Computation Bits And Secure Computation Efficiency Optimization For Mobile-Edge Computing Networks

Mobile edge computing(MEC)technology provides users with an important way to supply computing services with low latency and high computing performance.However,it faces two major technical challenges.Firstly,for mobile users with limited energy,it is difficult to enjoy MEC services for a long time.Secondly,mobile users face security threats when the computation tasks are offloaded to the MEC server.This paper studies the weighted sum computation bits maximization problem in order to obtain the optimal resource allocation strategy of the unmanned aerial vehicle(UAV)-enabled MEC wireless powered system,which improves the computing performance and energy harvesting efficiency.Under the MEC network with non-orthogonal multiple access(NOMA);the resource optimization strategy for maximizing secure computation efficiency is proposed to improve the secure computation efficiency.To tackle with the insufficient computing capability and limited energy storage of mobile devices,in the UAV-enabled MEC wireless powered system,by using the characteristics of MEC network and the characteristics of UAV easy to that is easy to deploy and can provide line-of-sight transmission,a weighted sum computation bits maximization problem is studied and the optimal resource allocation strategy is proposed.In the binary computation offloading mode,the weighted sum computation bits maximization problem is established,by jointly optimizing the central processing unit(CPU)frequency,offloading time and transmit power of users and the optimal operation selection scheme as well as the UAV trajectory.Since the established optimization problem is non-convex,a three-stage alternative optimization algorithm is proposed.Simulation results show that the proposed resource allocation scheme outperforms other benchmark schemes in terms of the weighted sum computation bits,and verify the trade-off between user priority and fairness,the convergence efficiency of the optimization algorithm.For the traditional MEC network resource allocation strategy,only maximizing computing rate or minimizing energy consumption are considered,and the security threats in the MEC network are not considered.This paper studies the problem of secure computation efficiency maximization in NOMA-enabled MEC networks.The physical-layer security is exploited to secure the multiuser computation offloading in order to not overhead by overheard by the eavesdropper.The secure computation efficiency optimization problem is formulated,by jointly optimizing the transmission power and CPU frequency.Since problem is non-concave and non-smooth that is difficult to solve,a low-complexity successive convex approximation iterative algorithm is proposed.Numerical results verify that the proposed schemes are superior to the traditional schemes in terms of the secure computation efficiency and our designed iteration algorithm's efficiency is verified.In summary,the research results on system models and resource optimization algorithms will provide reliable theoretical and technical support for the practical application of MEC.