NGN网络中基于出口节点资源预测的高效端到端QoS机制

S. Ban, J. Choi, Hyong S. Kim
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引用次数: 12

摘要

提出了一种基于探测法的下一代网络出口节点资源预测的高效端到端QoS机制。随着网络的智能化和智能化,为用户提供融合、有保障的服务是下一代网络的首要任务。为了提供这些服务,NGN应该支持适当的端到端机制,以支持分组网络中的异构QoS环境。我们研究了IPv6 DiffServ, MPLS DiffServ和其他端到端QoS与差分服务,并有四种方式提供端到端QoS从当前的最佳努力网络到下一代网络;传统IP网络中的best-effort QoS、DiffServ网络中的QoS分类优先级、MPLS网络中的QoS聚合/TE和单个QoS/TE。当前发展下一代网络所面临的问题之一是遗留设备众多,不能一次性更换,网络间存在各种QoS差异服务。为了解决这个问题,应该有适当的准入控制机制来保护核心网并支持接入网的端到端QoS。基于计划的准入简单但效率不高,基于探测的准入控制效率高但网络开销大,而基于出口资源预测的准入控制效率高,网络开销小。基于出口资源预测的准入控制机制包括两个部分。首先,它通过探测来检查出口节点的利用率。但与基于探测的准入控制不同,它并不总是在有QoS请求时发送探测。它通过探测处理一束请求,预测出口节点的状态,并发送探测来处理下一束请求。在这种机制中,如何度量出节点的当前状态并预测出节点的未来状态
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient end-to-end QoS mechanism using egress node resource prediction in NGN network
This paper proposes an efficient end-to-end QoS mechanism using egress node resource prediction via probe method in next generation network (NGN). As we want more smart and intelligent network, NGN is the most important issue to provide users converged and guaranteed services. To provide these services, NGN should support proper end-to-end mechanism to support a heterogeneous QoS environment in packet networks. We have studied in IPv6 DiffServ, MPLS DiffServ and other end-to-end QoS with differential service and, there are four ways to provide end-to-end QoS from current best-effort network to NGN; best-effort QoS in traditional IP network, QoS classification with priority in DiffServ network, QoS aggregation/TE in MPLS network and individual QoS/TE. One of the current problems to evolve NGN are there are many legacy equipments which we can not replace at once and various QoS differential service among networks. To address this, there should be proper admission control mechanisms to protect the core network and support end-to-end QoS in the access network. While planning-based admission is simple but not efficient, and probed-based admission control is efficient but has overhead in the network, egress resource prediction-based admission control is efficient and less overhead compared to the previous mechanisms. Egress resource prediction-based admission control mechanism has two parts. First, it checks the utilization of the egress node by probing. But not like probe-based admission control, it does not send probes as always as there are QoS requests. It handles a bundle of requests with probing, predicts the state of the egress node and sends the probe to handle the next bundle of requests. In this mechanism, how to measure the current state of egress node and predict its future state
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