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移动边缘计算任务卸载和基站关联协同决策问题研究

于博文, 蒲凌君, 谢玉婷, 徐敬东, 张建忠

于博文, 蒲凌君, 谢玉婷, 徐敬东, 张建忠. 移动边缘计算任务卸载和基站关联协同决策问题研究[J]. 计算机研究与发展, 2018, 55(3): 537-550. DOI: 10.7544/issn1000-1239.2018.20170714
引用本文: 于博文, 蒲凌君, 谢玉婷, 徐敬东, 张建忠. 移动边缘计算任务卸载和基站关联协同决策问题研究[J]. 计算机研究与发展, 2018, 55(3): 537-550. DOI: 10.7544/issn1000-1239.2018.20170714
Yu Bowen, Pu Lingjun, Xie Yuting, Xu Jingdong, Zhang Jianzhong. Joint Task Offloading and Base Station Association in Mobile Edge Computing[J]. Journal of Computer Research and Development, 2018, 55(3): 537-550. DOI: 10.7544/issn1000-1239.2018.20170714
Citation: Yu Bowen, Pu Lingjun, Xie Yuting, Xu Jingdong, Zhang Jianzhong. Joint Task Offloading and Base Station Association in Mobile Edge Computing[J]. Journal of Computer Research and Development, 2018, 55(3): 537-550. DOI: 10.7544/issn1000-1239.2018.20170714
于博文, 蒲凌君, 谢玉婷, 徐敬东, 张建忠. 移动边缘计算任务卸载和基站关联协同决策问题研究[J]. 计算机研究与发展, 2018, 55(3): 537-550. CSTR: 32373.14.issn1000-1239.2018.20170714
引用本文: 于博文, 蒲凌君, 谢玉婷, 徐敬东, 张建忠. 移动边缘计算任务卸载和基站关联协同决策问题研究[J]. 计算机研究与发展, 2018, 55(3): 537-550. CSTR: 32373.14.issn1000-1239.2018.20170714
Yu Bowen, Pu Lingjun, Xie Yuting, Xu Jingdong, Zhang Jianzhong. Joint Task Offloading and Base Station Association in Mobile Edge Computing[J]. Journal of Computer Research and Development, 2018, 55(3): 537-550. CSTR: 32373.14.issn1000-1239.2018.20170714
Citation: Yu Bowen, Pu Lingjun, Xie Yuting, Xu Jingdong, Zhang Jianzhong. Joint Task Offloading and Base Station Association in Mobile Edge Computing[J]. Journal of Computer Research and Development, 2018, 55(3): 537-550. CSTR: 32373.14.issn1000-1239.2018.20170714

移动边缘计算任务卸载和基站关联协同决策问题研究

基金项目: 国家自然科学基金项目(61702287,61702288);天津市自然科学基金项目(16JCQNJC00700);南开大学基础科研业务项目(070-63171112)
详细信息
  • 中图分类号: TP393.1

Joint Task Offloading and Base Station Association in Mobile Edge Computing

  • 摘要: 为了缩小IoT应用的服务质量要求与IoT设备有限的计算资源之间的差距,提高设备与基站能源利用率,设计了基于超密集网络的移动边缘计算框架COMED,提出了一个结合任务卸载、设备-基站关联以及基站睡眠调度的在线优化问题,旨在最小化设备和基站的整体能量消耗,同时满足IoT应用的服务质量要求.针对这一在线优化问题,提出了一个基于李雅普诺夫优化理论的任务调度算法JOSA,该算法只使用当前时间片的系统信息进行调度.仿真实验证明了COMED框架具有良好的性能:1)与设备本地处理相比,系统整体节能30%以上,与DualControl算法相比平均节能10%~50%;2)算法的执行时间与IoT设备数量呈近似线性的关系.
    Abstract: In order to narrow the gap between the requirements of IoT applications and the restricted resources of IoT devices and achieve devices energy efficiency, in this paper we design COMED, a novel mobile edge computing framework in ultra-dense mobile network. In this context, we propose an online optimization problem by jointly taking task offloading, base station (BS) sleeping and device-BS association into account, which aims to minimize the total energy consumption of both devicesand BSs, and meanwhile satisfies applications’ QoS. To tackle this problem, we devise an online Lyapunov-based algorithm JOSA by exploiting the system information in the current time slot only. As the core component of this algorithm, we resort to the loose-duality framework and propose an optimal joint task offloading, BS sleeping and device-BS association policy for each time slot. Extensive simulation results corroborate that the COMED framework is of great performance: 1) more than 30% energy saving compared with local computing, and on average 10%-50% energy saving compared with the state-of-the-art algorithm DualControl (i.e., energy-efficiency); 2) the algorithm running time is approximately linear proportion to the number of devices (i.e., scalability).
  • 期刊类型引用(2)

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出版历程
  • 发布日期:  2018-02-28

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