| 移动Ad Hoc云中任务卸载的联合优化策略 |
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| 引用本文： | 胡杨,韩嘉伟,张志红,李军,刘畅,曾祥豹,李小飞,王音心.移动Ad Hoc云中任务卸载的联合优化策略[J].压电与声光,2019,41(3):459-464. |
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| 作者姓名： | 胡杨 韩嘉伟 张志红 李军 刘畅 曾祥豹 李小飞 王音心 |
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| 作者单位： | (1.中电科技集团重庆声光电有限公司，重庆 401332；2.中国电子科技集团公司第二十六研究所，重庆 400060；
3.重庆邮电大学 移动通信技术重庆市重点实验室，重庆 400065) |
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| 基金项目： | 重庆市科技重大主题专项集成电路产业基金资助项目（cstc2018jszx cyztzxX0001）；重庆市教委科学技术研究基金资助项目（KJQN201800642）；重庆市科技创新领军人才基金资助项目（cstc2018kjcxljrc0084）；重庆市重点产业共性关键技术创新专项基金资助（cstc2017zdcy zdyf0607） |
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| 摘 要： | 为了降低移动Ad Hoc云中客户端卸载计算密集型任务过程中产生的计算能耗、传输能耗和任务时延,该文提出了一种联合优化算法。该算法首先基于计算能耗、通信能耗及任务时延进行建模;然后进行预估计,以选择更优的代理终端,并由此降低总的系统能耗与任务时延。仿真结果表明,相对于传统云算法,该算法在系统能耗和任务时延两方面均有显著提升。
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| 关 键 词： | 移动Ad Hoc云 系统能耗 任务时延 卸载策略 |
Joint Optimization Strategy for Task Offloading in Mobile Ad Hoc Cloud |
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| HU Yang,HAN Jiawei,ZHANG Zhihong,LI Jun,LIU Chang,ZENG Xiangbao,LI Xiaofei,WANG Yinxin.Joint Optimization Strategy for Task Offloading in Mobile Ad Hoc Cloud[J].Piezoelectrics & Acoustooptics,2019,41(3):459-464. |
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| Authors: | HU Yang HAN Jiawei ZHANG Zhihong LI Jun LIU Chang ZENG Xiangbao LI Xiaofei WANG Yinxin |
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| Affiliation: | (1. Chongqing Acoustic Optic Electronic Co. Ltd, China Electronics Technology Group, Chongqing 401332,China;
2.The 26th Institute of China Electronics Technology Group Corporation, Chongqing 400060, China;
3. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China) |
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| Abstract: | In order to reduce the computational energy consumption, transmission energy consumption and task delay generated in the process of computing intensive tasks offloaded by the clients in mobile Ad Hoc cloud, a joint optimization algorithm is proposed in this paper. Firstly, the algorithm model is established based on the computational energy consumption, communication energy consumption and task delay. Then, the algorithm is pre estimated to select a better proxy terminal, thereby reducing the total system energy consumption and task delay. The simulation results show that compared with the traditional cloud computing algorithm, the proposed algorithm has significant improvement in both system energy consumption and task delay. |
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| Keywords: | mobile Ad Hoc cloud system energy consumption task delay offloading strategy |
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