Recently, fog computing has been introduced as a modern distributed paradigm and complement to cloud computing to provide services. The fog system extends storing and computing to the edge of the network, which can remarkably solve the problem of service computing in delay-sensitive applications besides enabling 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 parameters such as resource utilization, throughput, cost, response time, performance, and energy consumption can be improved by load balancing. In recent years, some research in load balancing algorithms in fog networks has been carried out, but there is no systematic study to consolidate these works. This article investigates the load-balancing algorithms systematically in fog computing in four classifications, including approximate, exact, fundamental, and hybrid algorithms. Also, this article investigates load balancing metrics with all advantages and disadvantages related to chosen load balancing algorithms 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 algorithms are discussed.

中文翻译：

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雾计算中的负载均衡算法


最近，雾计算作为一种现代分布式范式被引入，并作为云计算的补充来提供服务。雾系统将存储和计算延伸到网络边缘，除了实现位置感知和移动性支持之外，还可以显着解决延迟敏感应用中的服务计算问题。负载均衡是雾网络的一个重要方面，可以避免某些雾节点负载不足或过载的情况。资源利用率、吞吐量、成本、响应时间、性能和能耗等服务质量参数可以通过负载平衡来提高。近年来，人们对雾网络中的负载均衡算法进行了一些研究，但还没有系统的研究来巩固这些工作。本文系统地研究了雾计算中的负载均衡算法，分为近似算法、精确算法、基本算法和混合算法四类。此外，本文还研究了负载平衡指标以及与雾网络中所选负载平衡算法相关的所有优点和缺点。还探讨了每项审查研究所采用的评估技术和工具。此外，还讨论了这些算法的基本开放挑战和未来趋势。