M-SOS : Mobility-Aware Secured Offloading and Scheduling in Dew-Enabled Vehicular Fog of Things

Rajareddy, Goluguri N. V. and Mishra, Kaushik and Majhi, Santosh Kumar and Sahoo, Kshira Sagar and Bilal, Muhammad (2025) M-SOS : Mobility-Aware Secured Offloading and Scheduling in Dew-Enabled Vehicular Fog of Things. IEEE Transactions on Intelligent Transportation Systems. ISSN 1524-9050

Text (M_SOS_Mobility-aware_Secured_Offloading_and_Scheduling_in_Dew-enabled_Vehicular_Fog_of_Things)
M_SOS_Mobility-aware_Secured_Offloading_and_Scheduling_in_Dew-enabled_Vehicular_Fog_of_Things.pdf - Accepted Version
Available under License Creative Commons Attribution.
Download (940kB)

Abstract

The gradual advancement of Internet-connected vehicles has transformed roads and highways into an intelligent ecosystem. This advancement has led to a widespread adoption of vehicular networks, driven by the enhanced capabilities of automobiles. However, managing mobility-aware computations, ensuring network security amidst instability, and overcoming resource constraints pose significant challenges in heterogeneous vehicular network applications within Fog computing. Moreover, the latency overhead remains a critical issue for tasks sensitive to latency and deadlines. The objective of this research is to develop a Mobility-aware Secured offloading and Scheduling (M-SOS) technique for a Dew-enabled vehicular Fog-Cloud computing system. This technique aims to address the issues outlined above by moving the computations closer to the edge of the network. Initially, a Dew-facilitated vehicular Fog network is proposed, leveraging heterogeneous computing nodes to handle diverse vehicular requests efficiently and ensuring uninterrupted services within the vehicular network. Further, task management is optimized using a Fuzzy logic that categorizes tasks based on their specific requirements and identifies the target layers for offloading. Besides, a cryptographic algorithm known as SHA-256 RSA enhances security. Moreover, a novel Linear Weight-based JAYA scheduling algorithm is introduced to assign tasks to appropriate computing nodes. The proposed algorithm surpasses the comparable algorithms by 23% in terms of AWT, 18% in terms of latency rate, 14% and 23% in terms of meeting the hard-deadline (H_d) and soft-deadline (S_d), and 35% in terms of average system cost, respectively.