论文标题

游戏理论和进化优化方法应用于新兴计算环境中的资源分配问题:调查

Game theory and Evolutionary-optimization methods applied to resource allocation problems in emerging computing environments: A survey

论文作者

Rahmani, Fatemeh, Joloudari, Javad Hassannataj, Shamshirband, Shahab, Mostafavi, Seyedakbar

论文摘要

当今的智能计算环境,包括物联网,云计算和雾计算,使世界上许多组织都可以优化其有关时间和能耗的资源分配。由于用户利用资源的敏感条件以及数据的实时性质,全面且集成的计算环境尚未能够为适当的资源分配提供强大而可靠的能力。虽然,在低容量硬件资源系统中,传统的资源分配方法对于小规模的资源提供商来说是有效的,对于动态计算资源和获得资源的激烈竞争的复杂系统,它们没有能力开发和适应最佳的条件。为了解决这个问题,计算智能技术试图以最小的时间延迟和能耗来优化资源分配。因此,这项研究的目的是一项针对新兴计算环境中的计算智能方法的全面,系统的调查,该调查使用计算智能方法,以及根据最新的科学研究成就,包括云,雾和互联网。

Today's intelligent computing environments, including Internet of Things, cloud computing and fog computing, allow many organizations around the world to optimize their resource allocation regarding time and energy consumption. Due to the sensitive conditions of utilizing resources by users and the real-time nature of the data, a comprehensive and integrated computing environment has not yet been able to provide a robust and reliable capability for proper resource allocation. Although, traditional methods of resource allocation in a low-capacity hardware resource system are efficient for small-scale resource providers, for a complex system in the conditions of dynamic computing resources and fierce competition in obtaining resources, they do not have the ability to develop and adaptively manage the conditions optimally. To solve this problem, computing intelligence techniques try to optimize resource allocation with minimal time delay and energy consumption. Therefore, the objective of this research is a comprehensive and systematic survey on resource allocation problems using computational intelligence methods under Game Theory and Evolutionary-optimization in emerging computing environments, including cloud, fog and Internet of Things according to the latest scientific-research achievements.

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