Secure Energy-efficient Resource Allocation in Mobile Edge Computing Based on Non-Orthogonal Multiple Access
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摘要: 为提高基于非正交多址接入(NOMA)的移动边缘计算(MEC)系统中计算任务部分卸载时的安全性，该文在存在窃听者情况下研究MEC网络的物理层安全，采用保密中断概率来衡量计算卸载的保密性能，考虑发射功率约束、本地任务计算约束和保密中断概率约束，同时引入能耗权重因子以平衡传输能耗和计算能耗，最终实现系统能耗加权和最小。在满足两个用户优先级情况下，为降低系统开销，提出一种联合任务卸载和资源分配机制，通过基于二分搜索的迭代优化算法寻求问题变换后的最优解，并获得最优的任务卸载和功率分配。仿真结果表明，所提算法可有效降低系统能耗。Abstract: In order to improve the security of Non-Orthogonal Multiple Access (NOMA) based Mobile Edge Computation (MEC) system when computation tasks are partially offloading, the physical layer security of MEC network in the presence of eavesdroppers is considered, and the security interruption probability is used to measure the security performance of computation offloading. Considering the transmit power constraint, local task calculation constraint and secret outage probability constraint, and then, the energy consumption weight factor is introduced to balance the transmission energy consumption and the calculated energy consumption. After that, the sum of system weighted energy consumption is finally achieved. In the case of satisfying two user priorities, to reduce the system overhead, a joint task offloading and resource allocation mechanism is proposed to archive the optimal solution of the transformed problem through an iterative optimization algorithm based on bisection search, and the optimal computing task offloading and power allocation are obtained. Simulation results show that the proposed algorithm can effectively reduce the energy consumption of the system.
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表 1 问题P2的二等分迭代优化算法
初始化：$C_k^{{\rm{loc}}},C_k^{{\rm{ser}}},f_k^{{\rm{loc}}},f_k^{{\rm{ser}}},{\delta ^{{\rm{loc}}}},{\delta ^{{\rm{ser}}}},$ $B,T,\alpha ,\varepsilon ,{\gamma _{{\rm{BS}},k}}$, 迭代次 数$x$, ${ {{X} }_{\max } }$, $l_k^{{\rm{MIN}}} = 0$, $l_k^{{\rm{MAX}}} = 0.7{L_k}$, 精度$\tau $ (1) while $l_k^{ {\rm{max} } } - l_k^{ {\rm{min} } } \ge \tau$do 定义${l_1}{\rm{ = } }\dfrac{ {l_1^{ {\rm{min} } } + l_1^{ {\rm{max} } } }}{2}$ 根据式(21)计算${R^*_{ {\rm{s} },1} }$ 根据式(22a)计算${p^*_1}$ 根据式(17a)计算${P_{{\rm{so}},1}}$ if ${P_{ {\rm{so} },1} } \le \varepsilon$ $l_1^{{\rm{MIN}}}{\rm{ = }}{l_1}$ else $l_1^{{\rm{MAX}}}{\rm{ = }}{l_1}$ (2) until ${l_1}$满足式(7)和$x$=${ {{X} }_{\max } }$ (3) $x$=$x + 1$ (4) while $l_k^{ {\rm{max} } } - l_k^{ {\rm{min} } } \ge \tau$ do 定义${l_2}{\rm{ = } }\dfrac{ {l_2^{ {\rm{min} } } + l_2^{ {\rm{max} } } }}{2}$ 根据式(21)计算${R^*_{ {\rm{s} },2} }$ 根据式(22b)计算${p^*_2}$ 根据式(17b)计算${P_{{\rm{so}},2}}$ if $\dfrac{{C_2^{{\rm{loc}}}{l_2}}}{{f_2^{{\rm{loc}}}}} \le T$ $l_2^{ {\rm{min} } }{\rm{ = } }{l_2}$ else $l_2^{ {\rm{max} } }{\rm{ = } }{l_2}$ (5) until ${l_2}$满足式(7)和$x$=${{{X}}_{\max }}$ (6) $x$=$x + 1$ (7) end while 
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表 2 仿真参数
参数 数值 任务计算比特${L_k}$ 0.5～2.5$ \times $105 bit 计算任务所需CPU周期$C_k^{{\rm{loc}}},C_k^{{\rm{ser}}}$ 1000 cycles/bit 移动终端计算能力$f_k^{{\rm{loc}}}$ 1.415 GHz MEC服务器计算能力$f_k^{{\rm{ser}}}$ 3.3 GHz 移动终端CPU每周期能耗${\delta ^{{\rm{loc}}}}$ 1.4265$ \times $10–4 W MEC服务器CPU每周期能耗${\delta ^{{\rm{ser}}}}$ 5.6265$ \times $10–4 W 路径损耗指数$\alpha $ 4 系统最大发射功率$p_k^{\max }$ 0.1 W 能耗权重因子$\eta $ 10000 J/s 最大保密中断概率$\varepsilon $ 5% 用户$k$到基站的距离${d_{{\rm{BS}},k}}$ 60 m 用户$k$到窃听者的距离${d_{{\rm{e}},k}}$ 100 m 噪声方差$\sigma _{{\rm{BS}}}^2,\sigma _{\rm{e}}^2$ –105 dBm/Hz 系统带宽$B$ 1 MHz 时延预算$T$ 0.1 s
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