Research On Cooperative Cache Strategy In Cellular Internet Of Things

The Internet of Things is one of the important application fields of 5 th generation mobile networks communication technology.With the emergence of new services such as smart cities,smart power grids and autonomous driving,mobile communication networks need to meet the demand of massive connectivity,high reliability and low latency.Faced with these requirements,mobile edge cache becomes an important research direction in cellular Internet of Things.By caching the Internet of Things data on the intermediate nodes of the network transmission layer,network traffic can be effectively reduced,and equipment energy consumption and user delay can be reduced.However,due to the limitations of a single cache node,cache utilization is low.In order to allocate cache resources reasonably,the collaboration between cache nodes has become one of the most promising techniques.How to carry out collaborative caching in cellular Internet of Things is an important research direction of Internet of Things technology.There are two challenges in studying collaborative caching technology in the Internet of Things.On the one hand,IoT devices are usually battery-powered,and working hours are limited by battery capacity.At the same time,IoT data has real-time characteristics,and caching will reduce the timeliness of data.On the other hand,with the exponential growth of IoT devices,the cold start data generated by new devices also affects the latency of user access.Although the active cache has excellent performance,it is limited by its interval update characteristics and cannot cache cold start data.Therefore,this article studies the two challenges of introducing collaborative caching technology in the Internet of Things.First,a collaborative caching strategy based on data life cycle is proposed to minimize the energy consumption of IoT devices.Firstly,the data life cycle is defined according to the timeliness of the data,the access rate of the federated users and the life cycle of the data are screened out to be cached.Secondly,in a layered cellular Internet of Things architecture,small base stations and macro stations are combined to optimize resource allocation and content placement.Then,the mathematical model is established and solved with the goal of minimizing the energy consumption of iot devices.According to the data life cycle,user access rate and data size,two heuristic algorithms are proposed to meet the requirements of different scenarios.Finally,simulation results show that the proposed scheme can dynamically adapt to the change of request rate and can effectively save energy consumption of IoT devices.Secondly,a cooperative caching strategy based on data cold start is proposed to minimize the delay.Firstly,it describes the common cold startup problem in the Internet of Things scenario.Caching strategies are implemented through the cooperation between small base stations and macro stations,and cache replacement strategies are implemented according to the popularity of data and real-time performance.Secondly,a novel hybrid caching strategy is designed for two different types of data.The cache space of the network intermediate node is divided into two parts.For hot data with historical records,deep learning is used to predict the popularity of the content in the future moments for caching.For cold startup data with no history,an improved passive caching algorithm is used to cache.The combination of the two can not only guarantee cache performance,but also solve the problem of cold data startup.Finally,simulation results show that the hybrid cache can process both hot data and cold startup data,improve cache hit ratio and reduce user access delay.