Security and Cost-Aware Computation Offloading via Deep Reinforcement Learning in Mobile Edge Computing
Security and Cost-Aware Computation Offloading via Deep Reinforcement Learning in Mobile Edge Computing
复制标题
通过移动边缘计算中的深度强化学习实现安全和成本感知计算卸载
DOI：
10.1155/2019/3816237
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发表时间：
2019-12
影响因子：
--
通讯作者：
Hu Haiyang
中科院分区：
文献类型：
--
作者：
Huang Binbin;Li Yangyang;Li Zhongjin;Pan Linxuan;Wang Shangguang;Xu Yunqiu;Hu Haiyang
随着移动的应用的爆炸式增长，移动的设备需要配备丰富的资源来处理海量复杂的移动的应用。然而，移动的设备通常由于其物理尺寸而受到资源约束。幸运的是，移动的边缘计算使移动的设备能够将计算任务卸载到具有丰富计算资源的边缘服务器，可以显著满足来自移动的应用的不断增长的计算需求。然而，将任务卸载到边缘服务器容易遭受外部安全威胁（例如，窥探和篡改）。针对这一问题，提出了一种面向移动的边缘计算环境中移动的用户的安全和成本感知的计算卸载（SCACO）策略，其目标是在风险概率约束下，最小化总成本（包括移动终端的能耗、处理延迟和任务丢失概率）.具体来说，我们首先制定的计算卸载问题作为一个马尔可夫决策过程（MDP）。然后，基于流行的深度强化学习方法，深度Q-网络（DQN），推导出所提出问题的最优卸载策略。最后，大量的实验结果表明，SCACO可以在移动的边缘计算环境中为移动的用户实现安全性和成本效率。
With the explosive growth of mobile applications, mobile devices need to be equipped with abundant resources to process massive and complex mobile applications. However, mobile devices are usually resource-constrained due to their physical size. Fortunately, mobile edge computing, which enables mobile devices to offload computation tasks to edge servers with abundant computing resources, can significantly meet the ever-increasing computation demands from mobile applications. Nevertheless, offloading tasks to the edge servers are liable to suffer from external security threats (e.g., snooping and alteration). Aiming at this problem, we propose a security and cost-aware computation offloading (SCACO) strategy for mobile users in mobile edge computing environment, the goal of which is to minimize the overall cost (including mobile device’s energy consumption, processing delay, and task loss probability) under the risk probability constraints. Specifically, we first formulate the computation offloading problem as a Markov decision process (MDP). Then, based on the popular deep reinforcement learning approach, deep Q-network (DQN), the optimal offloading policy for the proposed problem is derived. Finally, extensive experimental results demonstrate that SCACO can achieve the security and cost efficiency for the mobile user in the mobile edge computing environment.
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DOI：
10.1109/vtcfall.2018.8690980
发表时间：
2018-03
期刊：
2018 IEEE 88th Vehicular Technology Conference (VTC-Fall)
影响因子：
--
作者：
Xianfu Chen;Honggang Zhang;Celimuge Wu;S. Mao;Yusheng Ji;M. Bennis
通讯作者：
Xianfu Chen;Honggang Zhang;Celimuge Wu;S. Mao;Yusheng Ji;M. Bennis
DOI：
--
发表时间：
2017-11
期刊：
ArXiv
影响因子：
--
作者：
S. Ranadheera;S. Maghsudi;E. Hossain
通讯作者：
S. Ranadheera;S. Maghsudi;E. Hossain
DOI：
10.1016/j.future.2016.11.009
发表时间：
2018-01-01
影响因子：
7.5
作者：
Roman, Rodrigo;Lopez, Javier;Mambo, Masahiro
通讯作者：
Mambo, Masahiro
影响因子：
16.4
作者：
Syed Noor-ul-Hassan Shirazi;Antonios Gouglidis;Arsham Farshad;D. Hutchison
通讯作者：
Syed Noor-ul-Hassan Shirazi;Antonios Gouglidis;Arsham Farshad;D. Hutchison
异构分布式系统中优先级约束任务的新型安全驱动调度算法
影响因子：
3.7
作者：
Tang, Xiaoyong;Li, Kenli;Zeng, Zeng;Veeravalli, Bharadwaj
通讯作者：
Veeravalli, Bharadwaj