Utility Optimization In Mobile Networks:From The View Of Network Externality

Humans in the 21st century have been living in the Information Age with the Internet as the core.With its outstanding characteristics and advantages of ubiquity,convenience,and intelli-gence,mobile networks have become a new space for people to study,work,and live,as well as an emerging and dynamic field of economic and social development.With people's increasing de-mand for high-quality mobile services,and concerns about privacy protection and security risks of mobile services,it is increasingly important to study the mechanism design of innovative mo-bile networks and optimize its overall utility,taking into account critical constraints,including 1)the resources limitation in the operation of mobile networks,2)the self-interest characteristic of individual network participants,3)the conflict between enhancing network performance and data privacy protection.At the same time,the effects of network externality are becoming more and more prominent with the enlarging scale of mobile networks.Researchers have made significant progress in studying the utility optimization and mechanism design in mobile networks,though there are still some deficiencies.For example,there is a lack of in-depth analysis and discussion from the perspective of network externalities in solving the problem of utility optimization;the consideration and characterization of the trade-off between optimizing network utility and individuals'privacy protection is insufficient;and existing incentive mechanisms are designed based on ideal rationality assumptions for the individuals' behaviors,which has limitations in its practical usageBased on the existing works on related topics,this thesis focuses on improving the utilities of different entities in the mobile networks from the perspective of the network externality.In particu-lar,utility optimization problems in three basic mobile networks scenarios,namely:the crowdsens-ing network,the spectrum sharing network,and the data services market,are studied.Accordingly,a privacy-preserving incentive mechanism,a privacy-preserving spectrum access mechanism and a data pricing mechanism are proposed as solutions to the above three problems.The results en-rich the theory of mobile network utility optimization and shed light on the design and practice of mobile network.The main contributions of the thesis are summarized as follows:1.Study the cost minimization problem of privacy-preserving mobile crowdsensing system un-der the single network externality effect.An auction based framework for privacy-preserving data aggregation is proposed while considering the conflict objectives of collecting data from mobile users and protect users' data privacy.Given the heterogeneity on mobile users' sens-ing capabilities and their unit privacy cost,this work carries out a local data perturbation scheme so that the privacy protection is provided and the data aggregation accuracy is satis-fied.The neg'ative network externality concerning the users' privacy-preserving level is then explicitly revealed.And two different settings,"privacy passive" setting and "privacy proac-tive" setting,are discussed separately which corresponds to two kinds of privacy-preserving attitudes.Based on the hidden monotonicity of the problem,two computational efficient incentive mechanisms,DPDA and EDPDA,are proposed satisfying the truthfulness and in-dividual rationality properties.By using the the proposed algorithms,the platform can ap-proximately minimize the cost under the aggregation accuracy constraint in both two settings.The performance of the algorithm is validated through extensive numerical experiments.2.Study the throughput maximization problem under the dual network externality effects within the context of locational privacy-preserving database-assisted spectrum sharing and propose a distributed spectrum sharing mechanism.Firstly,to mitigate RSS-based PH Y-layer location privacy threat,a power perturbation approach is employed where each secondary user judi-ciously "reduces" its transmission power by choosing a power level following a statistical dis-tribution(with a negative bias).Then the double impacts of network externality arc explicitly revealed:the mobile users jointly take into account their physical coupling(negative network externality due to the signal interference)and social coupling(positive network externality due to the social network effect)while making spectrum sharing decisions.Accordingly,the privacy-preserving spectrum sharing among users is cast as a stochastic channel selection game,where strategic players(secondary users)adjust their strategies dynamically aiming to solve a social group utility maximization(SGUM)problem.Specifically,a two-time-scale distributed learning algorithm based on no regret-based rule is devised,which is shown to converge almost surely towards the set of socially-aware correlated equilibrium.The numer-ical results corroborate that the higher the privacy protection level,the more significant the degradation of the network throughput would be.3.Study the revenue maximization problem for the wireless service providers in a competitive data service market under the dual network externality effects and propose a pricing mech-anism based on Stackelberg game model.Firstly,the two effects that influence the mobile users' data consumption behaviors are studied,namely:the network effect(positive network externality)and the congestion effect(negative network externality).To analyze the strategic interactions between mobile users and service providers,a two-stage Stackelberg game is de-vised,consisting of a providers' game in Stage ? and a users' game in Stage ?,respectively In particular,for the users' game,the equilibrium solution is characterized explicitly and its uniqueness is established.For the providers' game,the analysis indicates that a mixed-strategy equilibrium solution is guaranteed for the scenario with rational providers as well as the scenario with providers of bounded rationality.A distributed learning algorithm for finding a mixed-strategy equilibrium solution is further provided.And the numerical results provide insights into how positive network effect and congestion effect would impact the system performance,and demonstrate that the bounded rational behavior incurs degradation to service providers'revenues4.Explore the methodology of integrating network economics into the research of mobile net-working technology,and innovatively study the utility optimization problem of mobile net-work from the perspective of network externality.This thesis chooses three independent mobile network scenarios,reveals the network externalities and proposes network utility op-timization solutions accordingly.The results have shown that a deep understanding and ac-curate characterization of the network externality of mobile networks is necessary and indis-pensable for enhancing the feasibility of mechanism design and the effectiveness of utility optimization.Moreover,the results turn out to be an extension and enrichment of the research on the applications of network economic theory.In addition,the theoretical tools of game theory and mechanism design used in this thesis combine the cutting-edge results in related fields with mature theoretical models,and also pay attention to their applicability in the real scenarios of mobile networks.