Keiko Design And Algorithms For Distributed Scheduling
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Keiko: Design and Algorithms for Distributed Scheduling
"Keiko: Design and Algorithms for Distributed Scheduling" "Keiko: Design and Algorithms for Distributed Scheduling" provides a comprehensive and authoritative exploration of modern distributed scheduling systems, combining foundational principles, state-of-the-art algorithms, and proven architectural techniques. Beginning with an in-depth introduction to the core concepts of distributed scheduling, the book examines computational models, system types, and the critical trade-offs surrounding consistency, scalability, and fault tolerance. A detailed taxonomy of scheduling algorithms and metrics offers readers the analytical tools required to evaluate and compare diverse systems on throughput, fairness, and resilience. The book progresses to illuminate the unique architecture of the Keiko scheduler, highlighting pluggable, extensible design and robust system initialization. Readers will encounter advanced treatments of distributed task scheduling, including load balancing, constraint-aware scheduling, fairness, adaptive algorithms, and both online and offline paradigms. Essential coordination and consensus techniques—such as Paxos, Raft, and transactional scheduling—are thoroughly covered, equipping practitioners to address the complexities of scalability, conflict resolution, and system agreement in large-scale environments. Further chapters offer an expert guide to fault tolerance, security, and performance optimization in distributed schedulers, including practical strategies for error masking, state recovery, and resource elasticity. The book concludes with advanced topics in AI-powered scheduling, edge computing, and energy-aware policies, before presenting case studies and real-world applications within cloud platforms, analytics clusters, and enterprise workloads. "Keiko" is both a practical handbook and an essential reference for engineers, architects, and researchers designing the next generation of distributed scheduling systems.