Journal
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
Volume 18, Issue 8, Pages 4116-4128Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2019.2921344
Keywords
Network virtualization; supplier-firm-buyer framework; three-sided matching; matching game
Funding
- National Nature Science Foundation of China [61431003, 61372113]
- U.S. Multidisciplinary University Research Initiative (MURI) Air Force Office of Scientific Research [MURI 18RT0073]
- NSF [CNS-1717454, CNS-1731424, CNS-1702850, CNS-1646607]
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In recent years, the joint configuration of communication, computing and popular content resources in wireless networks has been gaining an increasing amount of attention to efficiently handle the gigantic data traffic. To effectively manage resources, the network virtualization is deemed as a promising technique in which mobile virtual network operators (MVNOs) create virtual slices to serve the requests issued by their subscribed users via obtaining contents and computing abilities from content providers and fog nodes. In this paper, the above MVNO optimization is formulated as an assignment game employing the supplier-firm-buyer game model, which gives the optimal solution of matchings among the contents, computation nodes, MVNOs, and users. Moreover, the existence of the non-empty core of such game is proved, indicating that the proposed framework is stable. In order to obtain the simple practical solution, a distributed suboptimal algorithm of reduced version of three-sided matching with size and cyclic preference (R-TMSC) is adopted. Furthermore, a greedy strategy is proposed to improve the convergence speed as well as performance of the R-TMSC scheme. The simulation results show that compared to the random allocation, a 12.97% increase in average revenue can be reached by solving the supplier-firm-buyer problem, and that the greedy R-TMSC algorithm is able to reach the similar point of the optimal value with a faster speed.
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