Intelligent Cloud Facilitated Traffic Management System: A Multi-Objective Evolutionary Workflow Scheduling

Abstract:- In the current era, Computing platforms like cloud computing provides various types of computing resources, such as application, software, hardware, etc. Smart science, technology and intelligent processes have shown their vast applications in smart cities by using intelligent traffic management system. This mechanism is Artificial, Computational, Parallel (ACP) and Parallel Transportation Management System (PTMS) enabled to construct future generation intelligent and smart traffic management system. The main components of this system include signal system, device tracker, cloud, traffic controller and transportation knowledge management automation system. As scheduling on cloud is an NP-Hard Problem, even distribution of workload is challenging task. In current article, an evolutionary based workflow scheduling algorithm is proposed with capability to assign workflows to multiple computing resources efficiently. The proposed algorithms (LPS-GA and Q scheduling) have been implemented and simulated using iFogSim simulators. The comparison analysis has been conducted with basic resource allocation methods (RR and Basic GA) and as per the knowledge outcomes of proposed algorithms outperforms by using an evolutionary approach to optimize time, cost, and utility of resources, speed and efficiency. The proposed algorithm demonstrates substantial reduction in the make span and enhance the resource utilization. As per the outcomes efficiency of LPS-GA is enhanced by approx. (11% – 20%) and Q scheduling has given improved result by (20%-27%) on an average. Both the proposed algorithms are best suitable solution to optimize the performance parameter of cloud computing. The additional result has been produced from Q scheduling is Network Usage which also enhanced performance.