PaF & MbOTS: Novel Task Scheduling Strategies for Fog Computing Environment

Task scheduling in cloud-fog architectures is a critical concern, necessitating prioritising latency-sensitive tasks with efficient resource utilization in order to enhance quality metrics. Effective task scheduling in the fog environment is crucial for mitigating issue of elongated response time and execution delay. The paper delves into these mentioned complexities of task scheduling by proposing a optimal schemes for efficient allocation of latency-sentive tasks to capable fog nodes in the fog environment. The work introduced two novel algorithms; Firstly, Promotion as Fog (PaF) method promoting volunteer end nodes to fog nodes considering their static and dynamic state. Secondly, Matrix-based Optimal Task Scheduling (MbOTS) method prioritizing tasks based on specific parameters for optimal scheduling. The proposed work is implemented and validated which demonstrates its efficiency in terms of reducing total execution time with an average improvement of 15.12 %, reducing total waiting time with 14.3%, and execution delay with 2% as compared to existing methods.