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The proliferation of Internet of Things (IoT) devices and other IT forms in almost every area of human existence has resulted in an enormous influx of data that must be managed and stored. One viable solution to this issue is to store and handle massive amounts of data in cloud environments. Real-time data analysis has always been critical. However, it becomes even more crucial as technology and the IoT develop, and new applications emerge, such as autonomous cars, smart cities, and IoT devices for healthcare, agriculture, and other industries. Given the massive volume of data, moving to a remote cloud is time-consuming and produces severe network congestion, rendering cloud administration and rapid data processing difficult. Fog computing provides close-to-device processing at the network&#x2019;s periphery, and fog computing can analyze data in near real-time. However, the increased amount of IoT gadgets and data they produce is a formidable challenge for fog nodes. Task offloading may enhance fog computing by offloading the excess data to other nodes for processing due to the restricted resources in the fog. Management of tasks and resources must be optimized in fog devices. This review article overviews related works on task offloading in IoT-Fog-Cloud Environment. In addition, we discuss about fog networks and Software-defined network (SDN) applications and challenges in fog offloading.

Fog Offloading and Task Management in IoT-Fog-Cloud Environment: Review of Algorithms, Networks and SDN Application.