Research On Centent Distribution And Base Station Sleep Management Algorithms In Edge Caching Networks

As the explosive growth of smart devices and new applications,traffic volume has been growing exponentially.With the increasing of traffic demands in future cellular networks,one promising approach is to deploy more small base stations(SBSs)along with macro base stations(MBSs).In order to further improve the network performance,some researchers suggest caching files into the base stations on the edge of the network.The files could be closer to users,and the download delay is reduced by this way.So the user experience would be improved.Thus the edge caching network appears and has attracted extensive attention of academia.However,the storage capacity of these SBSs is usually limited.In this case,one SBS could not cache all the files that the users may need.There are many aspects should be considered when designing a caching scheme.With the limited storage,how to decide whether or not to store a file in a SBS depends on not only the file's popularity and hit rate,but also users' experience like transmission delay.Moreover,the energy consumption of the network is a problem worth studying as well with so many SBSs deployed.SBS sleeping is an effective way to save energy consumption.However,there may be many challenges in the edge caching network with limited storage SBSs when considering many factors like content distribution.In this paper,the above problems are studied,and the main works are as follows:Firstly,we propose a minimizing user download delay caching algorithm.The conflict between hit rate and download delay with the limited SBS storage capacity is fully considered and weighed.An optimizing strategy is established to minimize the user average download delay when meeting a certain user average hit rate.In the strategy,all the files are ranked by their popularity.All the SBSs pre-store the files according to the serial number.The hit rate of each user could be calculated with the connection status between this user and all SBSs.Then we may get the expression of the average hit rate of all users.The user average download delay is expressed by utilizing the network parameters and the connection states of SBSs.We establish an optimization mathematical model of the caching problem and find the optimal solution through the traversing method.The simulation results show that the average user download delay is reduced.Secondly,we propose a content fragmentation storage-based SBS sleeping algorithm.Each SBS will randomly store a part of each file.We establish the connection state matrix for users and the active SBSs according to the SBS working state and user connection.The request probability of each file is calculated by Zipf law.Then the file transfer energy consumption could be expressed.The energy consumption used to maintain SBSs working would be established on the basis of SBSs working states.We model the energy consumption into a two-dimensional problem and find a solution to optimize it.The simulation results show that the energy consumption is reduced and the hit rate is improved.