SPES Algorithm Improves Cloud Computing Efficiency

Researchers developed SPES, a Stochastic Predictive Energy-Aware Scheduling algorithm, to better distribute dynamic workloads across cloud resources. The team addressed limitations in existing methods like Min-Min and the Improved Sparrow Search Algorithm, which struggle with scalability and real-time efficiency.

SPES uses predictive execution estimation, considers multiple resource demands, CPU, memory, and I/O, and incorporates stochastic decision-making to improve adaptability. The algorithm was tested using the CloudSim 5.0 framework in multi-region cloud environments.

Results showed SPES consistently outperformed the ISSA algorithm. SPES aims to offer a lightweight solution for large-scale, energy-aware cloud computing and promote resource efficiency. Further development could support green computing goals by optimizing resource utilization in rapidly growing cloud infrastructures.