With the explosion of data traffic, mobile edge computing (MEC) has emerged to solve the problem of high time delay and energy\nconsumption. In order to cope with a large number of computing tasks, the deployment of edge servers is increasingly intensive.\nThus, server service areas overlap. We focus on mobile users in overlapping service areas and study the problem of computation\noffloading for these users. In this paper, we consider a multiuser offloading scenario with intensive deployment of edge servers. In\naddition, we divide the offloading process into two stages, namely, data transmission and computation execution, in which\nchannel interference and resource preemption are considered, respectively. We apply the noncooperative game method to model\nand prove the existence of Nash equilibrium (NE).Thereal-time update computation offloading algorithm (RUCO) is proposed to\nobtain equilibrium offloading strategies. Due to the high complexity of the RUCO algorithm, the multiuser probabilistic offloading\ndecision (MPOD) algorithm is proposed to improve this problem. We evaluate the performance of the MPOD algorithm\nthrough experiments. The experimental results show that the MPOD algorithm can converge after a limited number of iterations\nand can obtain the offloading strategy with lower cost.
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