부산대학교 도서관

Mobile edge computing (MEC) can provide service requests and resource allocation for user equipments (UEs), effectively reducing service delay for massive Internet-of-Things (IoT). Application providers cache services in the edge servers to reduce service requests delay. However, limited channel resources will affect transmission delay and communication quality when UEs request services from edge servers, thus reducing the user's Quality-of-Experience. In this paper, we investigate the service offloading problem between UEs and base stations (BSs), as well as between BSs and remote data centers (RDCs) in MEC systems with heterogeneous networks, considering channel selection between UEs and BSs. To minimize the service delay of each UE and thus improve user satisfaction, we propose game theory to model the problem as a non-cooperative game of channel selection and then demonstrate the existence of Nash equilibrium (NE). In order to find the ideal channel selection scheme, this paper proposes a best response based on a multi-user service request channel selection (SRCS) algorithm. Simulation results reveal that the proposed channel selection mechanism can improve user satisfaction and verify the effectiveness and convergence of the proposed algorithm.