Performance analysis of Bayesian Networks-based distributed Call Admission Control for NGN
Performance analysis of Bayesian Networks-based distributed Call Admission Control for NGN
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DOI：
10.1109/noms.2012.6212054
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发表时间：
2012-04
期刊：
影响因子：
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通讯作者：
A. Bashar;G. Parr;S. McClean;B. Scotney;D. Nauck
中科院分区：
文献类型：
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作者：
A. Bashar;G. Parr;S. McClean;B. Scotney;D. Nauck
网络的有效管理和提供具有期望的QoS保证的服务是一个挑战，需要通过智能、轻量级和可扩展的自主机制来解决。最近的重点是应用机器学习方法来模拟网络和服务行为模式，已被证明是非常有效的，在实现自主管理的目标。为此，本文提出了实现分布式管理解决方案，利用贝叶斯网络（BN）的预测能力的想法。提出并实现了一种多节点分布式呼叫接纳控制解决方案（简称BNDAC），以展示BN的建模和预测能力。从预测精度、算法复杂度和决策速度等方面对BNDAC进行了全面的评价。在一个在线的设置，BNDAC的性能进行评估，并与一个集中的情况下进行比较，以证明其上级性能的呼叫阻塞概率和QoS提供。基于Opnet Modeler和Hugin Researcher的仿真结果表明了BNDAC解决方案对于NGN等真实的世界网络的实时操作和管理的可行性和适用性。
The efficient management of networks and the provisioning of services with desired QoS guarantees is a challenge which needs to be addressed through autonomous mechanisms which are intelligent, lightweight and scalable. Recent focus on applying Machine Learning approaches to model the network and service behavioural patterns have proved to be quite effective in fulfilling the objectives of autonomous management. To this end, this paper advances on the idea of implementing a distributed management solution which harnesses the predictive capability of Bayesian Networks (BN). A multi-node distributed Call Admission Control solution (termed as BNDAC) is proposed and implemented to demonstrate the modelling and prediction power of BN. A thorough evaluation of BNDAC is presented in terms of its prediction accuracy, algorithmic complexity and decision-making speed. In an online setup, performance of BNDAC is evaluated and compared with a centralised scenario, to demonstrate its superior performance for Call Blocking Probability and QoS provisioning. Simulation results based on Opnet Modeler and Hugin Researcher show the feasibility and applicability of BNDAC solution for real-time operation and management of real world networks such as the NGN.