A Strategic Approach to Metric Management for a Real-time Process Based on a Task Scheduling Algorithm in Distributed Mobile Environments

This project introduces a metric-driven strategy for enhancing real-time task planning within a mobile distributed system. The core design revolves around a real-time task planning algorithm that exploits consensus mechanisms among multiple nodes. By incorporating innovative real-time scheduling algorithms, validated on a supercomputer, the project establishes frameworks for simulating distributed mobile environments in real-time. This enables the execution of tasks in unpredictable contexts, ensuring adherence to stringent time constraints and empowering decision-making capabilities. The primary objective is to optimize task allocation in mobile distributed systems, including aerial nodes, thereby facilitating seamless data transfer while maintaining data integrity. The project builds upon the Fan task scheduler, integrating compensatory measures for online load distribution and optimization of message routes, effectively reducing communication latency in dynamic mobile environments. The contributions made aim to enhance real-time task allocation across diverse nodes, enabling the transfer of location and search data across networks without any data loss. This approach bears significant importance for the efficient management of tasks within dynamic scenarios.