Big Data-Based Content Delivery In D2D Networks

With the rapid update of current user equipment and the surge in demand for Internet services,the current base station's service load is exponentially increasing,which poses great challenges to the physical resources,communication resources and computing power of the base station.The problem of extended service response and possible interruption of video transmission to the user brings a poor user experience to games,audio and video services that pursue high-rate and low-latency,and is more suitable for wearable devices in the medical industry.It is about the life of a person.Therefore,it is urgent to study how to unload the services of the base station and realize high-reliability and low-latency communication.D2D communication,one of the key technologies of 5G,is receiving wide attention from academia.D2 D technology allows devices to bypass base stations and communicate directly with other devices that are adjacent to them.Therefore,the pressure on the cellular network can be effectively alleviated and the utilization of spectrum resources can be improved.And efficient and real-time data sharing services.The cache server can be deployed on the base station side to cache the hot content,and a certain policy is formulated according to the popularity of the content to distribute the content to the user,and the user caches the content by using its own powerful storage capability.When the user has content requirements,it can be directly obtained from its own memory or a neighboring D2 D user,thereby reducing the content acquisition delay and offloading the base station service.Therefore,content distribution research under D2 D communication is of great significance.Firstly,the thesis introduces the research background and significance of this thesis,expounds the purpose and significance of this research,and briefly introduces the research content of this thesis,and gives the organizational structure of this thesis.Then it briefly introduces the mathematical foundation and theoretical knowledge involved in this thesis,as well as the research status of D2 D communication and content distribution network,and summarizes the research status of big data applied to wireless communication.It provides a theoretical basis for the research of D2 D content distribution network.Aiming at the unloading rate and energy consumption of the existing content distribution methods,it is impossible to accurately customize the content distribution strategy according to the user's interest.A content distribution network architecture based on big data clustering is proposed to analyze user interest through big data technology.Customized content.Subsequently,a D2 D content distribution method that considers both the base station energy consumption and the base station service unloading rate is designed.The simulation results show that the performance of the method is significantly improved.According to the actual situation,the D2 D link may be interrupted due to user movement.The paper analyzes the user's mobile attribute according to the user activity data,and can introduce a more efficient content caching strategy by bringing the parameters representing the mobile attribute into the optimization function.And effectively prevent transmission interruption problems caused by mobility.The user obtains the content delay and the base station service unloading rate.The simulation shows that the method has smaller delay,higher unloading rate and more reliable D2 D link than the existing method.