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