Research On Collaborative Edge Cache Strategy

With the rapid growth of mobile video traffic,the base station and core network links are under tremendous pressure.The surge in wireless traffic makes it difficult for existing mobile networks to meet users' needs for high-bandwidth,low-latency cache services.The mobile edge cache technology that provides super cache services on the edge side is considered to be an effective method to solve this problem,and has been studied by many domestic and foreign scholars.However,the storage space of devices such as base stations and servers at the edge of the network is limited.Therefore,how to effectively cooperate with the caching equipment and use limited cache resources to provide users with higher-quality video caching services is a problem that needs to be solved.With the rapid development of emerging self-media applications such as Douyin and Kuaishou,a large number of user-generated content(UGC)with obvious geographical and social attributes continue to emerge.Their popular models and traditional occupationally generated content(Occupationally Generated Content,OGC)has a big difference,further increasing the difficulty of video caching and updating.At the same time,there are also problems of insufficient user demand and dynamic content value perception,and high transmission energy consumption in the collaborative caching.In response to the above problems,the thesis proposes a collaborative cache placement strategy based on regional user demand perception and a collaborative update scheme based on dynamic content value perception.The main research contents are as follows:Firstly,to address the problems of high transmission energy consumption and insufficient user demand perception in current edge caching strategies,this thesis proposes a collaborative cache placement strategy based on regional user demand perception.First,based on the regional user's long-term and short-term interests and existing network-wide popularity information,estimate the potential request willingness of the regional users;then,the thesis selects the content to be cached and the cache priority based on the regional users' interest and activity.Finally,this thesis designs a collaborative placement strategy to optimize the energy consumption of the regional cache which considering the difference between the location information of the base stations in the area and the needs of users,under the MEC collaborative cache architecture.Simulation results show that the proposed strategy has a certain increase in request hit rate,bite hit rate and cache energy consumption compared with the traditional cache strategy.Secondly,in view of the insufficient value perception of cache content and the difficulty of updating cache caused by the popularity difference between OGC content and UGC content,a cache update strategy based on dynamic content value perception is proposed.This strategy firstly perceives and evaluates the cache value of content based on user preferences and feedback to the content.Then select the cached content based on the expected cache value of the content.Finally,this thesis taking the cache update gain of content as a reference goal,optimize the replacement and update of cache content and optimize the replacement and update of cache content.Simulation results show that the proposed strategy has better performance in terms of hit rate than the comparison scheme.