Research On User Attribute-aware Mobile Social Network Edge Cache Strategy

With the rapid growth of mobile users and the ever-increasing size of Mobile Social Networks(MSNs),the data traffic in MSNs is growing exponentially,which brings tremendous pressure to mobile communication systems.To alleviate these pressures,edge cache technology,as one of the key technologies of the 5G mobile communication network,will be applied to mobile social networks.The edge cache technology can effectively reduce content access delay and improve the quality of user experience by caching popular content near the edges of users.However,there are some problems in edge cache technology,such as limited cache capacity of edge nodes,diversified user needs,and user selfishness.To solve these problems,it is necessary to conduct further research on edge cache technology in mobile social networks.Firstly,this thesis introduces the mobile social networks and its research hotspots.At the same time,it describes on the edge caching technologies and the edge caching strategies.Then,aiming at the problem of network congestion and user experience quality deterioration caused by the explosive growth of data traffic,an edge cache mechanism based on user-aware is proposed.This thesis predicts popular content in Macro cell in terms of the interest of user based on implicit semantic model.Small base station within identical macro cell cache data cooperatively,which updates local popular content based on the changing dynamically of content preference of user.In order to further reduce the content delivery delay,this thesis helps user to ascertain its best belonging interesting community based on the content preference,at the same time,the most appropriate user equipment(UE)is selected considering the caching willingness and caching ability,to cache data for other UEs in identical interesting community.The results show that the proposed mechanism outperforms the random cache and the most popular content caching algorithm,which improves the cache hit rate and reduces the transmission delay while enhancing the user experience quality.Furthermore,aiming at the selfishness of base stations and users and the unwillingness to consume their own resources to cache content for content requesters,an edge cache resource allocation strategy based on the incentive mechanism is proposed.Different social interest groups are formed based on the user's interests and social relationships.The macro base station quantifies the contribution of different social interest groups to the cache process according to the resource sharing and activity of users in the group,and then gives different incentives.At the same time,the macro base station sets the unit cache resource price,and each social interest group pays different incentives to the macro base station based on its cache resource demand.Finally,the distributed iterative method is used to obtain the optimal cache resource price of the macro base station and the optimal cache resource demand of the social interest group.The results show that the proposed strategy has lower content transmission delay and higher user experience quality compared to other cache resource allocation strategies.