Load and Latency aware Cost Optimal Controller Placement in 5G Network using sNFV
Load and Latency aware Cost Optimal Controller Placement in 5G Network using sNFV
复制标题
使用 sNFV 在 5G 网络中实现负载和延迟感知成本最优控制器放置
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Addanki Sankara Rao
中科院分区：
文献类型：
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作者：
Deborsi Basu;R. Datta;Uttam Ghosh;Addanki Sankara Rao
第五代移动网络（5G）的目标是以经济高效的方式满足最终用户的所有服务需求。在资源有限的环境中提供最佳的端到端网络服务确实是一项具有挑战性的任务。电信服务提供商（TSP）面临着巨大的麻烦，如何通过增加网络覆盖面积来最小化网络部署成本以覆盖更多用户。软件定义网络（SDN）和网络功能虚拟化（NFV）是关键技术推动者，有潜力改善下一代电信网络的技术经济场景。在这项工作中，我们制定了一种独特的具有成本效益的控制器放置算法（LLACPA - 负载和延迟感知控制器放置算法），该算法可以使用软件化网络功能虚拟化（sNFV）的概念成功降低高密度 5G 网络的 CAPEX（资本支出）、OPEX（运营支出）和 TCO（总拥有成本）成本。超低延迟 (ULL) 无缝连接是 5G 的关键特性之一。因此，我们根据网络延迟和UE（用户设备）的流量负载需求进一步优化模型。通过比较图形分析，已经证明我们提出的算法与现有的当前网络相比，5G 网络的成本显着降低。具有成本效益的控制器部署算法还考虑了所有其他网络约束，并使这种方法对于 TSP 非常有效。
5th Generation of Mobile Networking (5G) is tar-geting to fulfil all the service demands of end users in acost effective manner. To provide optimum end-to-end network services within a resource restricted environment is really a challenging task. Tele-communication Service Providers (TSPs)are facing huge trouble in order to minimize the network deployment cost to cover more users by increasing the network coverage area. Software Defined Networking (SDN) and Network Function Virtualization (NFV) are key technology enablers to have potential to improve techno-economic scenarios for next generation telecommunication networks. In this work, we have formulated a unique cost effective controller placement algorithm(LLACPA - Load & Latency aware Controller Placement Algorithm) that can successfully reduce the cost of CAPEX (Capital Expenditure), OPEX (Operational Expenditure) and TCO (Total Cost of Ownership) of a highly dense 5G network using the concept of softwarized Network Function Virtualization (sNFV). Seamless connectivity in Ultra Low Latency (ULL) is one of the key features of 5G. So, we further optimize the model based on network latency and traffic load demand of the UEs (User Equipment). Using a comparative graphical analysis it has been demonstrated that our proposed algorithm shows significant cost reduction in the 5G network as compare to existing current days networks. The cost effective controller deployment algorithm also takes care of all other network constrains and make this approach very much efficient for TSPs.