Abstract
After upgrading to 5G, a network operator still faces congestion when providing the ubiquitous wireless service to the crowd. To meet users’ ever-increasing demand, some other operators (e.g., Fon) have been developing another crowdsourced WiFi network to combine many users’ home WiFi access points and provide enlarged WiFi coverage to them. Besides, to meet users’ ever-increasing demand on information, online content platforms are concerned about the freshness of their content updates to their end customers, and increasingly more platforms now invite the crowd to sample real-time information (e.g., traffic observations and sensor data) to help reduce their ages of information (AoI). In this thesis, we investigate economics of competition in such entities under negative and positive network externalities. Regarding co-exisiting 5G and crowdsourced WiFi networks with diverse network externalities, we propose a dynamic game theoretic model to analyze the hybrid interaction among the 5G operator, the crowdsourced WiFi operator, and users. Our user choice model with WiFi’s complementarity for 5G allows users to choose both services, departing from the traditional economics literature where a user chooses one over another alternative. Despite of non-convexity of the operators’ pricing problems, we prove that the 5G operator facing severe congestion may purposely lower his price to encourage users to add-on WiFi to offload, and he benefits from the introduction of crowdsourced WiFi. Regarding competing AoI platforms under negative network externalities, when these selfish platforms know each other’s sampling cost, we formulate their competition as a non-cooperative game and show they want to over-sample to reduce their own AoIs, causing the price of anarchy (PoA) to be infinity. To remedy this huge efficiency loss, we propose a trigger mechanism of non-monetary punishment in a repeated game to enforce the platforms’ cooperation to approach the social optimum. We also study the more challenging scenario of incomplete information that some new platform hides its private sampling cost information from the other incumbent platforms in the Bayesian game, and a trigger mechanism under incomplete information is proposed to approach the social optimum.