This paper focusses on Service Level Agreement (SLA) based end-to-end Quality of Service (QoS) maintenance across a wireless optical integrated network. We use long term evolution (LTE) based spectrum access system (SAS) in the wireless network and the optical network is comprised of an Ethernet Passive Optical Network (EPON). The proposal targets a learning-based intelligent SAS where opportunistic allocation of any available bandwidth is done after meeting the SLA requirements. Such an opportunistic allocation is particularly beneficial for nomadic users with varying QoS requirements. The opportunistic allocation is carried out with the help of Vickrey-Clarke-Groves (VCG) auction. The proposal allows the users of the integrated network to decide the payment they want to make in order to opportunistically avail bandwidth. Learning automata is used for the users to intelligently converge to the optimal payment value based on the network load. The payment made by the users is later used by the optical network units of the EPON to prepare the bids for the auction. The proposal has been verified through extensive simulations.
翻译:本文的重点是基于服务级协议(SLA)的端到端服务质量维护,它涉及无线光学综合网络,我们使用无线网络和光学网络的长期进化(LTE)频谱访问系统(SAS),光学网络包括以太网被动光学网络(EPON),建议针对的是基于学习的智能SAS,在满足SLA要求后,可以有机会分配任何现有带宽。这种机会性分配对具有不同QOS要求的游牧用户特别有利。机会分配是在Vickrey-Clarke-Groves(VCG)拍卖的帮助下进行的。建议允许综合网络的用户决定他们想要支付什么钱,以便有机会利用带宽。学习自动数据,供用户在满足网络负荷后明智地与最佳支付价值汇合。用户的付款后来由EPON光学网络单位用来准备拍卖的投标。该提案经过广泛的模拟核实。