Isbn: 9786208848057 - cloud task scheduling:: concepts, algorithms, and frameworks (7 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

Taschenbuch. Condición: Neu. Cloud Task Scheduling: | Concepts, Algorithms, and Frameworks | N. Kannammal | Taschenbuch | Englisch | 2025 | Scholars' Press | EAN 9786208848057 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 56 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Cloud task scheduling is the process of assigning computational tasks to cloud resources-like virtual machines or containers-to optimize performance and meet user-defined goals such as minimizing execution time (makespan), reducing costs, and maximizing resource utilization. Given the dynamic, heterogeneous, and large-scale nature of cloud environments, task scheduling is a complex and NP-hard problem.This field has evolved from classical heuristics (e.g., FCFS, Min-Min) to advanced techniques such as metaheuristics (e.g., Genetic Algorithms, PSO, ACO) and AI-driven approaches like reinforcement learning and deep learning. Real-world frameworks like Hadoop YARN, Kubernetes, and CloudSim implement these strategies to manage workloads effectively.Modern cloud scheduling emphasizes multi-objective optimization, balancing trade-offs between speed, cost, energy consumption, and fairness. Emerging trends include edge computing, serverless scheduling, and green computing, positioning task scheduling as a foundational challenge for the future of cloud services.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Cloud task scheduling is the process of assigning computational tasks to cloud resources-like virtual machines or containers-to optimize performance and meet user-defined goals such as minimizing execution time (makespan), reducing costs, and maximizing resource utilization. Given the dynamic, heterogeneous, and large-scale nature of cloud environments, task scheduling is a complex and NP-hard problem.This field has evolved from classical heuristics (e.g., FCFS, Min-Min) to advanced techniques such as metaheuristics (e.g., Genetic Algorithms, PSO, ACO) and AI-driven approaches like reinforcement learning and deep learning. Real-world frameworks like Hadoop YARN, Kubernetes, and CloudSim implement these strategies to manage workloads effectively.Modern cloud scheduling emphasizes multi-objective optimization, balancing trade-offs between speed, cost, energy consumption, and fairness. Emerging trends include edge computing, serverless scheduling, and green computing, positioning task scheduling as a foundational challenge for the future of cloud services.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.…