A Lightweight Energy-Efficient Technique for QoS Enhancement in Urban VFC for Intelligent Transportation System

Resource optimization, and quality of service (QoS) improvement, for real-time latency-sensitive applications, are the two major challenges in vehicular fog computing (VFC), due to constraint resources, and the temporal relevance of the results of queries. In this research work, a multi-objective optimization model is presented to optimize the latency, and resource utilization in VFC. A heuristic-based algorithm, the lightweight energy-efficient algorithm for quality-of-service (LEAQoS) to solve the MOO model and a novel concept of adaptive capacity tuning for the dynamic workload (ACT-DW) is proposed for optimizing the resource consumption and latency. The proposed technique enables dynamic resource provisioning in VFC, to process all the dynamically generated latency-sensitive requests at vehicular fog nodes (VFN). A novel and nature-inspired concept of publisher-subscriber at static fog nodes is proposed in this research work for the processing of algorithms, to conserve the scarce VFN resources for the processing of latency-sensitive requests. The simulation results on real-world data prove a significant improvement in latency, resource consumption, and QoS satisfaction ratio as compared to the state-of-the-art competing works. This proves the suitability and practical applicability of the proposed technique for latency-sensitive applications in VFC.