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by Lizhe Wang, Albert Y. Zomaya, Samee U. Khan
Scalable Computing and Communications: Theory and Practice
Coverpage
Halftitlepage
Editorpage
Titlepage
Copyright
Dedication
Contents
Preface
Contributors
1 Scalable Computing and Communications: Past, Present, and Future
1.1 Scalable Computing and Communications
References
2 Reliable Minimum Connected Dominating Sets for Topology Control in Probabilistic Wireless Sensor Networks
2.1 Topology Control in Wireless Sensor Networks (WSNs)
2.2 DS-Based Topology Control
2.3 Deterministic WSNs and Probabilistic WSNs
2.4 Reliable MCDS Problem
2.5 A GA to Construct RMCDS-GA
2.6 Performance Evaluation
2.7 Conclusions
References
3 Peer Selection Schemes in Scalable P2P Video Streaming Systems
3.1 Introduction
3.2 Overlay Structures
3.3 Peer Selection for Overlay Construction
3.4 A Game Theoretic Perspective on Peer Selection
3.5 Discussion and Future Work
3.6 Summary
References
4 Multicore and Many-Core Computing
4.1 Introduction
4.2 Architectural Options for Multicore Systems
4.3 Multicore Architecture Examples
4.4 Programming Multicore Architectures
4.5 Many-Core Architectures
4.6 Many-Core Architecture Examples
4.7 Summary
References
5 Scalable Computing on Large Heterogeneous CPU/GPU Supercomputers
5.1 Introduction
5.2 Heterogeneous Computing Environments
5.3 Scalable Programming Patterns for Large GPU Clusters
5.4 Hybrid Implementations
5.5 Experimental Results
5.6 Conclusions
Acknowledgments
References
6 Diagnosability of Multiprocessor Systems
6.1 Introduction
6.2 Fundamental Concepts
6.3 Diagnosability of (1,2)-MCNS under PMC Model
6.4 Diagnosability of 2-MCNS under MM* Model
6.5 Application to Multiprocessor Systems
6.6 Concluding Remarks
References
7 A Performance Analysis Methodology for MultiCore, Multithreaded Processors
7.1 Introduction
7.2 Methodology
7.3 Simulation Tool (ST)
7.4 Analytic Modeling Technique
7.5 Testing
7.6 Related Work
7.7 Conclusions and Future Work
References
8 The Future in Mobile Multicore Computing
8.1 Introduction
8.2 Background
8.3 Hardware Initiatives
8.4 Software Initiatives
8.5 Additional Discussion
8.6 Future Trends
8.7 Conclusion
References
9 Modeling and Algorithms for Scalable and Energy-Efficient Execution on Multicore Systems
9.1 Introduction
9.2 Model-Based Hybrid Message-Passing Interface (MPI)/OpenMP Power-Aware Computing
9.3 Power-Aware MPI Task Aggregation Prediction
9.4 Conclusions
References
10 Cost Optimization for Scalable Communication in Wireless Networks with Movement-Based Location Management
10.1 Introduction
10.2 Background Information
10.3 Cost Measure and Optimization for a Single User
10.4 Cost Optimization with Location Update Constraint
10.5 Cost Optimization with Terminal Paging Constraint
10.6 Numerical Data
10.7 Concluding Remarks
References
11 A Framework for Semiautomatic Explicit Parallelization
11.1 Introduction
11.2 Explicit Parallelization Using MPI
11.3 Building Blocks of FraSPA
11.4 Evaluation of FraSPA through Case Studies
11.5 Lessons Learned
11.6 Related Work
11.7 Summary
References
12 Fault Tolerance and Transmission Reliability in Wireless Networks
12.1 Introduction: Reliability Issues in Wireless and Sensor Networks
12.2 Reliability and Fault Tolerance of Coverage Models for Sensor Networks
12.3 Fault-Tolerant k-Fold Pivot Routing in Wireless Sensor Networks
12.4 Impact of Variable Transmission Range in All-Wireless Networks
12.5 Conclusions and Open Problems
References
13 Optimizing and Tuning Scientific Codes
13.1 Introduction
13.2 An Abstract View of the Machine Architecture
13.3 Optimizing Scientific Codes
13.4 Empirical Tuning of Optimizations
13.5 Related Work
13.6 Summary and Future Work
Acknowledgments
References
14 Privacy and Confi dentiality in Cloud Computing
14.1 Introduction
14.2 Cloud Stakeholders and Computational Assets
14.3 Data Privacy and Trust
14.4 A Cloud Computing Example
14.5 Conclusion
Acknowledgments
References
15 Reputation Management Systems for Peer-to-Peer Networks
15.1 Introduction
15.2 Reputation Management Systems
15.3 Case Study of Reputation Systems
15.4 Open Problems
15.5 Conclusion
Acknowledgments
References
16 Toward a Secure Fragment Allocation of Files in Heterogeneous Distributed Systems
16.1 Introduction
16.2 Related Work
16.3 System and Threat Models
16.4 S-FAS: A Secure Fragment Allocation Scheme
16.5 Assurance Models
16.6 Sap Allocation Principles and Prototype
16.7 Evaluation of System Assurance and Performance
16.8 Conclusion
Acknowledgments
References
17 Adopting Compression in Wireless Sensor Networks
17.1 Introduction
17.2 Compression in Sensor Nodes
17.3 Compression Effect on Packet Delay
17.4 Online Adaptive Compression Algorithm
17.5 Performance Evaluations
17.6 Summary
References
18 GFOG: Green and Flexible Opportunistic Grids
18.1 Introduction
18.2 Related Work
18.3 UnaGrid Infrastructure
18.4 Energy Consumption Model
18.5 Experimental Results
18.6 Conclusions and Future Work
References
19 Maximizing Real-Time System Utilization by Adjusting Task Computation Times
19.1 Introduction
19.2 Expressing Task Schedulability in Polylinear Surfaces
19.3 Task Execution Time Adjustment Based on the P-Bound
19.4 Conclusions
Acknowledgments
References
20 Multilevel Exploration of the Optimization Landscape through Dynamical Fitness for Grid Scheduling
20.1 Introduction
20.2 Statement of the Problem
20.3 General Characteristics of the Optimization Landscape
20.4 Multilevel Metaheuristic Schedulers
20.5 Empirical Analysis
20.6 Conclusions
References
21 Implementing Pointer Jumping for Exact Inference on Many-Core Systems
21.1 Introduction
21.2 Background
21.3 Related Work
21.4 Pointer Jumping-Based Algorithms for Scheduling Exact Inference
21.5 Analysis with Respect to Many-Core Processors
21.6 From Exact Inference to Generic Directed Acyclic Graph (DAG)-Structured Computations
21.7 Experiments
21.8 Conclusions
References
22 Performance Optimization of Scientifi c Applications Using an Autonomic Computing Approach
22.1 Introduction
22.2 Scientifi c Applications and Their Performance
22.3 Load Balancing via DLS
22.4 The Use of Machine Learning in Improving the Performance of Scientifi c Applications
22.5 Design Strategies and an Integrated Framework
22.6 Experimental Results, Analysis, and Evaluation
22.7 Conclusions, Future Work, and Open Problems
Acknowledgments
References
23 A Survey of Techniques for Improving Search Engine Scalability through Profi ling, Prediction, and Prefetching of Query Results
23.1 Introduction
23.2 Modeling User Behavior
23.3 Grouping Users into Neighborhoods of Similarity
23.4 Similarity Metrics
23.5 Conclusion and Future Work
Appendix A Comparative Analysis of Comparison Algorithms
Appendix B Most Popular Searches
References
24 KNN Queries in Mobile Sensor Networks
24.1 Introduction
24.2 Preliminaries and Infrastructure-Based KNN Queries
24.3 Infrastructure-Free KNN Queries
24.4 Future Research Directions
24.5 Conclusions
References
25 Data Partitioning for Designing and Simulating Effi cient Huge Databases
25.1 Introduction
25.2 Background and Related Work
25.3 Fragmentation Methodology
25.4 Hardness Study
25.5 Proposed Selection Algorithms
25.6 Impact of HP on Data Warehouse Physical Design
25.7 Experimental Studies
25.8 Physical Design Simulator Tool
25.9 Conclusion and Perspectives
References
26 Scalable Runtime Environments for Large-Scale Parallel Applications
26.1 Introduction
26.2 Goals of a Runtime Environment
26.3 Communication Infrastructure
26.4 Application Deployment
26.5 Fault Tolerance and Robustness
26.6 Case Studies
26.7 Conclusion
References
27 Increasing Performance through Optimization on APU
27.1 Introduction
27.2 Heterogeneous Architectures
27.3 Related Work
27.4 OpenCL, CUDA of the Future
27.5 Simple Introduction to OpenCL Programming
27.6 Performance and Optimization Summary
27.7 Application
27.8 Summary
Appendix
References
28 Toward Optimizing Cloud Computing: An Example of Optimization under Uncertainty
28.1 Cloud Computing: Why We Need It and How We Can Make It Most Effi cient
28.2 Optimal Server Placement Problem: First Approximation
28.3 Server Placement in Cloud Computing: Toward a More Realistic Model
28.4 Predicting Cloud Growth: Formulation of the Problem and Our Approach to Solving This Problem
28.5 Predicting Cloud Growth: First Approximation
28.6 Predicting Cloud Growth: Second Approximation
28.7 Predicting Cloud Growth: Third Approximation
28.8 Conclusions and Future Work
Acknowledgments
Appendix: Description of Expenses Related to Cloud Computing
References
29 Modeling of Scalable Embedded Systems
29.1 Introduction
29.2 Embedded System Applications
29.3 Embedded Systems: Hardware and Software
29.4 Modeling: An Integral Part of the Embedded System Design Flow
29.5 Single- and Multiunit Embedded System Modeling
29.6 Conclusions
Acknowledgments
References
30 Scalable Service Composition in Pervasive Computing
30.1 Introduction
30.2 Service Composition Framework
30.3 Approaches and Techniques for Scalable Service Composition in PvCE
30.4 Conclusions
References
31 Virtualization Techniques for Graphics Processing Units
31.1 Introduction
31.2 Background
31.3 VOCL Framework
31.4 VOCL Optimizations
31.5 Experimental Evaluation
31.6 Related Work
31.7 Concluding Remarks
References
32 Dense Linear Algebra on Distributed Heterogeneous Hardware with a Symbolic DAG Approach
32.1 Introduction and Motivation
32.2 Distributed Datafl ow by Symbolic Evaluation
32.3 The DAGuE Datafl ow Runtime
32.4 Datafl ow Representation
32.5 Programming Linear Algebra with DAGuE
32.6 Performance Evaluation
32.7 Conclusion
32.8 Summary
References
33 Fault-Tolerance Techniques for Scalable Computing
33.1 Introduction and Trends in Large-Scale Computing Systems
33.2 Hardware Features for Resilience
33.3 Systems Software Features for Resilience
33.4 Application or Domain-Specifi c Fault-Tolerance Techniques
33.5 Summary
References
34 Parallel Programming Models for Scalable Computing
34.1 Introduction to Parallel Programming Models
34.2 The Message-Passing Interface (MPI)
34.3 Partitioned Global Address Space (PGAS) Models
34.4 Task-Parallel Programming Models
34.5 High-Productivity Parallel Programming Models
34.6 Summary and Concluding Remarks
Acknowledgment
References
35 Grid Simulation Tools for Job Scheduling and Data File Replication
35.1 Introduction
35.2 Simulation Platforms
35.3 Problem Statement: Data-Aware Job Scheduling (DAJS)
References
Bindex
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