Traffic Engineering and Quality of Service in Hybrid Software Defined Networks  

作　　者：Samiullah Mehraban Rajesh Kumar Yadav 

机构地区：[1]IOT Lab,Department of Computer Science&Engineering,Delhi Technological University,Delhi 110042,India

出　　处：《China Communications》2024年第2期96-121,共26页中国通信（英文版）

摘　　要：For Future networks, many research projects have proposed different architectures around the globe;Software Defined Network(SDN) architectures, through separating Data and Control Layers, offer a crucial structure for it. With a worldwide view and centralized Control, the SDN network provides flexible and reliable network management that improves network throughput and increases link utilization. In addition, it supports an innovative flow scheduling system to help advance Traffic Engineering(TE). For Medium and large-scale networks migrating directly from a legacy network to an SDN Network seems more complicated & even impossible, as there are High potential challenges, including technical, financial, security, shortage of standards, and quality of service degradation challenges. These challenges cause the birth and pave the ground for Hybrid SDN networks, where SDN devices coexist with traditional network devices. This study explores a Hybrid SDN network’s Traffic Engineering and Quality of Services Issues. Quality of service is described by network characteristics such as latency, jitter, loss, bandwidth,and network link utilization, using industry standards and mechanisms in a Hybrid SDN Network. We have organized the related studies in a way that the Quality of Service may gain the most benefit from the concept of Hybrid SDN networks using different algorithms and mechanisms: Deep Reinforcement Learning(DRL), Heuristic algorithm, K path partition algorithm, Genetic algorithm, SOTE algorithm, ROAR method, and Routing Optimization with different optimization mechanisms that help to ensure high-quality performance in a Hybrid SDN Network.

关 键 词：DRL hSDN QOE QOS SDN TE 

分 类 号：TP393.02[自动化与计算机技术—计算机应用技术]