Optimized Controller Placement for Soft Handover in Virtualized 5G Network
Optimized Controller Placement for Soft Handover in Virtualized 5G Network
复制标题
虚拟化 5G 网络中软切换的优化控制器布局
DOI：
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发表时间：
2020
期刊：
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通讯作者：
Uttam Ghosh
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作者：
Deborsi Basu;Abhishek Jain;R. Datta;Uttam Ghosh
软化网络功能虚拟化(SNFV)正在推动下一代5G电信网络满足移动用户的所有实时业务需求。在高移动性场景中实现超低延迟(ULL)的无缝连接是研究人员正在紧张工作的最必要和最具挑战性的领域之一。得益于网络功能软化，借助软件定义网络(SDN)，可以非常轻松地优化用户数据平面和控制平面特性。在5G网络架构中，服务网关(SGW)和分组数据网关(PGW)负责将控制功能(例如信令和隧道创建)从一个控制器移交给另一个控制器。SDN制动SGW，使S/PGW-C在控制平面，S/PGW-U在数据平面。UE业务转发决策在S/pgw-C处做出，并进一步指示S/pgw-U执行所需的数据传输操作。在SGW-C上使用在联合云上运行的虚拟机进行不间断信号流的动态升级。在本文中，我们重点研究了一个独特而新颖的SGW控制器放置问题(CPP)，该问题在受限的网络延迟约束下在控制器负载和切换频率之间进行了权衡。问题的表述是基于混合整数线性优化规划模型进行的。Pareto最优算法解表明，SGW-C的适当控制面分布满足所有必要的目标。
Softwarized Network Function Virtualization (sNFV) is driving the next generation 5G telecommunication networks to fulfill all the real time service demands of mobile users. Seamless connectivity with ultra low latency (ULL) in high mobility scenarios is one of the most necessary and challenging areas where researchers are working intensively. Thanks to Network Function Softwarization that helps to optimize the user data plane and control plane characteristics very easily with the help of Software Defined Networking (SDN). Inside a 5G network architecture the Serving Gateways (SGW) and Packet Data Gateways (PGW) are responsible for handing over the control functions (e.g signaling and tunnel creation) from one controller to another. SDN brakes SGW to make S/PGW-C at control plane and S/PGW-U at data plane. The UE traffic forwarding decisions are taken at S/PGW-C and further it instructs the S/PGW-U to execute the required data transferring operations. Dynamic up-gradations for uninterrupted signal flow are done at SGW-C using virtual machines running on a federated cloud. In this paper, we focus on a unique and novel SGW Controller Placement Problem (CPP) where a trade off has been made in between the controller load and handover frequency within a restricted network latency constraint. The problem formulations are done based on a Mixed Integer linear Optimization Programming model. The Pareto optimal algorithmic solution shows the suitable control plane distributions of SGW-C satisfying all the necessary objectives.