面向可靠性的5G網(wǎng)絡(luò)切片重構(gòu)及映射算法

趙國繁; 唐倫; 胡彥娟; 趙培培; 陳前斌

doi:10.11999/JEIT190500

面向可靠性的5G網(wǎng)絡(luò)切片重構(gòu)及映射算法

doi: 10.11999/JEIT190500 cstr: 32379.14.JEIT190500

1.
重慶郵電大學(xué)通信與信息工程學(xué)院重慶 400065
2.
重慶郵電大學(xué)移動通信技術(shù)重點實驗室重慶 400065

基金項目: 國家自然科學(xué)基金(61571073)，重慶市教委科學(xué)技術(shù)研究項目(KJZD-M201800601)

詳細信息

作者簡介:
趙國繁：女，1993年生，碩士，研究方向為5G網(wǎng)絡(luò)切片中的資源分配，可靠性

唐倫：男，1973年生，教授，博士生導(dǎo)師，研究方向為新一代無線通信網(wǎng)絡(luò)、異構(gòu)蜂窩網(wǎng)絡(luò)、軟件定義無線網(wǎng)絡(luò)等

胡彥娟：女，1993年生，碩士生，研究方向為網(wǎng)絡(luò)切片的映射與資源分配

趙培培：女，1993年生，碩士生，研究方向為5G網(wǎng)絡(luò)切片、網(wǎng)絡(luò)虛擬化

陳前斌：男，1967年生，教授，博士生導(dǎo)師，主要研究方向為個人通信、多媒體信息處理與傳輸、下一代移動通信網(wǎng)絡(luò)、異構(gòu)蜂窩網(wǎng)絡(luò)等

通訊作者:
趙國繁　1349366355@qq.com

中圖分類號: TN929.5
計量
- 文章訪問數(shù): 3870
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2019-07-04
- 修回日期: 2020-02-16
- 網(wǎng)絡(luò)出版日期: 2020-03-11
- 刊出日期: 2020-06-22

A Reliability-aware 5G Network Slice Reconfiguration and Embedding Algorithm

1.
School of Communication and Information Engineering, Chongqing University of Post and Telecommunications, Chongqing 400065, China
2.
Key Laboratory of Mobile Communication Technology, Chongqing University of Post and Telecommunications, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (61571073), The Science and Technology Research Program of Chongqing Municipal Education Commission (KJZD-M201800601)

摘要

摘要:
針對傳統(tǒng)網(wǎng)絡(luò)切片映射方法資源利用率低且可靠性差的問題，該文提出了可靠性感知的網(wǎng)絡(luò)切片(NS)重構(gòu)及映射策略(RNSRE)。首先，建立了面向可靠性和資源的網(wǎng)絡(luò)切片可靠映射效用函數(shù)。其次，綜合考慮虛擬網(wǎng)絡(luò)功能(VNF)的資源需求和位置約束，提出了一種VNF可靠性需求的度量方法。在此基礎(chǔ)上，以最大化VNF可靠部署收益的同時最小化鏈路帶寬資源開銷為目標，建立了切片可靠映射整數(shù)線性規(guī)劃模型。最后，針對不同的網(wǎng)絡(luò)切片類型，提出了基于鄰域搜索的網(wǎng)絡(luò)切片映射算法和關(guān)鍵VNF備份的網(wǎng)絡(luò)切片重構(gòu)映射算法。仿真結(jié)果表明，所提算法在滿足VNF可靠性需求的同時，提高了資源利用率，降低了映射的開銷。
- 5G網(wǎng)絡(luò)切片 /
- 可靠映射 /
- 資源利用率
Abstract:
Considering the problems of low resource utilization and poor reliability of traditional network slice embedding, a Reliability-aware Network Slice (NS) Reconfiguration and Embedding (RNSRE) strategy is proposed. Firstly, a utility function of reliable embedding oriented reliability and available resources is established. Then, considering the resource requirements and the location constraints of Virtual Network Function (VNF), a method is proposed to quantify the reliability requirement of VNF. Based on the above works, the reliable network slice embedding problem is formulated as an integer linear programming which maximizes the profits of reliable VNF deployment while minimizing the consumption of link bandwidth resource. Finally, according to different types of network slices, a network slice reliable embedding algorithm based on neighborhood search and a network slice reconfiguration embedding algorithm based on key VNF backup are proposed. Simulation results show that the proposed algorithms improve the resources utilization and reduce the embedding cost while meeting the reliability of VNF.
- 5G Network Slice (NS) /
- Reliable embedding /
- Resource utilization

HTML全文

圖 1 5G網(wǎng)絡(luò)切片場景

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圖 2 不同算法平均成本比較

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圖 3 所提算法與3種算法的平均物理節(jié)點、鏈路資源利用率累計分布函數(shù)

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圖 4 不同算法NSR平均接受率比較

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圖 5 不同算法到達的可靠性比較

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表 1 基于鄰域搜索的網(wǎng)絡(luò)切片映射算法

輸入：NSR $G_v^{\rm{g}} = (V_{\rm{g}},E_{\rm{g}},R_{{\rm{req}}}^{\rm{g}})$，物理網(wǎng)絡(luò)${G_{\rm{s}}} = \left( {{N_{\rm{s}}},{L_{\rm{s}}}} \right)$	(5)　　　　${P_i} = P_{{\rm{next}}}^{\rm{g}}$, ${R_{{\rm{gap}}}} = \displaystyle\prod\limits_{{n_i} \in P_{{\rm{next}}}^{\rm{g}}} {{R_i}} - R_{{\rm{req}}}^{\rm{g}}$
輸出：NSE方案${P^{\rm{g}}} = \left[ {P^{\rm{g}}\left( {{v_k}} \right),P^{\rm{g}}\left( {{e_k}} \right)} \right]$	(6)　　　　計算當前的帶寬消耗為${b_{\rm{g}}}$
(1) 搜索空間$S$, $P_{{\rm{opt}}}^{\rm{g}} = {P_{{\rm{init}}}}$; ${P_i} = P_{{\rm{init}}}^{\rm{g}}$	(7)　　　end if
(2) while($0.5 \le { { {R_{ {\rm{gap} } } }} / { {R_{ {\rm{req} } } } } } + { {\left( { {b^{\rm{g} } } - b_{ {\rm{req} } }^{\rm{g} } } \right)} / {b_{ {\rm{req} } }^{\rm{g} } } } \le 1$), do	(8)　　　if $\left( {{\rm Obj}\left( {P_{ {\rm{next} } }^{\rm{g} } } \right) < {\rm Obj}\left( {P_{ {\rm{opt} } }^{\rm{g} } } \right)} \right)$ then
(3)　　　在${P_i}$的鄰域解中搜索當前更優(yōu)的個體$P_{{\rm{next}}}^{\rm{g}}$	(9)　　　　$P_{{\rm{opt}}}^{\rm{g}} = P_{{\rm{next}}}^{\rm{g}}$
(4)　　　if $\displaystyle\prod\limits_{ {n_i} \in P_{ {\rm{next} } }^{\rm{g} } } { {R_i} } \ge R_{ {\rm{req} } }^{\rm{g} }$ then	(10)　　　end if
	(11)　end while

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表 2 關(guān)鍵VNF備份網(wǎng)絡(luò)切片重構(gòu)算法

輸入：NSR $G_v^{\rm{g}} = (V_{\rm{g}},E_{\rm{g}})$，備份節(jié)點集${V_{{\rm{reconf}}}}$
輸出：${P^{\rm{g}}} = \left[ {P_{}^{\rm{g}}\left( {{v_k}} \right),P_{}^{\rm{g}}\left( {{e_k}} \right)} \right]$
(1) for each $v_i^{\rm{g}} \in {V_{{\rm{reconf}}}}$
(2)　專有備份節(jié)點$v_i^b$, $C_k^b = C_i^{\rm{g}}$，
(3)　備份鏈路
(4)　基于式(23)得到$R\left( {G_{{\rm{backup}}}^{\rm{g}}} \right)$
(5) end for
(6) while($R\left( {G_{ {\rm{backup} } }^{\rm{g} } } \right) \le R_{ {\rm{req} } }^{\rm{g} }$), do
(7)　　for all $v_k^{\rm{g}} \in {V_{\rm{g}}}$, do
(8)　　　按照VNF可靠性遞增，對節(jié)點進行排序

(9)　　　選擇相鄰VNF對提供共享備份節(jié)點$v_i^b$, $C_k^b = \max \left\{ {C_i^{\rm g} ,C_j^{\rm{g}}} \right\}$
(10)　　　選擇關(guān)鍵VNF對$v_i^{\rm{g}},v_j^{\rm{g}} = {\rm{arg}}\;{\rm{max}}\left\{ {{\theta _{ij}}|v_i^{\rm{g}},v_j^{\rm{g}} \in {V_{\rm{g}}}} \right\}$
(11)　　　根據(jù)$v_i^{\rm{g}},v_j^{\rm{g}} \in {V_{\rm{g}}}$的狀態(tài)，選擇共享備份可靠性估算模型得到
　　　　 $R\left( {G_{{\rm{backup}}}^{\rm{g}}} \right)$
(12)　　end for
(13)　　　鏈路備份
(14) end while
(15) return

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表 3 仿真參數(shù)設(shè)置表

仿真參數(shù)	參數(shù)設(shè)置	仿真參數(shù)	參數(shù)設(shè)置
物理節(jié)點的數(shù)目	N=12, 25, 36	物理節(jié)點CPU資源容量	U[10, 20]
物理節(jié)點可靠性分布	U[0.95, 0.99]	物理鏈路帶寬資源容量	U[20, 50]
NSR的VNF個數(shù)	3	NSR生命周期	[4, 12, 24]
3種類型切片的可靠性需求	U[0.90, 0.98]	VNF節(jié)點CPU資源需求	U[2, 6]
VNF之間帶寬資源需求	U[8, 16]

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