Strategic Pricing and Resource Allocation: Framework and Applications

Enabled by ubiquitous broadband connectivity and seamless wireless connections, we have witnessed in the past few years the emergence of a plethora of wireless applications, ranging from data communications and social networking to the more recently wireless cloud computing. The growing tension between the exploding demand for such wireless applications and the increasingly scarce network resources (e.g., spectrum, power) has urged a rethinking of the service providers' pricing strategies and network resource management techniques to cope with potential threats of quality-of-service degradation and revenue decreases. Specifically, it has become of paramount importance for service providers to strategically redesign their pricing policies and to understand how various pricing policies will affect the service demand, competition in the market, as well as the network resource management.In this dissertation, I propose a novel framework to optimize a service provider's pricing policy as well as its network resource allocation decision for profit maximization, in the presence of self-interested participating users that strategically respond to the charged price to maximize their own benefits. Applicable to both static and stochastic environments, the proposed framework explicitly takes into account user heterogeneity, which is observed in a wide range of applications. Based on the framework, I investigate the problem of optimizing pricing and resource allocation for the service provider's profit maximization in various contexts, including cooperative relay networks, communications markets, online user-generated content platforms, and mobile cloud computing systems