Game-theoretic Approaches for Network Pricing

As 6G communication technology evolves, the complexity of network infrastructure introduces new challenges for pricing and resource management. This survey reviews the application of game theory in network economics, focusing on key areas such as dynamic pricing, (edge) cloud computing pricing, and two-sided pricing models. We first explore dynamic pricing strategies, analyzing how real-time adjustments based on network demand and user behavior can optimize resource allocation and maximize revenue. Next, we review research on (edge) cloud computing pricing, discussing models that account for the specific requirements of edge computing to enhance service efficiency. Finally, we examine two-sided pricing strategies, focusing on how platforms can balance supply and demand by effectively pricing interactions between different user groups. This survey aims to provide insights and directions for future research in pricing strategies as networks become increasingly complex in the 6G era. By applying game theory, we aim to outline potential approaches for developing adaptive and intelligent pricing mechanisms suitable for next-generation networks.