CoopAI-Route: DRL Empowered Multi-Agent Cooperative System for Efficient QoS-Aware Routing for Network Slicing in Multi-Domain SDN

作     者：Meignanamoorthi Dhandapani V.Vetriselvi R.Aishwarya 

作者机构：College of Engineering GuindyAnna UniversityChennai600025India 

出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)

年 卷 期：2024年第140卷第9期

页      面：2449-2486页

核心收录：

学科分类：0710[理学-生物学] 0810[工学-信息与通信工程] 080904[工学-电磁场与微波技术] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 0835[工学-软件工程] 081001[工学-通信与信息系统] 0836[工学-生物工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：The authors wish to express their appreciation to the reviewers for their helpful suggestions  which greatly improved the presentation of this paper 

主　　题：6G multi-domain multi-agent routing DRL SDN 

摘      要：The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global *** slicing is crucial in delivering services for different,demanding vertical applications in this ***-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended ***,the existing IP(Internet Protocol)over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network *** inter-domain routing methods,like Border Gateway Protocol(BGP),cannot make routing decisions based on performance,which frequently results in traffic flowing across congested paths that are never *** address these issues,we propose CoopAI-Route,a multi-agent cooperative deep reinforcement learning(DRL)system utilizing hierarchical software-defined networks(SDN).This framework enforces network slicing in multi-domain networks and cooperative communication with various administrators to find performance-based routes in intra-and ***-Route employs the Distributed Global Topology(DGT)algorithm to define inter-domain Quality of Service(QoS)***-Route uses a DRL agent with a message-passing multi-agent Twin-Delayed Deep Deterministic Policy Gradient method to ensure optimal end-to-end routes adapted to the specific requirements of network slicing *** evaluation demonstrates CoopAI-Route’s commendable performance in scalability,link failure handling,and adaptability to evolving topologies compared to state-of-the-art methods.