Research On Resource Management In Mobile Edge Computing Environment Based On Multi-Base Stations Cooperation

Mobile edge computing gives cellular network edge devices,base station computing and storage capabilities.Mobile terminals can migrate their tasks to these devices for assistant processing,thereby improving task processing efficiency and reducing mobile terminal energy consumption.As one of the core technologies of mobile edge computing,resource management technology has important research value.Research on integration and optimization of computational storage resources for multi-base station cooperation is relatively scarce.The existing research mainly focuses on single base station scenario,and optimizes the computing and storage resources in isolation,without fully considering the impact of operator revenue on the system.Firstly,the deployment of mobile edge computing service and information interaction mode in multi-terminal and multi-smart base station environment are studied in depth.The operation mechanism of computing migration and data caching is established,and the system architecture and cooperative resource management algorithm based on multi-base station cooperation are designed.Secondly,a resource management scheme for minimizing overall task processing delay is proposed.In this thesis,the characteristics of various mobile terminal tasks are abstracted as ordered vectors,and the characteristics and signal transmission rate of each component of the system are quantified.The optimization problem for overall task processing delay is decomposed into two parts:computing delay and transmission delay,and modeled separately.The optimization algorithm based on genetic algorithm is combined with resource management algorithm based on multi-base station cooperation.The simulation work revolves around the different values of different parameters.The results show that the overall task processing delay of the proposed scheme is significantly reduced compared with the two schemes which do not have the function of mobile edge computing and data caching.Finally,this thesis proposes a resource management scheme for maximizing the revenue of mobile operators.Under the premise of satisfying the user satisfaction boundary,the overall revenue problem is decomposed into five parts:transmission cost,computing cost,cache cost,computing revenue and cache revenue.The model is built separately.The user satisfaction is abstracted as task processing delay,and the operation and maintenance cost and revenue of mobile edge computing smart base station are abstracted as unit cost and revenue.Finally,the corresponding optimal resource management algorithm is designed and simulated.Compared with the scheme that the data caching function is not turned on,the overall revenue of mobile operators is significantly increased.The proposed resource management schemes for minimizing overall task processing delay and maximizing revenue for mobile operators improve system performance and revenue,and contribute to the research work of mobile edge computing resource management technology.