A Non-cooperative Game-Theoretic Framework for Sponsoring Content in the Internet Market

Data traffic demand over the Internet is increasing rapidly, and it is changing the pricing model between internet service providers (ISPs), content providers (CPs) and end users. One recent pricing proposal is sponsored data plan, i.e., when CP negotiates with the ISP on behalf of the users to remove the network subscription fees so as to attract more users and increase the number of advertisements. As such, a key challenge is how to provide proper sponsorship in the situation of complex interactions among the telecommunication actors, namely, the advertisers, the content provider, and users. To answer those questions, we explore the potential economic impacts of this new pricing model by modeling the interplay among the advertiser, users, and the CPs in a game theoretic framework. The CP may have either a subscription revenue model (charging end-users) or an advertisement revenue model (charging advertisers). In this work, we design and analyze the interaction among CPs having an advertisement revenue as a non-cooperative game, where each CP determines the proportion of data to sponsor and a level of credibility of content. In turn, the end-users demand for the content of a CP depends not only on their strategies but also upon those proposed by all of its competitors. Through rigorous mathematical analysis, we prove the existence and uniqueness of the Nash equilibrium. Based on the analysis of the game properties, we propose an iterative algorithm, which guarantees to converge to the Nash equilibrium point in a distributed manner. Numerical investigation shows the convergence of a proposed algorithm to the Nash equilibrium point and corroborates the fact that sponsoring content may improve the CPs outcome

Sponsored data with ISP competition

We analyze the effect of sponsored data platforms when Internet service providers (ISPs) compete for subscribers and content providers (CPs) compete for a share of the bandwidth usage by the customers. Our analytical model is of a full information, leader-follower game. ISPs lead and set prices for sponsorship. CPs then make the binary decision of sponsoring or not sponsoring their content on the ISPs. Lastly, based on both of these, users make a two-part decision of choosing the ISP to which they subscribe, and the amount of data to consume from each of the CPs through the chosen ISP. User consumption is determined by a utility maximization framework, the sponsorship decision is determined by a non-cooperative game between the CPs, and the ISPs set their prices to maximize their profit in response to the prices set by the competing ISP. We analyze the pricing dynamics of the prices set by the ISPs, the sponsorship decisions that the CPs make and the market structure therein, and the surpluses of the ISPs, CPs, and users. This is the first analysis of the effect sponsored data platforms in the presence of ISP competition. We show that inter-ISP competition does not inhibit ISPs from extracting a significant fraction of the CP surplus. Moreover, the ISPs often have an incentive to significantly skew the CP marketplace in favor of the most profitable CP

Analyzing coalitions in wireless heterogeneous networks and their economic aspects

The massive investment that is essential to implement a large area wireless network is one of the significant roadblocks that stops service providers from offering more affordable data services. The fact that the fast evolution of wireless technologies requires frequent updates of hardware and software also leads to higher capital expenditure and operation costs for the providers and subsequently to more expensive data plans for the end users. The implementation of suboptimal pricing schemes in today’s wireless market, which does not consider service level agreements and forces users to pay for both network connectivity and data transfer, is another reason to decrease the overall satisfaction of subscribers. In view of these issues our objective in this thesis is to study the proper pricing methods based on the reality of current market as well as to consider alternative options that can reduce the service costs of wireless providers are our objectives. We study the volume-based pricing which is the dominant method in cellular networks nowadays. We derive the optimal data plan parameters such as the data volume cap, price, and data rate. Considering the cost-reduction possibilities, we prove that a coalition of providers in which they can serve users of each other is a valid alternative that reduces the implementation costs of network expansion. We build our analysis based on the cooperation between heterogeneous providers and we consider the heterogeneity in both technology and service aspects. We avoid the models which consider a coalition of all providers since it forms a monopoly and is prohibited by regulatory entities. Hence, we study models of coalitional structures that include several sets of providers. In this way, users have the option to select their data plan based on the service offered by a coalitional set of providers that can have different technologies in their access network. Concerning the service-oriented heterogeneous networks, we track the directions of payments from the content providers (CP) to the service providers (SP) and finally to the end users and try to modify it based on social fairness. To do so, we analyze several content types based on subscriber usage patterns and we find the ones that can be offered with a different pricing method without causing profit loss to CP or SP. Our goal is to set a coalitional framework between CP and SP that can lead to a free unlimited access to particular content types. We show that such agreements, if set correctly, can increase the profit of CP and SP. Throughout this thesis, the analytical models are verified with numerical examples that are designed to simulate the real world scenarios