Time-Dependent Pricing for Bandwidth Slicing under Information Asymmetry and Price Discrimination

Zhenyu Zhou, Bingchen Wang, Bo Gu, Bo Ai, Shahid Mumtaz, Jonathan Rodriguez, Mohsen Guizani

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    Abstract

    Due to the bursty nature of Internet traffic, network service providers (NSPs) are forced to expand their network capacity in order to meet the ever-increasing peak-time traffic demand, which is however costly and inefficient. How to shift the traffic demand from peak time to off-peak time is a challenging task for NSPs. In this paper, we study the implementation of time-dependent pricing (TDP) for bandwidth slicing in software-defined cellular networks under information asymmetry and price discrimination. Congestion prices indicating real-time congestion levels of different links are used as a signal to motivate delay-tolerant users to defer their traffic demands. We formulate the joint pricing and bandwidth demand optimization problem as a two-stage Stackelberg leader-follower game. Then, we investigate how to derive the optimal solutions under the scenarios of both complete and incomplete information. We
    also extend the results from the simplified case of a single congested link to the more complicated case of multiple congested links, where price discrimination is employed to dynamically adjust the price of each congested link in accordance with its real-time congestion level. Simulation results demonstrate that the proposed pricing scheme achieves superior performance in increasing the NSP’s revenue and reducing the peak-to-average traffic ratio (PATR).
    Original languageEnglish
    Article number9112235
    Pages (from-to)6975 - 6989
    Number of pages15
    JournalIEEE Transactions on Communications
    Volume68
    Issue number11
    DOIs
    Publication statusPublished - 9 Jun 2020

    Keywords

    • Time-dependent pricing
    • bandwidth slicing
    • information asymmetry
    • price discrimination
    • software-defined cellular networks

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