Deadline-aware Task Scheduling for Cloud Computing using Firefly Optimization Algorithm

Task scheduling poses a major challenge for cloud computing environments. ensures cost-effective task execution and improved resource utilization. It is classified as NP-hard problem due to its nondeterministic polynomial time nature. This characteristic motivates researchers employ meta-heuristic algorithms. The number of users capabilities leading increased concerns about energy consumption in data centers. In order leverage resources the most energy-efficient manner while delivering real-time services users, viable solution necessary. study proposes new deadline-aware algorithm environments based on Firefly Optimization Algorithm (FOA). suggested achieves higher level efficiency multiple parameters, including time, waiting utilization, percentage missed tasks, power consumption, makespan. According simulation results, proposed more effective superior CSO under HP2CN NASA workload archives.