论文标题
雾计算中的新型服务部署政策，考虑使用多物镜进化算法的可用性和雾化景观的程度
A Novel Service Deployment Policy in Fog Computing Considering The Degree of Availability and Fog Landscape Utilization Using Multiobjective Evolutionary Algorithms
论文作者
论文摘要
雾计算是实时和关键任务互联网（IoT）应用程序的有希望的范式。关于雾资资源的高分配，异质性和限制，应以分布式方式放置应用程序，以充分利用这些资源。在本文中，我们提出了一种线性公式，以确保应用程序服务的不同可用性要求，同时最大程度地利用雾资资源。我们还比较了三种多主体进化算法，即MOPSO，NSGA-II和MOEA/D，以在上述优化目标之间进行权衡。 IFOGSIM模拟器中的评估结果证明了所有三种算法的效率以及MOPSO算法在获得的目标值，应用截止日期满意度和执行时间方面的总体上更好的行为。
Fog computing is a promising paradigm for real-time and mission-critical Internet of Things (IoT) applications. Regarding the high distribution, heterogeneity, and limitation of fog resources, applications should be placed in a distributed manner to fully utilize these resources. In this paper, we propose a linear formulation for assuring the different availability requirements of application services while maximizing the utilization of fog resources. We also compare three multiobjective evolutionary algorithms, namely MOPSO, NSGA-II, and MOEA/D for a trade-off between the mentioned optimization goals. The evaluation results in the iFogSim simulator demonstrate the efficiency of all three algorithms and a generally better behavior of MOPSO algorithm in terms of obtained objective values, application deadline satisfaction, and execution time.
