Data and Spectrum Trading Policies in a Trusted Cognitive Dynamic Network Architecture
Data and Spectrum Trading Policies in a Trusted Cognitive Dynamic Network Architecture
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DOI：
10.1109/tnet.2018.2828460
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发表时间：
2018-05
期刊：
影响因子：
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通讯作者：
B. Lorenzo;A. Shafigh;Jianqing Liu;F. González-Castaño;Yuguang Fang
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作者：
B. Lorenzo;A. Shafigh;Jianqing Liu;F. González-Castaño;Yuguang Fang
未来的无线网络将逐步将服务提供转移到边缘，以适应流量的不断增长。这种范式转变需要智能策略来有效共享网络资源并确保服务交付。在本文中，我们考虑了一种认知动态网络架构（CDNA），其中主要用户（PU）因共享其连接性并充当次要用户（SU）的接入点而获得奖励。 CDNA 通过在网络范围内收集来自不同运营商的未使用数据计划和频谱，创造了增加容量的机会。基于涉及主运营商（PO）、二级运营商（SO）及其各自的最终用户的集中式、混合式和分布式方案，提出了不同的数据和频谱交易策略。在这些方案中，PO和SO逐步将交易委托给最终用户，并采用更灵活的合作协议来减少计算时间并动态跟踪可用资源。提出了一种新颖的匹配定价算法，能够以低计算复杂度实现自组织 SU-PU 关联、数据和频谱的信道分配和定价。由于连接是由实际用户提供的，因此底层协作市场的成功取决于连接的可信度。开发基于行为的访问控制机制来激励/惩罚诚实/不诚实的行为并创建可信的协作网络。数值结果表明，混合方案的计算时间比基准集中式方案快一个数量级，并且匹配算法重新配置网络的速度比集中式方案快三个数量级。
Future wireless networks will progressively displace service provisioning towards the edge to accommodate increasing growth in traffic. This paradigm shift calls for smart policies to efficiently share network resources and ensure service delivery. In this paper, we consider a cognitive dynamic network architecture (CDNA) where primary users (PUs) are rewarded for sharing their connectivities and acting as access points for secondary users (SUs). CDNA creates opportunities for capacity increase by network-wide harvesting of unused data plans and spectrum from different operators. Different policies for data and spectrum trading are presented based on centralized, hybrid, and distributed schemes involving primary operator (PO), secondary operator (SO), and their respective end users. In these schemes, PO and SO progressively delegate trading to their end users and adopt more flexible cooperation agreements to reduce computational time and track available resources dynamically. A novel matching-with-pricing algorithm is presented to enable self-organized SU-PU associations, channel allocation and pricing for data and spectrum with low computational complexity. Since connectivity is provided by the actual users, the success of the underlying collaborative market relies on the trustworthiness of the connections. A behavioral-based access control mechanism is developed to incentivize/penalize honest/dishonest behavior and create a trusted collaborative network. Numerical results show that the computational time of the hybrid scheme is one order of magnitude faster than the benchmark centralized scheme and that the matching algorithm reconfigures the network up to three orders of magnitude faster than in the centralized scheme.