A Real Time Optimizing Mobile Operating System: An Interactive Context - Couverture souple

Misal, Ganesh; Thigale, Somnath; Shinde, Sahadev

Couverture souple

ISBN 10 : 6630413288 ISBN 13 : 9786630413281

Editeur : LAP Lambert Academic Publishing, 2026

Synopsis

Predicting the execution time of workflow tasks in a cloud environment is vital for optimizing resource utilization and meeting service level agreements (SLAs). In this study, we propose a Two-Stage Machine Learning Approach for Workflow Task Execution Time Prediction. In the first stage, we employ a task classifica-tion model to categorize tasks into groups based on their expected execution times (e.g., short, medium, long). The proposed two-stage approach aims to enhance prediction accuracy and interpretability by leveraging both classification and re-gression techniques. We evaluate the performance of the model using historical data, considering metrics such as accuracy, Mean Absolute Error, and Root Mean Squared Error. Finally, we discuss the deployment and monitoring of the model in a cloud environment, emphasizing its adaptability to evolving infrastructure and workload patterns. Many methods, including resource provisioning and scheduling, depend on predict-ing the workflow activities' performance for changing input data. On the other hand, producing such estimates in the cloud is challenging.

Détails de l'édition

• Éditeur: LAP Lambert Academic Publishing
• Date d'édition: 2026
• Langue: anglais
• ISBN 10: 6630413288
• ISBN 13: 9786630413281
• Reliure: Tapa blanda
• Nombre de pages: 72
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible