Data and Spectrum Trading Policies in a Trusted Cognitive Dynamic Network Architecture - 2018


Future wireless networks can progressively displace service provisioning towards the sting to accommodate increasing growth in traffic. This paradigm shift concerns good policies to efficiently share network resources and guarantee service delivery. During this Project, we tend to consider a cognitive dynamic network design (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 totally different operators. Totally different policies for knowledge and spectrum trading are presented based mostly on centralized, hybrid, and distributed schemes involving primary operator (PO), secondary operator (SO), and their respective finish users. In these schemes, PO and THUS progressively delegate trading to their end users and adopt additional flexible cooperation agreements to scale back computational time and track accessible resources dynamically. A completely unique matching-with-pricing algorithm is presented to enable self-organized SU-PU associations, channel allocation and pricing for information 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 mostly 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 theme and that the matching algorithm reconfigures the network up to three orders of magnitude faster than in the centralized scheme.

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