Details salient features of grid computing, introduces grid and its architecture and also discusses advances to the complex hybridized model of grid computing, grid scheduling, and grid resource management. It addresses problems causing grid bottlenecks, the formulation of solution strategies, implementation of grid scheduling, and more.
Details salient features of grid computing, introduces grid and its architecture and also discusses advances to the complex hybridized model of grid computing, grid scheduling, and grid resource management. It addresses problems causing grid bottlenecks, the formulation of solution strategies, implementation of grid scheduling, and more.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Ankita, PhD, is Assistant Professor of Computer Science and Engineering at the Pranveer Singh Institute of Technology (PSIT), Kanpur, India. Her fields of interest are grid computing, artificial intelligence, and computational intelligence. She has authored research papers on computer science and has been assigned as a reviewer for several SCI-indexed journals and IEEE conferences. Sudip Kumar Sahana, PhD, is Associate Professor of Computer Science and Engineering at the Birla Institute of Technology, Mesra, India. His major field of study is in computer science. His research and teaching interests include soft computing, computational intelligence, distributed computing, and artificial intelligence. He has authored numerous articles, research papers, and books in the field of computer science and has been assigned as an editorial team member and reviewer for several reputed journals. He also holds several patents. He is a lifetime member of the Indian Society for Technical Education (ISTE) and fellow of the Institution of Electronics and Telecommunication Engineers (IETE), India.
Inhaltsangabe
Introduction PART 1: FOUNDATIONS 1. Introduction to Grid Computing 2. Scheduling: Conventional and Bio-Inspired Algorithms 3. Work Done Using Conventional and Bio-Inspired Algorithms 4. Scheduling Algorithms: Modified and Hybrid Algorithms PART 2: IMPLEMENTATION OF SCHEDULING ALGORITHMS 5. Research-Based Case Study to Solve Grid-Scheduling Problems Using FCFS, SJF, ACO, PSO, and GA 6. Research-Based Case Study to a Solve Grid Scheduling Problem Using Modified and Hybrid Algorithms: ACOthresh, SJF- ACOthresh, and SJF-GA PART 3: PERFORMANCE COMPARISON OF ALGORITHMS 7. Comparison of Conventional, Bio-Inspired and Hybrid Algorithms: A Review 8. New Computing Platforms for Solving Convoluted Engineering Problems: A Review
Introduction PART 1: FOUNDATIONS 1. Introduction to Grid Computing 2. Scheduling: Conventional and Bio-Inspired Algorithms 3. Work Done Using Conventional and Bio-Inspired Algorithms 4. Scheduling Algorithms: Modified and Hybrid Algorithms PART 2: IMPLEMENTATION OF SCHEDULING ALGORITHMS 5. Research-Based Case Study to Solve Grid-Scheduling Problems Using FCFS, SJF, ACO, PSO, and GA 6. Research-Based Case Study to a Solve Grid Scheduling Problem Using Modified and Hybrid Algorithms: ACOthresh, SJF- ACOthresh, and SJF-GA PART 3: PERFORMANCE COMPARISON OF ALGORITHMS 7. Comparison of Conventional, Bio-Inspired and Hybrid Algorithms: A Review 8. New Computing Platforms for Solving Convoluted Engineering Problems: A Review
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