Research On Energy Consumption And Computation Efficiency Optimization Of Secure Communication In Mobile-Edge Computing Networks

In mobile edge computing(MEC),computing-intensive or delay-sensitive tasks can be offloaded to the closest base station and are processed by the edge servers for achieving the ultra-low latency and ultra-low energy consumption of terminal equipment,extending the long battery life of terminal equipment.However,the computing resources of terminal devices and MEC servers are limited,and the information security threats are faced by task offloading,how to provide secure and effective services for terminal users with limited energy should be further research.Therefore,based on the above problems,this thesis focuses on the optimization of energy consumption and computation efficiency for secure communication in MEC networks,This thesis studies the resource allocation strategy for minimizing the weighted energy consumption of secure communication in MEC network with nonorthogonal multiple access(NOMA);the resource allocation strategy for maximizing secure computation efficiency(SCE)is proposed in MEC network based on massive multiple-input multiple-output(m MIMO).The main works are as follows:1)In order to solve with the energy consumption optimization problem of secure communication in MEC network and to improve the secure offloading of low energy consumption in MEC networks based on NOMA,the physical layer security(PLS)technology is introduced.By jointly optimizing transmission power,local computing tasks,confidentiality interruption probability,and introducing energy consumption weighting factors to balance transmission energy consumption and computing energy consumption,the weighted sum of system energy consumption is minimized.In the case of satisfying two user priorities,the solution of the transformed problem is obtained through an iterative optimization algorithm based on bisection search,and the optimal computing task offloading and power allocation are obtained.Simulation results show that the proposed algorithm can effectively reduce the energy consumption of the system.2)For the traditional MEC resource allocation strategy,only performance indicators such as maximizating computing rate,minimizing energy consumption,and minimizing the weight sum of energy and delay are considered,while secure communication and computation energy efficiency are ignored.In the MEC network based on m MIMO,the PLS technology is introduced to ensure the security of multiuser unloading,and the SCE is studied.First,the secure transmission rate under imperfect channel state information(CSI)is derived.On this basis,the SCE of the system is maximized by jointly optimizing the local computing frequency,offloading time,downloading time,the transmit power of user and base station.Generalized fractional programming theory is used to transform the original problem,and an iterative optimization algorithm based on successive convex approximation(SCA)is proposed to obtain the effective solution of the original problem,and power allocation is obtained.Simulation results show that the SCE of the proposed scheme is superior to that of the other schemes.