| With the rapid development of mobile social networks and the increasing number of video content providers,the demand for data traffic in wireless mobile networks has exploded,and the multimedia demand of mobile devices has become the main driving factor for the explosion of mobile video streaming.In order to reduce transmission delay and improve user experience,using base stations to cache video streams in advance is an optional solution.However,designing a separate cache scheme for each base station is not only troublesome but also can not make full use of cache resources.To address these challenges,researchers propose collaborative caching schemes to improve network performance.Compared with non-cooperative caching,cooperative caching improves cache utilization.However,due to the highly dynamic network conditions and the heterogeneity of user processing capabilities,users have different preferences and demands for specific video quality and format,which further increases the difficulty of video caching.In this paper,the decision scheduling of video cache in a heterogeneous MEC network consisting of one macro station and several small base stations is studied.Aiming at the problem of minimizing user access delay in edge computing,this paper studies the adaptive video cache cooperation strategy in heterogeneous mobile edge computing networks.With the goal of minimizing delay,the problem is formalized into the caching decision and scheduling problem in heterogeneous edge computing networks,which is used to determine the location of each video variant in the cache and the scheduling of video requests to the cache server.The original problem is divided into two problems: cache placement problem and request scheduling problem by divide-and-conquer method.In the cache placement problem,the problem is reduced to solving the monotone submodel maximum problem.In the request scheduling problem,the problem is solved by the online knapsack algorithm.A large number of simulation results show that the proposed joint cache and processing framework provides at least 10.2%,16.3%,and 21.8% performance improvements in cache hit ratio,backhaul traffic load,and average access latency,respectively.Aiming at the problem of minimizing user access delay in edge computing,this paper studies the adaptive video cache cooperation strategy in heterogeneous mobile edge computing networks.With the goal of minimizing delay,the problem is formalized into the caching decision and scheduling problem in heterogeneous edge computing networks,which is used to determine the location of each video variant in the cache and the scheduling of video requests to the cache server.The original problem is divided into two problems: cache placement problem and request scheduling problem by divide-and-conquer method.In the cache placement problem,the problem is reduced to solving the monotone submodel maximum problem.In the request scheduling problem,the problem is solved by the online knapsack algorithm.A large number of simulation results show that the proposed joint cache and processing framework provides at least 10.2%,16.3%,and 21.8% performance improvements in cache hit ratio,backhaul traffic load,and average access latency,respectively. |
