Dual-Constraint Based Task Scheduling and Secure Offloading in Triune Layered Fog Assisted IoT Environment
Pratibha Sharma, Hemraj Saini, Arvind Kalia · 2023
Fog computing has been addressed as one of the prime candidates for Internet of Things (IoT) applications in near future. Task management in the large-scale network is the chief research issue in the fog assisted IoT environment. Many research works have been undertaken in task scheduling and offloading in the fog-IoT environment. However security issues in fog task management need to be take into consideration. To be precise, the fog resources are likely to be used by the unauthorized users in recent times. In this paper, we address this above issue and resolve through our novel secure triune layered (Sec-TriL) architecture. A novel triune layer is constructed with device layer, fog layer and cloud layer. In the device layer, Two-Fold Physically Unclonable Function (TF-PUF) approach is presented with the Montgomery Curve Encryption (MCE) to identify the authorized users. In next layer, the fog nodes are arranged in the Hybrid Start Peer-to-Peer (HyS-P2P) topology to manage the fog resources. The tasks from authorized users are scheduled to fog nodes on the basis of Priority-aware Adaptive Scheduling (PAS) protocol that is operated with the Adaptive Threshold Function Cross Entropy (ATFXE) queue management policy. When the fog layer suffers with overloading problem, the super fog node initiates Dual-Constraint Teaching Learning based Optimization (DC-TLBO) for task offloading upon task-oriented constraints and fog-oriented constraints. To evaluate the performance of the proposed work, the overall work is implemented in iFogSim simulator. The observations are made on time efficiency (response time, delay, offloading time), throughput and energy consumption show promising results in fog-assisted IoT environment.