SDTS: Security Driven Task Scheduling Algorithm for Real-Time Applications Using Fog Computing

Abstract

Nowadays, security and scheduling have become more critical issues of rapidly increasing applications running in real-time systems. In this work, we tried to solve these intricate issues and develop a security-driven task scheduling algorithm for real-time applications using Fog computing, which is abbreviated as SDTS. It works for the enhancement of both the security and scheduling services of real-time applications. SDTS is the integration of various proposed algorithms that are modified quadratic search algorithm, Min_Heap algorithm, and modified Earliest Deadline First (m-EDF). In which, modified quadratic search, Min Heap algorithm, and m-EDF algorithms are used for evaluating the average security value of tasks, optimal nodes using Fog computing, and task selection according to their absolute deadlines, respectively. The quantitative results analysis shows that the proposed model outperforms the existing models in terms of guarantee ratio (rate of success), average security value, and overall performance, i.e. 7.4% for success ratio, 7.69% for average security value, and 1.02% for overall performance in comparison to traditional methods.