Research On Energy Consumption Optimization Method With Hybrid Collaborative NOMA For Secure MEC

In recent years,mobile edge computing has shifted from centralized mobile cloud computing to a paradigm that pushes computing,network control,and storage to the network edge(base stations and access points).This shift is driven by the vision of the Internet of Things(Io T)and 5G communication.Mobile edge computing enables computationally intensive and latency-sensitive applications on mobile devices with limited resources.By reducing latency and energy consumption,mobile edge computing addresses the challenges of realizing the 5G vision.At the same time,the widespread application of non-orthogonal multiple access(NOMA)has also liberated the traditional physical layer security constraints on the transmission rate of each user,which followed by the increase of complexity and system energy consumption.To address the increasing demands of user devices,combining mobile edge computing with NOMA can solve many of the problems that emerging applications face in the current scenario.Therefore,this thesis investigates the design of an information security optimization scheme based on the combination of mobile edge computing and NOMA,and the specific content is as follows:(1)Aiming at reducing latency and preventing eavesdropping,a secure mobile edge computing transmission method is proposed by using a hybrid cooperative non-orthogonal multiple access(NOMA)with energy efficiency optimization.The proposed method designs a multi-slot hybrid cooperation scheme for the data processing process of each user,setting different offloading decisions based on the strength of different user’s channel gains,in order to optimize the total energy consumption of the system while ensuring fairness among users.A closed-form expression for the system’s secrecy outage probability is derived,and the optimization problem is decomposed into three sub-problems.Finally,the system energy consumption is minimized within the deadline delay by cyclic iterations of the block coordinate descent algorithm and with the goal of minimizing the system energy consumption.Simulation results demonstrate that the proposed transmission approach can effectively reduce system energy consumption while ensuring information security,under the premise of reasonable timeslot allocation.(2)To address the significant data processing demands of computation-intensive services in the mobile edge computing combined with non-orthogonal multiple access networks,while ensuring information security and orderly handling of bursty events and special requirements,an energy optimization scheme is proposed with the assistance of friendly jamming for offloading a large amount of data.The optimization takes into consideration the worst-case scenario,where information security rate,secrecy outage probability,and transmit power are combined to optimize the total energy consumption of the system.A semi-closed expression for the correlation between the auxiliary interference power and the unloading power is also derived;finally,the nonconvex optimization problem is divided into four subproblems by a block coordinate descent algorithm,and better performance is achieved compared to that when no auxiliary interference is introduced.The simulation results show that the total system energy consumption can be further reduced by dynamically changing the unloading decision when the system is handling a large amount of input tasks while ensuring information security.