively improve the IoV network dynamics, which enables the application to achieve better performance by offloading some tasks to fog node or cloud center. Current computation offloading approaches for IoV and fog computing mostly focus on resource utilization. However, the energy-aware offloading has not been adequately addressed, especially for IoV systems with many battery-powered roadside units (RSU) and electric vehicles (EV). In this paper, we study the offloading problem in SDN and fog computing-based IoV systems. An energy-aware dynamic offloading scheme is proposed to prolong the running time of the IoV system by leveraging available battery power to execute more applications. The remaining battery power is defined as a dynamic weight factor in the execution cost model to adjust the optimization objective. Meanwhile, the dependence between applications is also taken into consideration in the cost model. A heuristic optimization algorithm is designed to solve the optimization problem. We conducted comprehensive experiments and results have shown that the offloading scheme could execute more applications with the available battery power under the constraints of application dependence.
机译:车辆互联网(IOV)是用于开发事物互联网的重要应用场景。软件定义的网络(SDN)和FOG计算可以有效地提高IOV网络动态,这使得应用程序通过将一些任务卸载到雾节点或云中心来实现更好的性能。 IOV和FOG计算的当前计算卸载方法主要关注资源利用率。然而,能量感知的卸载尚未得到充分解决,特别是对于具有许多电池供电的路边单元(RSU)和电动车辆(EV)的IOV系统。在本文中,我们研究了基于SDN和FOG计算的IOV系统的卸载问题。提出了一种能量感知动态卸载方案来延长IOV系统的运行时间,利用可用的电池电源来执行更多应用程序。剩余的电池电量被定义为执行成本模型中的动态权重因因子,以调整优化目标。同时,在成本模型中也考虑了应用之间的依赖性。启发式优化算法旨在解决优化问题。我们进行了全面的实验,结果表明,根据应用依赖的约束,卸载方案可以在可用电池功率下执行更多应用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号