The foundation of urban computing and smart technology is edge computing. Edge computing provides a new solution for largescale\ncomputing and saves more energy while bringing a small amount of latency compared to local computing on mobile devices.\nTo investigate the relationship between the cost of computing tasks and the consumption of time and energy, we propose a\ncomputation offloading scheme that achieves lower execution costs by cooperatively allocating computing resources by mobile\ndevices and the edge server. For the mixed-integer nonlinear optimization problem of computing resource allocation and\noffloading strategy, we segment the problem and propose an iterative optimization algorithm to find the approximate optimal\nsolution. The numerical results of the simulation experiment show that the algorithm can obtain a lower total cost than the\nbaseline algorithm in most cases.
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