Research On Resource Allocation And Computing Energy Efficiency Of Mobile Edge Networks

With the vigorous development of wireless communication technology,the explosive growth of computing-intensive applications,the increasing demand for computing resources by terminals,and the rapid rise in network computing energy consumption.Although the computing power and energy storage level of terminal equipment have been greatly improved,it is still unable to cope with the geometrically increased computing demand and energy consumption.Mobile Edge Computing(MEC)provides users with distributed computing services at the edge of the cellular network,which not only solves the computing pressure of terminal equipment,but also reduces the delay of business data transmission;Energy Harvesting(EH)technology is It can effectively alleviate the energy limitation problem of the terminal equipment and prolong the use time of the equipment.How to combine MEC and EH technologies to achieve low-latency,high-energy-efficient computing-based mobile services through efficient resource scheduling has become a challenging task for current mobile communication networks.Therefore,this thesis focuses on the efficient resource allocation of mobile edge networks,and proposes a low-latency and energy-efficient computing resource allocation scheme combining MEC and EH technologies.The research contents and main results are as follows:(1)The computing resource scheduling problem of MEC system based on task delay is studied,and a two-step computing resource optimal allocation scheme is proposed.For the multi-user task MEC offloading calculation scenario with limited delay,the resource allocation priority(weight)is given to the user task according to the calculation delay of the user task,and the weighted calculation is established with the goal of minimizing the total weighted calculation time and considering the user’s cost constraint.In order to solve the time optimization problem,a two-step computing resource allocation algorithm with initial allocation and compensation allocation is proposed.(2)The optimization problem of computing energy efficiency of MEC system based on energy harvesting is studied,and an iterative algorithm based on Dinkelbach method is proposed to realize energy efficient resource allocation.For the single-user task MEC scenario with both energy and delay constraints,considering that users use the time slot frame structure to perform periodic energy harvesting and task offloading calculations,the MEC system computing energy efficiency optimization problem is established under the dual constraints of calculation amount and delay.An iterative algorithm was proposed to solve the problem and obtained the transmission power of wireless power base station,user equipment transmission power,user equipment computing frequency,MEC server computing frequency and other parameters.optimal configuration.The simulation results show that the algorithm proposed in this paper can effectively improve the computational energy efficiency of the MEC system.The work in this thesis provides technical solutions and algorithm support for low-latency and energy-efficient resource management of mobile edge networks,and helps to solve the delay and energy constraints of MEC systems.