This work investigates the dynamical weighted deployment of mobile fog computing devices to support a mobile edge computing environment, in which each edge device is associated with a weight to reflect its importance based on the application. Since edge devices are mobile and could be switched off, it is challenging to dynamically optimize the deployment to adapt to dynamic change. This work further models the problem mathematically and solves it by a bat-inspired algorithm (BA), which searches the optimal solutions by simulating the food-searching behavior of bats via echolocation. Furthermore, three local search methods designed specifically for this problem are integrated into the BA, and a dynamic local search selection mechanism is proposed to adjust the probabilities of choosing the three local search methods iteratively in the BA main loop. Simulation results show outperformance of the proposed BA over the BA without local search and the previous approach.

这项工作研究了移动雾计算设备的动态加权部署以支持移动边缘计算环境，在该环境中，每个边缘设备都与权重相关联，以根据应用程序反映其重要性。由于边缘设备是移动设备，可以关闭，因此动态优化部署以适应动态变化是一项挑战。这项工作进一步对问题进行了数学建模，并通过蝙蝠启发算法（BA）解决了该问题，该算法通过回声定位模拟蝙蝠的食物搜索行为来搜索最佳解决方案。此外，针对该问题专门设计的三种本地搜索方法已集成到BA中，并提出了一种动态本地搜索选择机制，以调整在BA主循环中迭代选择这三种本地搜索方法的可能性。