Smart admission control strategy utilizing volunteer-enabled fog-cloud computing

Fog computing has become an effective platform for computing delay-sensitive IoT tasks. However, the increased scalability of IoT devices (IDs$$ \mathrm{IDs} $$) makes it difficult for fog nodes to perform better. Volunteer computing (VC) has emerged as a supportive technology in which resource-capable ID$$ \mathrm{ID} $$s, such as computers and laptops, share their idle resources to compute the IoT tasks. However, in VC-based approaches, improper selection of volunteer nodes (VNs) may result in an increased failure rate and delay. To address these challenges, this work proposes a Smart Admission Control strategy utilizing volunteer-enabled Fog-Cloud computing (SAC-VFC). The VNs are selected based on grey TOPSIS ranking. The incoming tasks are classified based on priority and delay and then scheduled using the Improved Jellyfish Algorithm (IJFA). Smart gateway (SGW) and fog manager (FM) act as mediators for allocating tasks among voluntary, fog, and cloud resources. FM performs a similarity-based clustering of fog nodes using the enhanced Fuzzy C Means clustering (EFCM) algorithm to manage resources. Simulation study suggests the superior performance of SAC-VFC over peers under comparison in terms of average delay, average makespan, success rate of tasks and tasks satisfying the deadline metrics.

Automated summary

This work proposes a Smart Admission Control strategy utilizing volunteer-enabled Fog-Cloud computing (SAC-VFC) to address the challenges of improper selection of volunteer nodes (VNs) in volunteer computing (VC) approaches. The VNs are selected based on grey TOPSIS ranking and tasks are scheduled using the Improved Jellyfish Algorithm (IJFA). Simulation study suggests the superior performance of SAC-VFC over peers in terms of average delay, average makespan, success rate of tasks, and tasks satisfying the deadline metrics.