An Efficient Computing Offloading Scheme Based on Privacy-Preserving in Mobile Edge Computing Networks

Abstract

Computation offloading is an important technology to achieve lower delay communication and improve the experience of service (EoS) in mobile edge computing (MEC). Due to the openness of wireless links and the limitation of computing resources in mobile computing process, the privacy of users is easy to leak, and the completion time of tasks is difficult to guarantee. In this paper, we propose an efficient computing offloading algorithm based on privacy-preserving (ECOAP), which solves the privacy problem of offloading users through the encryption technology. To avoid the algorithm falling into local optimum and reduce the offloading user energy consumption and task completion delay in the case of encryption, we use the improved fast nondominated sorting genetic algorithm (INSGA-II) to obtain the optimal offloading strategy set. We obtain the optimal offloading strategy by using the methods of min-max normalization and simple additive weighting based on the optimal offloading strategy set. The ECOAP algorithm can preserve user privacy and reduce task completion time and user energy consumption effectively by comparing with other algorithms.