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{ "item_title" : "Cloud Task Scheduling", "item_author" : [" Prof N. Kannammal "], "item_description" : "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.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/6/20/884/805/6208848059_b.jpg", "price_data" : { "retail_price" : "59.00", "online_price" : "59.00", "our_price" : "59.00", "club_price" : "59.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Cloud Task Scheduling|Prof N. Kannammal

Cloud Task Scheduling

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Overview

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.

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Details

  • ISBN-13: 9786208848057
  • ISBN-10: 6208848059
  • Publisher: Scholars' Press
  • Publish Date: June 2025
  • Dimensions: 9 x 6 x 0.13 inches
  • Shipping Weight: 0.19 pounds
  • Page Count: 56

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