云计算平台中面向车联网应用的能耗感知调度算法

发布时间：2019-01-22 16:41

【摘要】：针对面向车联网应用的云计算平台的高能耗问题,提出一种采用节能整合策略的能耗感知调度算法——任务集整合算法(Task Set Consolidation Algorithm)。该算法的主要思想是通过减少活跃物理服务器的数目,有效降低云平台的能量消耗。建立了云平台模型、车联网任务集模型和能耗模型,确定了云平台的节能目标函数和变量因子。仿真实验通过模拟多维资源多并发任务集的云平台环境,以物理服务器的活跃时间和活跃数目、云平台的能量消耗作为性能指标,将任务集整合算法与现有算法进行了比较。实验结果表明,TSC算法能够在避免任务集资源发生冲突的情况下,使面向车联网应用的云平台激活的物理服务器数量达到最少,能耗降到最低。
[Abstract]:In order to solve the problem of high energy consumption in cloud computing platform for vehicle networking applications, this paper proposes an energy-consumption aware scheduling algorithm, (Task Set Consolidation Algorithm)., which adopts energy-saving integration strategy. The main idea of this algorithm is to reduce the energy consumption of cloud platform by reducing the number of active physical servers. The cloud platform model, vehicle networking task set model and energy consumption model are established, and the energy saving objective function and variable factors of the cloud platform are determined. By simulating the multi-dimensional resource multi-concurrent task set cloud platform environment, the paper compares the task set integration algorithm with the existing algorithm, taking the active time and active number of physical server and the energy consumption of cloud platform as performance index. The experimental results show that the TSC algorithm can minimize the number of physical servers activated by cloud platform for vehicle networking applications and reduce energy consumption to the minimum while avoiding conflicts of task set resources.
【作者单位】：西南交通大学信息科学与技术学院;计算机软件新技术国家重点实验室(南京大学);
【基金】：国家自然科学基金资助项目(61202043,61170111) 网络智能信息处理四川省高校重点实验室开放课题资助项目(SZJJ2014-049)资助
【分类号】：TP393.09

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