A Systematic Review of Task Offloading & Load Balancing Methods in a Fog Computing Environment: Major Highlights & Research Areas

Abstract

Fog computing allows for the availability of services and resources exterior of the computing resources, closer to end devices on the network edge, and finally at regions mandated by service level agreement. Fog nodes along with deployed Cloud is a strong additional support for computation. It allows for processing at the edge while yet allowing for cloud interaction. A crucial component of fog networks is load balancing, which put off some fog nodes from getting unutilized or extra loaded. Load balancing can improve service quality (QoS) factors such latency, resource usage, throughput, response or execution time, cost incurred and energy consumed for passive nodes. The job offloading and load redistribution strategies which are used in a fog network are reviewed in detail in this study. The review is divided into two categories: single parameter optimization algorithms and multi-objective parameter optimization algorithms, both with their suggested ideas. The review is also analysed in various ways, including the proportion of articles published by publisher, methods based on optimization parameters, performance evaluation metrics, simulation evaluation tools, and upcoming research areas in the fog computing field.