论文标题
在启用车辆云计算的软件定义的IOV中，能源感知的图形作业分配
Energy-aware Allocation of Graph Jobs in Vehicular Cloud Computing-enabled Software-defined IoV
论文作者
论文摘要
软件定义的车辆互联网（SDIOV）已成为一个有前途的范式，以实现灵活而全面的资源管理，以实现下一代汽车运输系统。在本文中，研究了一个基于车辆云计算的SDIOV框架，其中传输功率和图形作业的联合分配被称为非线性整数编程问题。为了有效解决该问题，提出了一种基于结构保护的两阶段分配方案，它将模板搜索搜索的电源分配。具体而言，通过识别图形作业和服务提供商的组件之间的潜在映射（模板），在第一阶段应用了基于层次树的随机子图机制。在第二阶段采用了基于结构的基于模拟退火的电源分配算法，以实现工作完成时间和能源消耗之间的权衡。进行了广泛的模拟以验证所提出的算法的性能。
Software-defined internet of vehicles (SDIoV) has emerged as a promising paradigm to realize flexible and comprehensive resource management, for next generation automobile transportation systems. In this paper, a vehicular cloud computing-based SDIoV framework is studied wherein the joint allocation of transmission power and graph job is formulated as a nonlinear integer programming problem. To effectively address the problem, a structure-preservation-based two-stage allocation scheme is proposed that decouples template searching from power allocation. Specifically, a hierarchical tree-based random subgraph isomorphism mechanism is applied in the first stage by identifying potential mappings (templates) between the components of graph jobs and service providers. A structure-preserving simulated annealing-based power allocation algorithm is adopted in the second stage to achieve the trade-off between the job completion time and energy consumption. Extensive simulations are conducted to verify the performance of the proposed algorithms.
