Research On Pricing Strategy Of Crowdsourced WiFi Community Network Based On Evolutionary Game Theroy

In recent years,the amount of global mobile data has grown exponentially at an average annual rate of 47% in all over the world.But,the main carrier of mobile data services — cellular network,it has a much slower growth rate than data traffic.WiFi network has the advantages of low deployment cost and high data transmission rate.Therefore,the WiFi network plays an increasingly important role in making up for the shortage of traffic.However,WiFi networks also have many shortages,the most important one among them is that the coverage of a single WiFi access point(hotspots)is usually very limited: typically tens of meters indoors and hundreds of meters outdoors.Therefore,it is very expencive for a single operator to deploy enough WiFi access point to cover such large-scale area.Thus,the concept of WiFi community networks has emerged as a very promising way.WiFi community network is an effective way to solve the problem of insufficient coverage of wireless network,whose main idea is to encourage the individual users to join the community network and share their private WiFi access points for the roamers,meanwhile,he can use other people’s hotspots when he is roaming.This is,by the idea of crowdsourcing,we can collect multiple private WiFi access points and form a large community network.This way can make full use of existing private WiFi resource without the need of deploying large number of new WiFi hotspots,thus it can save a lot of cost and achieve flexible network deployment.It is clear that the success of the WiFi community network largely depends on an appropriate economic model and appropriate incentives mechanism.With this incentive mechanism,users will actively take part in this community and choose to share their private WiFi network,which is also the main thinking of this topic.We mainly studies two different WiFi community network scenarios: fixed WiFi community network scenario and mobile WiFi community network scenario.The former one mainly focuses on sharing fixed home WiFi access points,taking the common influence of users’ different network requirements and different family location advantages on user behavior decision-making into consideration;the latter one focuses on sharing mobile phone access points,analyzing the changing behaviors of mobile users who shares mobile phone hotspots,and explores the probability that users may connect to the Internet during the process of collisions and the number of users who may be served.Both scenarios are modeled on the new concept of “pay” and “reward”: when a user accesses to other people’s access points,he need to pay a certain fee,which will be eventually given to people who shares his or her WiFi access points as reward.Based on the above model,we transform the traditional incentive problem into a pricing strategy problem,and design a more flexible and versatile hybrid pricing strategy which combines both fixed monthly fee and usage-based charging methods.In addition,with the knowledge of game theory and numerical simulation technology,we characterizes the game evolution process of user clusters in the system and the final distribution of user types under equilibrium state.Then,we adjust the parameters of price and observe the influence of it to the system equilibrium point and social welfare,providing theoretical support for operators to make proper pricing strategies.