Load Balancing Approaches in Cloud and Fog Computing Environments: A Framework, Classification, and Systematic Review

Cloud and fog computing are modern technologies that handle multiple dynamic user requests. Cloud provides demand-based services to users over the internet on pay-as-you-go basis. Fog handles real-time requests that are received from smart devices. Millions of requests arrive at the cloud-fog layer, often leading to overloaded virtual machines (VMs). Load balancing (LB) is an important issue for cloud-fog systems and has been proved to be an NP-hard problem. It is essential as it distributes the load equally among VMs to properly utilize resources and improve quality of service (QoS). Therefore, this paper presents a complete classification of LB algorithms and also a comprehensive study using heuristic, meta-heuristic, and hybrid approaches in cloud and fog computing environments. The main goal of this paper is to highlight the importance of LB to overcome the challenges of the systems. This study reviews papers of the last seven years and systematically discusses them using various tables and pie charts. Finally, the paper concludes with the research gaps and future insights.