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Register a new userData and Spectrum Trading Policies in a Trusted Cognitive Dynamic Network
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Added by
Beatriz Lorenzo
Publication date
2018
fields
Informatics Engineering
and research's language is
English
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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.
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In this paper, we consider context-awareness to enhance route reliability and robustness in multi-hop cognitive networks. A novel context-aware route discovery protocol is presented to enable secondary users to select the route according to their QoS requirements. The protocol facilitates adjacent relay selection under different criteria, such as shortest available path, route reliability and relay reputation. New routing and security-based metrics are defined to measure route robustness in spatial, frequency and temporal domains. Secure throughput, defined as the percentage of traffic not being intercepted in the network, is provided. The resources needed for trading are then obtained by jointly optimizing secure throughput and trading price. Simulation results show that when there is a traffic imbalance of factor 4 between the primary and secondary networks, 4 channels are needed to achieve 90% link reliability and 99% secure throughput in the secondary network. Besides, when relay reputation varies from 0.5 to 0.9, a 20% variation in the required resources is observed.
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