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A Bayesian k-NN based scheme for QoS provisioning in IP/MPLS networks

机译:IP / MPLS网络中基于QoS的基于贝叶斯k-NN的方案

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The Quality of Service (QoS) provisioning paradigm has become highly complicated due to the rising of networks complexity, heterogeneity and unpredictability. This complexity resulted in the need to satisfy stringent user's QoS requirements which depends generally on network capabilities. To deal with this complexity, an autonomic management of the global network seems to be mandatory. Indeed, autonomic network management can offer a new way to master end-to-end performances by providing self-∗ properties to networks. Self-∗ properties include self-optimization, self-organization, self-protection and many others. This paper proposes an autonomic and flexible end-to-end QoS provisioning scheme which is based on the per-hop classes of service discovery and its mapping to user's QoS requirements basing on the k-nearest neighbor algorithm (k-NN). Simulation results show that the proposed scheme significantly outperforms performances of parallel solutions such as the IntServ-over-Diffserv model and the EEAC-SV approach proposed in [14] with respect to the request delay bounds and the packet dropping ratio capability, respectively.
机译:由于网络复杂性,异构性和不可预测性的提高,服务质量(QoS)设置范例已变得高度复杂。这种复杂性导致需要满足严格的用户QoS要求,该要求通常取决于网络功能。为了应对这种复杂性,似乎必须对全球网络进行自主管理。确实,自主网络管理可以通过为网络提供自属性来提供一种掌握端到端性能的新方法。自我属性包括自我优化,自我组织,自我保护等。本文提出了一种自动且灵活的端到端QoS设置方案,该方案基于每跳类的服务发现及其基于k最近邻居算法(k-NN)映射到用户的QoS要求。仿真结果表明,在请求延迟范围和丢包率方面,该方案明显优于并行解决方案的性能,如IntServ-over-Diffserv模型和EEAC-SV方法[14]中提出的。

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