B. Lorenzo, A. S. Shafigh, J. Liu, F. J. González-Castaño and Y. Fang, "Data and Spectrum Trading Policies in a Trusted Cognitive Dynamic Network Architecture," in IEEE/ACM Transactions on Networking, vol. 26, no. 3, pp. 1502-1516, June 2018. doi: 10.1109/TNET.2018.2828460
Data and spectrum trading policies in a trusted cognitive dynamic network architecture
|Author:||Lorenzo, Beatriz1; Shafigh, Alireza Shams2; Liu, Jianqing3;|
1University of Vigo
2Centre for Wireless Communications, University of Oulu
3University of Florida
|Online Access:||PDF Full Text (PDF, 2.4 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2018112649171
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2018-11-26
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.
|Pages:||1502 - 1516|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported in part by the Fulbright Program under Grant CAS16/00093, and in part by MINECO, Spain, under Grant TEC2016-76465-C2-2-R, Grant IJCI-2014-20611, and Grant EUIN2017-88225. The work of A. S. Shaﬁgh was supported by the Finnish Academy/NSF US collaborative program/WiFiUS 2018. The work of J. Liu and Y. Fang was supported in part by the National Science Foundation under Grant CNS-1717736 and Grant CNS-1343356.
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