Modified Glowworm Swarm Optimization Algorithm based on Task Scheduling for Cyber-Physical System

The extensive application of Cyber-Physical Systems (CPS) requires efficient optimization of computational units as well as physical plant. Task scheduling (TS) is serious to enlightening resource utilization and system efficacy within CPS. Standard task schedulers in embedded real-time systems fall short of achieving CPS performance criteria due to task diversity and system heterogeneity. This research proposes a novel task-scheduling technique called Multi objective based Modified Glowworm Swarm Optimization algorithm (MMGSO) for TS that is specifically designed for the CPS context. MMGSO involves assigning number of autonomous tasks to various resources during the TS process. The objective function focuses on reducing task completion time and optimizing resource use. A series of simulations were run to demonstrate MMGSO improved performance. The comparison analysis demonstrated that the MMGSO system performed better across a variety of parameters. The proposed approach attains the better performance in Task Execution (ms) of 347ms and Average Load Balancing Ratio (%) of 69.91% from 100 iterations.