Job Scheduling Strategies for Parallel Processing 1st Edition by Dalibor Klusacek, Walfredo Cirne, Gonzalo P Rodrigo ISBN 9783030882242

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ISBN 10: 
ISBN 13: 9783030882242
Author: Dalibor Klusacek, Walfredo Cirne, Gonzalo P Rodrigo

This book constitutes the thoroughly refereed post-conference proceedings of the 24th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2021, held as a virtual event in May 2021 (due to the Covid-19 pandemic).

The 10 revised full papers presented were carefully reviewed and selected from 17 submissions. In addition to this, one keynote paper was included in the workshop. The volume contains two sections: Open Scheduling Problems and Proposals and Technical Papers. The papers cover such topics as parallel computing, distributed systems, workload modeling, performance optimization, and others.

Job Scheduling Strategies for Parallel Processing 1st Table of contents:

• Fundamentals of Job Scheduling

  • Job Scheduling Concepts and Objectives
  • Types of Scheduling Algorithms
  • Challenges in Job Scheduling for Parallel Systems
  • Resource Management in Parallel Processing

• Classification of Job Scheduling Strategies

  • Centralized vs. Distributed Scheduling
  • Static vs. Dynamic Scheduling
  • Centralized Scheduling for Parallel Systems
  • Load Balancing and Resource Allocation

• Scheduling Algorithms in Parallel Systems

  • First-Come, First-Served (FCFS)
  • Shortest Job First (SJF)
  • Round-Robin Scheduling
  • Priority-Based Scheduling
  • Least-Loaded Scheduling

• Task Allocation and Load Balancing

  • The Importance of Load Balancing in Parallel Systems
  • Dynamic Load Balancing Algorithms
  • Static Load Balancing Techniques
  • Task Allocation Strategies for Heterogeneous Systems

• Real-Time and Multi-Level Scheduling

  • Real-Time Scheduling in Parallel Computing
  • Multi-Level Feedback Queue Scheduling
  • Managing Real-Time Constraints in Parallel Systems
  • Scheduling in Multi-Core and Multi-Processor Systems

• Advanced Job Scheduling Techniques

  • Task Scheduling for Heterogeneous Architectures
  • Scheduling for Cloud Computing Environments
  • Fault-Tolerant and Resilient Scheduling
  • Energy-Efficient Scheduling in Parallel Systems

• Scheduling for High-Performance Computing (HPC) Systems

  • Job Scheduling in Supercomputers and HPC Clusters
  • Resource Management in High-Performance Parallel Systems
  • Parallel Task Scheduling in Grid Computing
  • HPC-Specific Scheduling Algorithms

• Job Scheduling in Cloud and Distributed Systems

  • Scheduling in Cloud Computing Environments
  • Resource Provisioning in Distributed Systems
  • Hybrid Scheduling Models for Cloud Resources
  • Scheduling in Virtualized Environments

• Heuristic and Metaheuristic Approaches to Scheduling

  • Genetic Algorithms for Job Scheduling
  • Simulated Annealing for Parallel Task Scheduling
  • Ant Colony Optimization for Resource Allocation
  • Particle Swarm Optimization in Parallel Systems

• Applications of Job Scheduling in Real-World Systems

  • Scheduling in Data Centers and Cloud Services
  • Scheduling for Scientific Computations and Simulations
  • Job Scheduling in Enterprise Systems
  • Scheduling in Data-Intensive Applications

• Performance Evaluation of Job Scheduling Algorithms

  • Metrics for Evaluating Scheduling Performance
  • Simulations and Case Studies for Scheduling Algorithms
  • Comparative Analysis of Scheduling Techniques
  • Performance Tuning for Parallel Systems

• Future Trends in Job Scheduling for Parallel Processing

  • Emerging Trends in Parallel Computing and Job Scheduling
  • Scheduling for Quantum Computing
  • AI and Machine Learning in Job Scheduling
  • Future Challenges and Opportunities

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