Privacy-aware service migration for edge computing in urban cities

Currently, to satisfy the increasing demands for the computing and network resources at the edge of networks, edge computing has emerged as an efficient paradigm for real-time resource provisioning. Due to the unbalanced resource requests of mobile devices in the urban cities, the edge computing nodes (ECN) easily suffers from the underload or overload resource usage. Thus, it is of great importance to devise rational and effective service migration strategies to guarantee the overall performance of edge computing in the urban city. However, during the service migration between ECNs, the privacy information in the services is detected by the network, which may lead to the privacy leakage. To avoid privacy leakage and provide favorable computation performance including load balance as well as transmission time, it is necessary to seek appropriate service migration routes. In this paper, an optimization problem is formulated to minimize the transmission time and the load balance while protecting the privacy data during the service migration. Then, a privacy-aware service migration method, named PSM, is proposed in this paper. Finally, numerous experiments and evaluations are conducted to confirm the effectiveness and efficiency of our designed method.