Fifth-generation(5G)systems have brought about new challenges toward ensuring Quality of Service(QoS)in differentiated services.This includes low latency applications,scalable machine-to-machine communication,and enha...Fifth-generation(5G)systems have brought about new challenges toward ensuring Quality of Service(QoS)in differentiated services.This includes low latency applications,scalable machine-to-machine communication,and enhanced mobile broadband connectivity.In order to satisfy these requirements,the concept of network slicing has been introduced to generate slices of the network with specific characteristics.In order to meet the requirements of network slices,routers and switches must be effectively configured to provide priority queue provisioning,resource contention management and adaptation.Configuring routers from vendors,such as Ericsson,Cisco,and Juniper,have traditionally been an expert-driven process with static rules for individual flows,which are prone to sub optimal configurations with varying traffic conditions.In this paper,we model the internal ingress and egress queues within routers via a queuing model.The effects of changing queue configuration with respect to priority,weights,flow limits,and packet drops are studied in detail.This is used to train a model-based Reinforcement Learning(RL)algorithm to generate optimal policies for flow prioritization,fairness,and congestion control.The efficacy of the RL policy output is demonstrated over scenarios involving ingress queue traffic policing,egress queue traffic shaping,and one-hop router coordinated traffic conditioning.This is evaluated over a real application use case,wherein a statically configured router proved sub optimal toward desired QoS requirements.Such automated configuration of routers and switches will be critical for multiple 5G deployments with varying flow requirements and traffic patterns.展开更多
校园专网中的重要业务需要足够的带宽以保障其服务质量。Open Flow仅设置端口队列忽略了总带宽需求超过链路容量的情况,OPPBG(Open Flow-Based Path-Planning with Bandwidth Guarantee)算法无法区分多个业务。针对这种情况,提出一种基...校园专网中的重要业务需要足够的带宽以保障其服务质量。Open Flow仅设置端口队列忽略了总带宽需求超过链路容量的情况,OPPBG(Open Flow-Based Path-Planning with Bandwidth Guarantee)算法无法区分多个业务。针对这种情况,提出一种基于SDN(Software Defined Networking)的路径选择与带宽保障策略。算法首先删除不满足带宽需求的链路,随后通过路径选择过程获得最佳路径,最后沿该路径为各业务设置交换机端口队列用于调度转发。实验结果表明,重要业务的各自带宽需求均能得到满足。该算法能有效提升专网服务质量,防止重要业务受现有流量及未来流量干扰,提升网络性能和健壮性。展开更多
文摘Fifth-generation(5G)systems have brought about new challenges toward ensuring Quality of Service(QoS)in differentiated services.This includes low latency applications,scalable machine-to-machine communication,and enhanced mobile broadband connectivity.In order to satisfy these requirements,the concept of network slicing has been introduced to generate slices of the network with specific characteristics.In order to meet the requirements of network slices,routers and switches must be effectively configured to provide priority queue provisioning,resource contention management and adaptation.Configuring routers from vendors,such as Ericsson,Cisco,and Juniper,have traditionally been an expert-driven process with static rules for individual flows,which are prone to sub optimal configurations with varying traffic conditions.In this paper,we model the internal ingress and egress queues within routers via a queuing model.The effects of changing queue configuration with respect to priority,weights,flow limits,and packet drops are studied in detail.This is used to train a model-based Reinforcement Learning(RL)algorithm to generate optimal policies for flow prioritization,fairness,and congestion control.The efficacy of the RL policy output is demonstrated over scenarios involving ingress queue traffic policing,egress queue traffic shaping,and one-hop router coordinated traffic conditioning.This is evaluated over a real application use case,wherein a statically configured router proved sub optimal toward desired QoS requirements.Such automated configuration of routers and switches will be critical for multiple 5G deployments with varying flow requirements and traffic patterns.
文摘针对快速路由器转发技术需求,提出了一种多协议端口转发技术(Multi-Protocol Label Switching,MPPF)。该技术采用多跳传输方式,其工作过程包括形成端口队列、形成端口转发表、发送Hello报文和封装端口转发报文。提出方法通过端口队列实现IP数据包的快速转发,大大减少了数据包的传输延时,同时还具有可用性、可靠性和安全性。与传统路由转发技术和MPLS(Multi-protocol Port Forwarding)相比,MPPF在大型网络中有更高的转发效率和更好的传输性能。
文摘校园专网中的重要业务需要足够的带宽以保障其服务质量。Open Flow仅设置端口队列忽略了总带宽需求超过链路容量的情况,OPPBG(Open Flow-Based Path-Planning with Bandwidth Guarantee)算法无法区分多个业务。针对这种情况,提出一种基于SDN(Software Defined Networking)的路径选择与带宽保障策略。算法首先删除不满足带宽需求的链路,随后通过路径选择过程获得最佳路径,最后沿该路径为各业务设置交换机端口队列用于调度转发。实验结果表明,重要业务的各自带宽需求均能得到满足。该算法能有效提升专网服务质量,防止重要业务受现有流量及未来流量干扰,提升网络性能和健壮性。
