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.

中文翻译：

---

边缘计算中的用户边缘协作资源分配和卸载策略

城市计算和智能技术的基础是边缘计算。与移动设备上的本地计算相比，边缘计算为大规模计算提供了新的解决方案，并节省了更多的能源，同时带来了少量的延迟。为了研究计算任务的成本与时间和能源消耗之间的关系，我们提出了一种计算分流方案，该方案通过移动设备和边缘服务器协同分配计算资源来实现较低的执行成本。对于计算资源分配和卸载策略的混合整数非线性优化问题，我们对该问题进行了细分，并提出了一种迭代优化算法来寻找近似最优解。