End to End Network Slicing Security Deployment Algorithm for Multi Service Scenarios
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摘要: 5G移动通信中，网络切片(NS)的引入成功解决了不同业务场景的网络资源分配不均问题。针对传统算法无法满足5G网络的多业务场景切片安全部署问题，该文提出一种针对于多业务场景的端到端网络切片安全需求(NSR)部署算法。首先，针对切片部署过程中节点的安全性进行了定义；其次，根据节点的安全性进行排序和映射，在此基础上，以最小化网络资源部署成本的同时提高部署的安全收益为目标，构建切片部署的数学模型；最后，考虑到每种类型切片的资源需求不同，提出一种针对性的部署算法实现端到端网络切片的安全部署。仿真结果表明，所提算法在满足端到端网络切片安全部署的同时，降低了部署的成本，获得了较好的部署安全收益。Abstract: In 5G mobile communication, the introduction of Network Slice (NS) solves successfully the problem of uneven network resource allocation in different business scenarios. In view of the problem that traditional algorithms can not meet the security deployment of 5G network multi business scenario slicing, an end-to-end Network Slicing security Requirement (NSR) deployment algorithm for multi business scenario is proposed. Firstly, the security of nodes in slice deployment process is defined; Secondly, the nodes are sorted and mapped according to their security. On this basis, in order to minimize the cost of network resource deployment and improve the security benefits of deployment, a mathematical model of slice deployment is constructed; Finally, considering the different resource requirements of each type of slicing, a targeted deployment algorithm is proposed to realize the secure deployment of end-to-end network slicing. Simulation results show that the proposed algorithm can satisfy the security deployment of end-to-end network slices, reduce the deployment cost and obtain better deployment security benefits.
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Key words:
- 5G Network Slice (NS) /
- Security deployment /
- Multi service scenarios /
- Safety benefits
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表 1 虚拟节点安全等级排序算法
输入：原始的节点集合$ {N^{\rm{R}}} $ 输出：排序的节点集合${{S} }({N^{\rm{R} } })$ (1) 计算所有节点的安全性NS并进行降序排列 (2) 将NS值最高的节点标记为R，并作为根节点生成BFS树 (3) 将树中的每一层节点按照式(1)中方法排序 (4) 返回排序后的节点集合${{S} }({N^{\rm{R} } })$ 
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表 2 切片请求中虚拟节点映射算法
输入：网络切片请求 输出：映射的节点集合 (1) for 每一个虚拟节点i do (2) if $i = {{R} }$ then (3) 映射到具有最高安全等级的物理节点上 (4) if $i \ne {{R} }$ then (5) 选择$ i $的父节点F, 物理节点P (6) 选择P的相邻节点为备用节点集合A (7) 满足节点容量的同时选择集合${{A} }$中$ {\rm{NS}} $值最大的节点 (8) end if (9) 返回节点集合 (10) end for
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表 3 切片请求中虚拟链路映射算法
输入：网络切片请求 输出：映射后的链路集合 (1) 将链路的带宽进行降序排列 (2) for 每一条虚拟链路 do (3) 计算该链路的带宽，并进行链路筛选 (4) 找到虚拟链路的两端的物理节点 (5) 利用插点法寻找两个链路之间的最短路径作为虚拟链路的
映射路径(6) 返回链路集合 (7) end for
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表 4 eMBB切片跨域部署实现算法
输入：eMBB类型切片$ {R^{\rm{e}}} $，网络资源$ {G^{\rm{P}}} $ 输出：部署结果 (1) 依据算法1对节点排序得到$ S\left( {{N^{\rm{R}}}} \right) $ (2) 依据算法2按照排序结果对ANs节点进行映射 (3) 依据算法2按照排序结果对CNs节点进行映射 (4) 依据算法3完成链路映射 (5) 依据链路映射结果对TNs节点进行映射 (6) 返回部署结果
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表 5 mMTC切片跨域部署实现算法
输入：mMTC类型切片$ {R^{\rm{m}}} $，网络资源$ {G^{\rm{P}}} $ 输出：部署结果 (1) 依据表1算法对节点排序得到$ S\left( {{N^{\rm{R}}}} \right) $ (2) 依据表2算法按照排序结果对CNs节点进行映射 (3) 选择资源满足需求的ANs节点作为候选ANs节点 (4) 搜索CNs节点和候选ANs节点之间的候选物理链路集合，并
根据对比结果完成链路映射(5) 依据虚拟链路映射结果对TNs节点进行映射 (6) 完成ANs节点的映射 (7) 返回部署结果
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表 6 uRLLC切片跨域部署实现算法
输入：uRLLC类型切片$ {R^{\rm{u}}} $，网络资源$ {G^{\rm{P}}} $ 输出：部署结果 (1) 依据表1算法对节点排序得到$ S\left( {{N^{\rm{R}}}} \right) $ (2) 依据节点安全等级选择ANs节点CNs节点作为候选节点集合 (3) 搜索候选CNs节点和候选ANs节点之间的候选物理路径集合，
并根据对比结果完成链路映射(4) 依据虚拟链路映射结果对TNs节点进行映射 (5) 完成ANs节点，CNs节点的映射 (6) 返回部署结果
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