Task Offloading in IoT- Fog-Cloud Architecture using Crow Search Algorithm

Today, As Internet of Things (IoT) devices grow in number and diversity, they generate vast amounts of data. Due to the processing and storage limitations of these devices, the data is typically transferred to cloud servers. However, the distance between cloud servers and IoT devices can prevent real-time applications from functioning optimally. To address this, fog computing is employed to meet the processing and storage needs closer to the devices, thereby improving the quality of service (QoS) parameters like response time and energy consumption. While fog servers cannot replace cloud servers due to their limited resources, they complement them effectively. Energy consumption remains a significant challenge across IoT devices, fog, and cloud computing servers. Thus, efficient task distribution among fog nodes is crucial to enhance response time and energy efficiency. Task offloading in fog computing is an NP-hard problem, and metaheuristic algorithms are well-suited to address this challenge. This paper proposes a novel task offloading method using the Crow Search Algorithm (CSA), which optimizes energy and response time. Simulation results in MATLAB demonstrate the proposed method’s effectiveness in improving these parameters.