Effective-Capacity Based Gaming for Optimal Power and Spectrum Allocations over Big-Data Virtual Wireless Networks

Big data transmission on a wireless network environment focuses on sharing the large volume information data with the effective capacity guaranteed. Wireless network virtualization provides an efficient technique to implement the big data transmission by enabling multiple virtual wireless networks (VWNs) to be mapped onto one physical substrate wireless network (SWN), downloading the information data from SWN. One of the most important challenges of this technique lies in how to efficiently allocate the wireless resources of physical wireless networks to the multiple virtual wireless network users, considering the quality of service for the data transmission. To overcome these difficulties, in this paper we propose a novel auction based scheme to resolve the wireless resources allocation problem in terms of transmit power and wireless spectrum. We formulate this wireless resources allocation problem as an auction process where each mobile user bids for the limited wireless resources from physical substrate wireless networks, and competes with the other mobile-user players bidding for the same resources. First, the mobile users derive their bids for transmit powers, which indicate their willingness to pay for the transmit powers, aiming at maximizing their payoffs (performance-gain minus cost) on each subchannel. Then, according to the derived available transmit power on each subchannel, mobile users derive their bids for the number of subchannels, aiming at maximizing their overall payoffs. The SWN assigns these two types of wireless resources to each mobile user according to the bids for all virtual users. Finally, as the mobile users' bidding processes proceed iteratively, our proposed games are guaranteed to converge to the Nash Equilibrium, where the benefits of SWN and mobile users are both optimized, thus maximizing the aggregate effective capacities for our resources-virtualized big data transmission wireless networks. The extensive simulation results obtained validate and evaluate our proposed schemes.