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Measurement-based traffic management for QoS guarantee in multi-service networks.

机译:用于多服务网络中QoS保证的基于测量的流量管理。

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This dissertation addresses some fundamental issues of measurement-based traffic management in multi-service networks. The major concerns include proper traffic measurement time interval and online QoS monitoring, the predictive network control performance, and the scalable scheme for weighted fairness guarantee in a DiffServ Assured Forwarding (AF) environment. The purpose is to provide the strict or elastic Qualify of Service (QoS) over multiple time scales at a multi-service ATM switch or a next-generation Internet router.; Given the practically ambiguous or insufficient network traffic knowledge, network operator relies on the on-line or off-line measurement of traffic statistics and resource utilization, in addition to a reliable traffic model, for robust control actions. Naturally the key points are how to accurately measure the real-time traffic bandwidth demand and how to guarantee the QoS over both short- and long-term periods. To answer these questions, we proposed a Virtual Queue (VQ) scheme to adapt the critical measurement interval Tc to real-time traffic dynamics and online measured QoS. The Tc derives an accurate load estimate at a single finite-buffer network node under explicit cell/delay loss constraints.; Assume that our measurement scheme has captured the accurate traffic load over the concerned time scales. However, it only reflects the past. We may set up certain traffic model to predict the traffic future for rate-based network controls. So what is the remotest future an online predictor can forecast confidently? This question motivated the predictability analysis of network traffic based on the idealized a priori traffic knowledge: stationarity, ergodicity and precise models. Our study reveals the typical MPI, i.e., the maximum prediction interval, the predictive control efficiency, and their tradeoff.; Due to the actual demand from the current industry, network researchers are working on the traffic management schemes for the next generation data network offering a variety of QoS guarantee. The merged DiffServ and MPLS technology in the Internet is a promising future, where heterogeneous flows ask for scalable weighted fairness from their AF services as a minimum QoS requirement. To meet this demand, we proposed a network-service model—SCALE-WFS. The model integrates the labeling concept from MPLS/ATM and the aggregated service concept from DiffServ with reliable traffic measurement. Performance evaluation shows its advantages over the popular schemes such as the Random Early Discarding (RED) and the core-stateless fair queueing (CSFQ). Again the traffic measurement plays a crucial role in the highly unpredictable and dynamic environment.
机译:本文解决了多业务网络中基于测量的流量管理的一些基本问题。主要问题包括正确的流量测量时间间隔和在线QoS监视,预测性网络控制性能以及DiffServ保证转发(AF)环境中加权公平性保证的可伸缩方案。目的是在多服务ATM交换机或下一代Internet路由器上的多个时间范围内提供严格或弹性的服务质量(QoS)。考虑到实际的模棱两可或不足的网络流量知识,网络运营商除了可靠的流量模型外,还依赖于流量统计和资源利用率的在线或离线测量,以实现可靠的控制措施。自然,关键点是如何准确测量实时流量带宽需求以及如何在短期和长期内保证QoS。为了回答这些问题,我们提出了一种虚拟队列(VQ)方案,以使关键测量间隔 T c 适应实时流量动态和在线测量的QoS。 T c 在显式信元/延迟损耗约束下,在单个有限缓冲区网络节点上得出准确的负载估计。假设我们的测量方案已捕获了有关时间范围内的准确流量负载。但是,它仅反映了过去。我们可能会建立某些流量模型,以预测基于速率的网络控制的流量未来。那么,在线预测器可以自信地预测的最遥远的未来是什么?这个问题基于理想的先验流量知识:平稳性,遍历性和精确模型,激发了网络流量的可预测性分析。我们的研究揭示了典型的 MPI ,即最大预测间隔,预测控制效率及其权衡。由于当前行业的实际需求,网络研究人员正在研究可提供各种QoS保证的下一代数据网络的流量管理方案。互联网中融合的DiffServ和MPLS技术是一个有希望的未来,异构流要求其AF服务提供可伸缩的加权公平性,以此作为最低QoS要求。为了满足这一需求,我们提出了一种网络服务模型SCALE-WFS。该模型将MPLS / ATM的标记概念和DiffServ的聚合服务概念与可靠的流量测量集成在一起。性能评估显示出它比诸如随机早期丢弃(RED)和无核无状态公平排队(CSFQ)等流行方案的优势。同样,流量测量在高度不可预测的动态环境中起着至关重要的作用。

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