車聯(lián)網(wǎng)中一種基于軟件定義網(wǎng)絡(luò)與移動邊緣計算的卸載策略
doi: 10.11999/JEIT190304
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重慶郵電大學(xué)通信與信息工程學(xué)院 重慶 400065
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2.
武漢大學(xué)電子信息學(xué)院 武漢 430000
An Offloading Mechanism Based on Software Defined Network and Mobile Edge Computing in Vehicular Networks
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School of Communication and Information Engineering, Chongqing University of Posts andTelecommunications, Chongqing 400065, China
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School of Electronic Information, Wuhan University, Wuhan 430000, China
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摘要:
在新興的車聯(lián)網(wǎng)絡(luò)中，汽車終端請求卸載的任務(wù)對網(wǎng)絡(luò)帶寬、卸載時延等有著更加嚴苛的需求，而新型通信網(wǎng)絡(luò)研究中移動邊緣計算(MEC)的提出更好地解決了這一挑戰(zhàn)。該文著重解決的是汽車終端進行任務(wù)卸載時卸載對象的匹配問題。文中引入了軟件定義車載網(wǎng)絡(luò)(SDN-V)對全局變量統(tǒng)一調(diào)度，實現(xiàn)了資源控制管理、設(shè)備信息采集以及任務(wù)信息分析?；谟脩羧蝿?wù)的差異化性質(zhì)，定義了重要度的模型，在此基礎(chǔ)上，通過設(shè)計任務(wù)卸載優(yōu)先級機制算法，實現(xiàn)任務(wù)優(yōu)先級劃分。針對多目標優(yōu)化模型，采用乘子法對非凸優(yōu)化模型進行求解。仿真結(jié)果表明，與其他卸載策略相比，該文所提卸載機制對時延和能耗優(yōu)化效果明顯，能夠最大程度地保證用戶的效益。
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關(guān)鍵詞:
- 車聯(lián)網(wǎng) /
- 軟件定義網(wǎng)絡(luò) /
- 移動邊緣計算 /
- 卸載機制
Abstract:In the emerging vehicular networks, the task of the car terminal requesting offloading has more stringent requirements for network bandwidth and offload delay, and the proposed Mobile Edge Computing (MEC) in the new communication network research solves better this challenge. This paper focuses on matching the offloaded objects when the car terminal performs the task offloading. By introducing the Software-Defined in-Vehicle Network (SDN-V) to schedule uniformly global variables, which realizes resource control management, device information collection and task information analysis. Based on the differentiated nature of user tasks, a model of importance is defined. On this basis, task priority is divided by designing the task to offload the priority mechanism. For the multi-objective optimization model, the non-convex optimization model is solved by the multiplier method. The simulation results show that compared with other offloading strategies, the proposed offloading mechanism has obvious effects on delay and energy consumption optimization, which can guarantee the benefit of users to the greatest extent.
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表 1 任務(wù)卸載優(yōu)先級機制
(1) 輸入：車輛$i$的請求信息為$\{ {C_i},{S_i},t_{{Q_i}}^{\max }\} $，定義$\zeta $的取值，$i \in \{ 1\; 2\; ··· \; n\} $, ${\rm{Im}}{{\rm{p}}_{\rm{i}}}{\rm{ = \{ im}}{{\rm{p}}_{\rm{1}}}{\kern 1pt} {\kern 1pt} {\rm{im}}{{\rm{p}}_{\rm{2}}}\; ···\; {\rm{im}}{{\rm{p}}_{{n}}}\; {\rm{\} }}$ (2) 輸出：降序排列的重要度${\rm{im}}{{\rm{p}}_i}$ (3) for $i = 1;i < n;i + + $ (4) 將${C_i},t_{{Q_i}}^{\max }$代入式(9)求出${\rm{im}}{{\rm{p}}_i}$ (5) ${\rm{Im}}{{\rm{p}}_{\rm{i}}}={\rm{\{ im}}{{\rm{p}}_{\rm{1}}}{\kern 1pt} {\kern 1pt} {\rm{im}}{{\rm{p}}_{\rm{2}}}{\kern 1pt} {\kern 1pt} ···\; {\rm{im}}{{\rm{p}}_{{i}}}{\rm{\} }}$ (6) for $i = 1:n$ do (7) if ${{{\rm Imp}(i) < {\rm Imp}(i + 1)}}$; ${{\rm temp} = {\rm Imp}(i + 1)}$; ${{{\rm Imp}(i + 1) = {\rm Imp}(i)}}{\kern 1pt} {\kern 1pt} {\kern 1pt} ;{{{\rm Imp}(i) = {\rm temp}}}$ (8) end 
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表 2 基于Q-學(xué)習(xí)的任務(wù)卸載策略機制
(1) 輸入：車輛$i$的請求信息$\{ {Q_i},{T_i}\} $, ${\tau _{\rm{1}}},{\tau _2},({\rm{0 < }}{\tau _{\rm{1}}} < {\tau _{\rm{2}}})$, $i \in \{ 1\; 2\; ··· \; n\} $, ${\rm{Im}}{{\rm{p}}_{{i}}}{\rm{ = \{ im}}{{\rm{p}}_{\rm{1}}}{\kern 1pt} {\kern 1pt} {\rm{im}}{{\rm{p}}_{\rm{2}}}\; ···\; {\rm{im}}{{\rm{p}}_{{i}}}{\rm{\} }}$ (2) 輸出：${x_i}$, ${\psi _i}$ (3) if ${\rm{im}}{{\rm{p}}_i} < {\tau _{\rm{1}}}$：${x_i}=0$；${\kern 1pt} {\kern 1pt} {\rm{im}}{{\rm{p}}_i} > {\tau _2}$：${x_i}{\rm{ = 1}}$ (4) elif ${\tau _{\rm{1}}} < {\rm{im}}{{\rm{p}}_i} < {\tau _{\rm{2}}}$：初始化$g$, ${x_{ij}} = 1$, $\varsigma $, $p$, $\hat Q\left( {{a_i}} \right) = 0,\; {\kern 1pt} t = 0$最大收斂時間${t_{c - \max }}$ (5) while ${\kern 1pt} t < {t_{c - \max }} + 1$：按照時延約束對車輛用戶排序 (6) for $i = 1:N\; {\kern 1pt} {\kern 1pt} $ do (7) 根據(jù)貪婪方法選擇行為${a_i}$、根據(jù)式(15)求出用戶獎勵 (8) 更新$\hat { Q}$數(shù)值矩陣通過${\hat Q_{t + 1}}\left( {s,a} \right) \leftarrow \left( {1 - \varsigma } \right){\hat Q_t}\left( {s,a} \right) + \varsigma \left( {g + \eta \mathop {\max }\limits_{a'} {{\hat Q}_t}\left( {s',a'} \right)} \right)$, $p \leftarrow \left( {p/\sqrt t } \right)$ (9) end for；$t = t + 1$；end while (10) 利用${\psi _i}$更新目標優(yōu)化式(7) (11) end
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表 3 模擬參數(shù)表
參數(shù) 數(shù)值 計算任務(wù)${Q_i}$ 1～50 MB 傳輸帶寬$W$ 100 MHz 汽車用戶發(fā)射功率${p_i}$ 0.2 W 任務(wù)所需CPU周期數(shù)${C_i}$ 0.1～1 GHz MEC服務(wù)器CPU周期頻率${f_{\rm b}}$ 6 GHz 車輛用戶的CPU周期頻率${f_v}$ 0.5～1 GHz 高斯噪聲${\sigma ^2}$ –100 dBm 信道傳輸距離${d_{mn}}$ 5～500 m 汽車CPU能耗功率系數(shù)${p_{{v} } }$ 80 W/GHz 電池最大容量 20 kWh
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