Recently, fog computing has been introduced as a modern distributed paradigm and complement to cloud computing to provide services. Fog system extends storing and computing to the edge of the network, which can solve the problem about service computing of the delay-sensitive applications remarkably besides enabling the location awareness and mobility support. Load balancing is an important aspect of fog networks that avoids a situation with some under-loaded or overloaded fog nodes. Quality of Service (QoS) parameters such as resource utilization, throughput, cost, response time, performance, and energy consumption can be improved with load balancing. In recent years, some researches in load balancing techniques in fog networks have been carried out, but there is no systematic review to consolidate these studies. This article reviews the load-balancing mechanisms systematically in fog computing in four classifications, including approximate, exact, fundamental, and hybrid methods (published between 2013 and August 2020). Also, this article investigates load balancing metrics with all advantages and disadvantages related to chosen load balancing mechanisms in fog networks. The evaluation techniques and tools applied for each reviewed study are explored as well. Additionally, the essential open challenges and future trends of these mechanisms are discussed.
翻译:最近,雾计算作为一种现代分布式模式被引入,并补充云计算提供服务。雾计算系统将储存和计算扩展至网络边缘,这可以解决延迟敏感应用的服务计算问题,除了提供定位意识和移动支持之外,还可以显著解决延迟敏感应用的服务计算问题。负载平衡是雾网络的一个重要方面,避免了某些载量不足或超载雾节点的情况。服务质量(Qos)参数,如资源利用、吞吐量、成本、反应时间、性能和能源消耗,可以通过负载平衡来改进。近年来,对雾网络负荷平衡技术进行了一些研究,但没有进行系统审查,以合并这些研究。文章回顾了雾计算过程中系统化的负载平衡机制,分为四种分类,包括近似、精确、基本和混合方法(2013年至2020年8月出版)。此外,文章还探讨了与雾网络选择的负载平衡机制相关的所有利弊平衡度和劣因素。此外,还探讨了每项审查研究所采用的评估技术和工具。此外,还讨论了这些机制的基本公开挑战和未来趋势。