Description

Book Synopsis

Reviews the latest advances in the all-important field of scalable computing

In telecommunications and software engineering, scalability is the ability of a system, network, or process to either handle growing amounts of work in a graceful manner or be enlarged to accommodate that growth. It is a desirable property for many scientific, industrial, and business applications and an important feature for hardware.

This immersive book summarizes the latest research achievements in the field of scalable computing and covers new topics that have emerged recently on computing and communications, such as unconventional computing, green and sustainable computing, cloud and volunteer computing, and more. Filled with contributions from world-renowned engineers, researchers, and IT professionals in diverse areas, Scalable Computing and Communications covers:

  • Circuit and component design
  • Operating systems
  • Green computing
  • Network

    Table of Contents
    Preface xix

    Contributors xxi

    1. Scalable Computing and Communications: Past, Present, and Future 1
    Yanhui Wu, Kashif Bilal, Samee U. Khan, Lizhe Wang, and Albert Y. Zomaya

    1.1 Scalable Computing and Communications 1

    References 4

    2. Reliable Minimum Connected Dominating Sets for Topology Control in Probabilistic Wireless Sensor Networks 7
    Jing (Selena) He, Shouling Ji, Yi Pan, and Yingshu Li

    2.1 Topology Control in Wireless Sensor Networks (WSNs) 7

    2.2 DS-Based Topology Control 10

    2.3 Deterministic WSNs and Probabilistic WSNs 12

    2.4 Reliable MCDS Problem 13

    2.5 A GA to Construct RMCDS-GA 17

    2.6 Performance Evaluation 26

    2.7 Conclusions 27

    References 28

    3. Peer Selection Schemes in Scalable P2P Video Streaming Systems 31
    Xin Jin and Yu-Kwong Kwok

    3.1 Introduction 31

    3.2 Overlay Structures 32

    3.3 Peer Selection for Overlay Construction 34

    3.4 A Game Theoretic Perspective on Peer Selection 45

    3.5 Discussion and Future Work 47

    3.6 Summary 48

    References 49

    4. Multicore and Many-Core Computing 55
    Ioannis E. Venetis

    4.1 Introduction 55

    4.2 Architectural Options for Multicore Systems 60

    4.3 Multicore Architecture Examples 64

    4.4 Programming Multicore Architectures 67

    4.5 Many-Core Architectures 74

    4.6 Many-Core Architecture Examples 75

    4.7 Summary 77

    References 77

    5. Scalable Computing on Large Heterogeneous CPU/GPU Supercomputers 81
    Fengshun Lu, Kaijun Ren, Junqiang Song, and Jinjun Chen

    5.1 Introduction 81

    5.2 Heterogeneous Computing Environments 82

    5.3 Scalable Programming Patterns for Large GPU Clusters 84

    5.4 Hybrid Implementations 87

    5.5 Experimental Results 89

    5.6 Conclusions 94

    Acknowledgments 94

    References 94

    6. Diagnosability of Multiprocessor Systems 97
    Chia-Wei Lee and Sun-Yuan Hsieh

    6.1 Introduction 97

    6.2 Fundamental Concepts 98

    6.3 Diagnosability of (1,2)-MCNS under PMC Model 103

    6.4 Diagnosability of 2-MCNS under MM* Model 105

    6.5 Application to Multiprocessor Systems 110

    6.6 Concluding Remarks 122

    References 122

    7. A Performance Analysis Methodology for MultiCore, Multithreaded Processors 125
    Miao Ju, Hun Jung, and Hao Che

    7.1 Introduction 125

    7.2 Methodology 126

    7.3 Simulation Tool (ST) 130

    7.4 Analytic Modeling Technique 132

    7.5 Testing 136

    7.6 Related Work 139

    7.7 Conclusions and Future Work 141

    References 141

    8. The Future in Mobile Multicore Computing 145
    Blake Hurd, Chiu C. Tan, and Jie Wu

    8.1 Introduction 145

    8.2 Background 146

    8.3 Hardware Initiatives 148

    8.4 Software Initiatives 151

    8.5 Additional Discussion 152

    8.6 Future Trends 153

    8.7 Conclusion 154

    References 155

    9. Modeling and Algorithms for Scalable and Energy-Efficient Execution on Multicore Systems 157
    Dong Li, Dimitrios S. Nikolopoulos, and Kirk W. Cameron

    9.1 Introduction 157

    9.2 Model-Based Hybrid Message-Passing Interface (MPI)/OpenMP Power-Aware Computing 158

    9.3 Power-Aware MPI Task Aggregation Prediction 170

    9.4 Conclusions 181

    References 182

    10. Cost Optimization for Scalable Communication in Wireless Networks with Movement-Based Location Management 185
    Keqin Li

    10.1 Introduction 185

    10.2 Background Information 187

    10.3 Cost Measure and Optimization for a Single User 190

    10.4 Cost Optimization with Location Update Constraint 192

    10.5 Cost Optimization with Terminal Paging Constraint 196

    10.6 Numerical Data 201

    10.7 Concluding Remarks 206

    References / 206

    11. A Framework for Semiautomatic Explicit Parallelization 209
    Ritu Arora, Purushotham Bangalore, and Marjan Mernik

    11.1 Introduction 209

    11.2 Explicit Parallelization Using MPI 210

    11.3 Building Blocks of FraSPA 211

    11.4 Evaluation of FraSPA through Case Studies 215

    11.5 Lessons Learned 221

    11.6 Related Work 222

    11.7 Summary 224

    References 224

    12. Fault Tolerance and Transmission Reliability in Wireless Networks 227
    Wolfgang W. Bein and Doina Bein

    12.1 Introduction: Reliability Issues in Wireless and Sensor Networks 227

    12.2 Reliability and Fault Tolerance of Coverage Models for Sensor Networks 230

    12.3 Fault-Tolerant k-Fold Pivot Routing in Wireless Sensor Networks 238

    12.4 Impact of Variable Transmission Range in All-Wireless Networks 244

    12.5 Conclusions and Open Problems 250

    References / 251

    13. Optimizing and Tuning Scientifi c Codes 255
    Qing Yi

    13.1 Introduction 255

    13.2 An Abstract View of the Machine Architecture 256

    13.3 Optimizing Scientifi c Codes 256

    13.4 Empirical Tuning of Optimizations 262

    13.5 Related Work 272

    13.6 Summary and Future Work 273

    Acknowledgments 273

    References 273

    14. Privacy and Confi dentiality in Cloud Computing 277
    Khaled M. Khan and Qutaibah Malluhi

    14.1 Introduction 277

    14.2 Cloud Stakeholders and Computational Assets 278

    14.3 Data Privacy and Trust 280

    14.4 A Cloud Computing Example 281

    14.5 Conclusion 288

    Acknowledgments 288

    References 288

    15. Reputation Management Systems for Peer-to-Peer Networks 291
    Fang Qi, Haiying Shen, Harrison Chandler, Guoxin Liu, and Ze Li

    15.1 Introduction 291

    15.2 Reputation Management Systems 292

    15.3 Case Study of Reputation Systems 307

    15.4 Open Problems 316

    15.5 Conclusion 316

    Acknowledgments 317

    References 317

    16. Toward a Secure Fragment Allocation of Files in Heterogeneous Distributed Systems 321
    Yun Tian, Mohammed I. Alghamdi, Xiaojun Ruan, Jiong Xie, and Xiao Qin

    16.1 Introduction 321

    16.2 Related Work 323

    16.3 System and Threat Models 325

    16.4 S-FAS: A Secure Fragment Allocation Scheme 327

    16.5 Assurance Models 329

    16.6 Sap Allocation Principles and Prototype 332

    16.7 Evaluation of System Assurance and Performance 333

    16.8 Conclusion 339

    Acknowledgments 341

    References 341

    17. Adopting Compression in Wireless Sensor Networks 343
    Xi Deng and Yuanyuan Yang

    17.1 Introduction 343

    17.2 Compression in Sensor Nodes 345

    17.3 Compression Effect on Packet Delay 348

    17.4 Online Adaptive Compression Algorithm 350

    17.5 Performance Evaluations 360

    17.6 Summary 362

    References 363

    18. GFOG: Green and Flexible Opportunistic Grids 365
    Harold Castro, Mario Villamizar, German Sotelo, Cesar O. Diaz, Johnatan Pecero, Pascal Bouvry, and Samee U. Khan

    18.1 Introduction 365

    18.2 Related Work 366

    18.3 UnaGrid Infrastructure 369

    18.4 Energy Consumption Model 372

    18.5 Experimental Results 374

    18.6 Conclusions and Future Work 382

    References 382

    19. Maximizing Real-Time System Utilization by Adjusting Task Computation Times 387
    Nasro Min-Allah, Samee Ullah Khan, Yongji Wang, Joanna Kolodziej, and Nasir Ghani

    19.1 Introduction 387

    19.2 Expressing Task Schedulability in Polylinear Surfaces 389

    19.3 Task Execution Time Adjustment Based on the P-Bound 391

    19.4 Conclusions 393

    Acknowledgments 393

    References 393

    20. Multilevel Exploration of the Optimization Landscape through Dynamical Fitness for Grid Scheduling 395
    Joanna Kolodziej

    20.1 Introduction 395

    20.2 Statement of the Problem 397

    20.3 General Characteristics of the Optimization Landscape 399

    20.4 Multilevel Metaheuristic Schedulers 402

    20.5 Empirical Analysis 408

    20.6 Conclusions 417

    References 417

    21. Implementing Pointer Jumping for Exact Inference on Many-Core Systems 419
    Yinglong Xia, Nam Ma, and Viktor K. Prasanna

    21.1 Introduction 419

    21.2 Background 420

    21.3 Related Work 422

    21.4 Pointer Jumping-Based Algorithms for Scheduling Exact Inference 423

    21.5 Analysis with Respect to Many-Core Processors 424

    21.6 From Exact Inference to Generic Directed Acyclic Graph (DAG)-Structured Computations 427

    21.7 Experiments 428

    21.8 Conclusions 434

    References 435

    22. Performance Optimization of Scientifi c Applications Using an Autonomic Computing Approach 437
    Ioana Banicescu, Florina M. Ciorba, and Srishti Srivastava

    22.1 Introduction 437

    22.2 Scientifi c Applications and Their Performance 439

    22.3 Load Balancing via DLS 441

    22.4 The Use of Machine Learning in Improving the Performance of Scientifi c Applications 441

    22.5 Design Strategies and an Integrated Framework 445

    22.6 Experimental Results, Analysis, and Evaluation 455

    22.7 Conclusions, Future Work, and Open Problems 462

    Acknowledgments 463

    References 463

    23. A Survey of Techniques for Improving Search Engine Scalability through Profi ling, Prediction, and Prefetching of Query Results 467
    C. Shaun Wagner, Sahra Sedigh, Ali R. Hurson, and Behrooz Shirazi

    23.1 Introduction 467

    23.2 Modeling User Behavior 472

    23.3 Grouping Users into Neighborhoods of Similarity 474

    23.4 Similarity Metrics 481

    23.5 Conclusion and Future Work 497

    Appendix A Comparative Analysis of Comparison Algorithms 498

    Appendix B Most Popular Searches 501

    References 502

    24. KNN Queries in Mobile Sensor Networks 507
    Wei-Guang Teng and Kun-Ta Chuang

    24.1 Introduction 507

    24.2 Preliminaries and Infrastructure-Based KNN Queries 509

    24.3 Infrastructure-Free KNN Queries 511

    24.4 Future Research Directions 519

    24.5 Conclusions 519

    References 520

    25. Data Partitioning for Designing and Simulating Efficient Huge Databases 523
    Ladjel Bellatreche, Kamel Boukhalfa, Pascal Richard, and Soumia Benkrid

    25.1 Introduction 523

    25.2 Background and Related Work 527

    25.3 Fragmentation Methodology 532

    25.4 Hardness Study 535

    25.5 Proposed Selection Algorithms 538

    25.6 Impact of HP on Data Warehouse Physical Design 544

    25.7 Experimental Studies 549

    25.8 Physical Design Simulator Tool 553

    25.9 Conclusion and Perspectives 559

    References 560

    26. Scalable Runtime Environments for Large-Scale Parallel Applications 563
    Camille Coti and Franck Cappello

    26.1 Introduction 563

    26.2 Goals of a Runtime Environment 565

    26.3 Communication Infrastructure 567

    26.4 Application Deployment 571

    26.5 Fault Tolerance and Robustness 577

    26.6 Case Studies 582

    26.7 Conclusion 586

    References 587

    27. Increasing Performance through Optimization on APU 591
    Matthew Doerksen, Parimala Thulasiraman, and Ruppa Thulasiram

    27.1 Introduction 591

    27.2 Heterogeneous Architectures 591

    27.3 Related Work 597

    27.4 OpenCL, CUDA of the Future 600

    27.5 Simple Introduction to OpenCL Programming 604

    27.6 Performance and Optimization Summary 607

    27.7 Application 607

    27.8 Summary 609

    Appendix 609

    References 612

    28. Toward Optimizing Cloud Computing: An Example of Optimization under Uncertainty 613
    Vladik Kreinovich

    28.1 Cloud Computing: Why We Need It and How We Can Make It Most Efficient 613

    28.2 Optimal Server Placement Problem: First Approximation 614

    28.3 Server Placement in Cloud Computing: Toward a More Realistic Model 618

    28.4 Predicting Cloud Growth: Formulation of the Problem and Our Approach to Solving This Problem 620

    28.5 Predicting Cloud Growth: First Approximation 621

    28.6 Predicting Cloud Growth: Second Approximation 622

    28.7 Predicting Cloud Growth: Third Approximation 623

    28.8 Conclusions and Future Work 625

    Acknowledgments 625

    Appendix: Description of Expenses Related to Cloud Computing 626

    References 626

    29. Modeling of Scalable Embedded Systems 629
    Arslan Munir, Sanjay Ranka, and Ann Gordon-Ross

    29.1 Introduction 629

    29.2 Embedded System Applications 631

    29.3 Embedded Systems: Hardware and Software 634

    29.4 Modeling: An Integral Part of the Embedded System Design Flow 638

    29.5 Single- and Multiunit Embedded System Modeling 644

    29.6 Conclusions 654

    Acknowledgments 655

    References 655

    30. Scalable Service Composition in Pervasive Computing 659
    Joanna Siebert and Jiannong Cao

    30.1 Introduction 659

    30.2 Service Composition Framework 660

    30.3 Approaches and Techniques for Scalable Service Composition in PvCE 664

    30.4 Conclusions 671

    References 671

    31. Virtualization Techniques for Graphics Processing Units 675
    Pavan Balaji, Qian Zhu, and Wu-Chun Feng

    31.1 Introduction 675

    31.2 Background 677

    31.3 VOCL Framework 677

    31.4 VOCL Optimizations 682

    31.5 Experimental Evaluation 687

    31.6 Related Work 696

    31.7 Concluding Remarks 696

    References 697

    32. Dense Linear Algebra on Distributed Heterogeneous Hardware with a Symbolic DAG Approach 699
    George Bosilca, Aurelien Bouteiller, Anthony Danalis, Thomas Herault, Piotr Luszczek, and Jack J. Dongara

    32.1 Introduction and Motivation 699

    32.2 Distributed Datafl ow by Symbolic Evaluation 701

    32.3 The DAGuE Datafl ow Runtime 705

    32.4 Datafl ow Representation 709

    32.5 Programming Linear Algebra with DAGuE 716

    32.6 Performance Evaluation 728

    32.7 Conclusion 731

    32.8 Summary 732

    References 733

    33. Fault-Tolerance Techniques for Scalable Computing 737
    Pavan Balaji, Darius Buntinas, and Dries Kimpe

    33.1 Introduction and Trends in Large-Scale Computing Systems 737

    33.2 Hardware Features for Resilience 738

    33.3 Systems Software Features for Resilience 743

    33.4 Application or Domain-Specifi c Fault-Tolerance Techniques 748

    33.5 Summary 753

    References 753

    34. Parallel Programming Models for Scalable Computing 759
    James Dinan and Pavan Balaji

    34.1 Introduction to Parallel Programming Models 759

    34.2 The Message-Passing Interface (MPI) 761

    34.3 Partitioned Global Address Space (PGAS) Models 765

    34.4 Task-Parallel Programming Models 769

    34.5 High-Productivity Parallel Programming Models 772

    34.6 Summary and Concluding Remarks 775

    Acknowledgment 775

    References 775

    35. Grid Simulation Tools for Job Scheduling and Data File Replication 777
    Javid Taheri, Albert Y. Zomaya, and Samee U. Khan

    35.1 Introduction 777

    35.2 Simulation Platforms 779

    35.3 Problem Statement: Data-Aware Job Scheduling (DAJS) 792

    References 795

    Index 799

Scalable Computing and Communications

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    A Hardback by Samee U. Khan, Albert Y. Zomaya, Lizhe Wang

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      View other formats and editions of Scalable Computing and Communications by Samee U. Khan

      Publisher: John Wiley & Sons Inc
      Publication Date: 05/03/2013
      ISBN13: 9781118162651, 978-1118162651
      ISBN10: 111816265X

      Description

      Book Synopsis

      Reviews the latest advances in the all-important field of scalable computing

      In telecommunications and software engineering, scalability is the ability of a system, network, or process to either handle growing amounts of work in a graceful manner or be enlarged to accommodate that growth. It is a desirable property for many scientific, industrial, and business applications and an important feature for hardware.

      This immersive book summarizes the latest research achievements in the field of scalable computing and covers new topics that have emerged recently on computing and communications, such as unconventional computing, green and sustainable computing, cloud and volunteer computing, and more. Filled with contributions from world-renowned engineers, researchers, and IT professionals in diverse areas, Scalable Computing and Communications covers:

      • Circuit and component design
      • Operating systems
      • Green computing
      • Network

        Table of Contents
        Preface xix

        Contributors xxi

        1. Scalable Computing and Communications: Past, Present, and Future 1
        Yanhui Wu, Kashif Bilal, Samee U. Khan, Lizhe Wang, and Albert Y. Zomaya

        1.1 Scalable Computing and Communications 1

        References 4

        2. Reliable Minimum Connected Dominating Sets for Topology Control in Probabilistic Wireless Sensor Networks 7
        Jing (Selena) He, Shouling Ji, Yi Pan, and Yingshu Li

        2.1 Topology Control in Wireless Sensor Networks (WSNs) 7

        2.2 DS-Based Topology Control 10

        2.3 Deterministic WSNs and Probabilistic WSNs 12

        2.4 Reliable MCDS Problem 13

        2.5 A GA to Construct RMCDS-GA 17

        2.6 Performance Evaluation 26

        2.7 Conclusions 27

        References 28

        3. Peer Selection Schemes in Scalable P2P Video Streaming Systems 31
        Xin Jin and Yu-Kwong Kwok

        3.1 Introduction 31

        3.2 Overlay Structures 32

        3.3 Peer Selection for Overlay Construction 34

        3.4 A Game Theoretic Perspective on Peer Selection 45

        3.5 Discussion and Future Work 47

        3.6 Summary 48

        References 49

        4. Multicore and Many-Core Computing 55
        Ioannis E. Venetis

        4.1 Introduction 55

        4.2 Architectural Options for Multicore Systems 60

        4.3 Multicore Architecture Examples 64

        4.4 Programming Multicore Architectures 67

        4.5 Many-Core Architectures 74

        4.6 Many-Core Architecture Examples 75

        4.7 Summary 77

        References 77

        5. Scalable Computing on Large Heterogeneous CPU/GPU Supercomputers 81
        Fengshun Lu, Kaijun Ren, Junqiang Song, and Jinjun Chen

        5.1 Introduction 81

        5.2 Heterogeneous Computing Environments 82

        5.3 Scalable Programming Patterns for Large GPU Clusters 84

        5.4 Hybrid Implementations 87

        5.5 Experimental Results 89

        5.6 Conclusions 94

        Acknowledgments 94

        References 94

        6. Diagnosability of Multiprocessor Systems 97
        Chia-Wei Lee and Sun-Yuan Hsieh

        6.1 Introduction 97

        6.2 Fundamental Concepts 98

        6.3 Diagnosability of (1,2)-MCNS under PMC Model 103

        6.4 Diagnosability of 2-MCNS under MM* Model 105

        6.5 Application to Multiprocessor Systems 110

        6.6 Concluding Remarks 122

        References 122

        7. A Performance Analysis Methodology for MultiCore, Multithreaded Processors 125
        Miao Ju, Hun Jung, and Hao Che

        7.1 Introduction 125

        7.2 Methodology 126

        7.3 Simulation Tool (ST) 130

        7.4 Analytic Modeling Technique 132

        7.5 Testing 136

        7.6 Related Work 139

        7.7 Conclusions and Future Work 141

        References 141

        8. The Future in Mobile Multicore Computing 145
        Blake Hurd, Chiu C. Tan, and Jie Wu

        8.1 Introduction 145

        8.2 Background 146

        8.3 Hardware Initiatives 148

        8.4 Software Initiatives 151

        8.5 Additional Discussion 152

        8.6 Future Trends 153

        8.7 Conclusion 154

        References 155

        9. Modeling and Algorithms for Scalable and Energy-Efficient Execution on Multicore Systems 157
        Dong Li, Dimitrios S. Nikolopoulos, and Kirk W. Cameron

        9.1 Introduction 157

        9.2 Model-Based Hybrid Message-Passing Interface (MPI)/OpenMP Power-Aware Computing 158

        9.3 Power-Aware MPI Task Aggregation Prediction 170

        9.4 Conclusions 181

        References 182

        10. Cost Optimization for Scalable Communication in Wireless Networks with Movement-Based Location Management 185
        Keqin Li

        10.1 Introduction 185

        10.2 Background Information 187

        10.3 Cost Measure and Optimization for a Single User 190

        10.4 Cost Optimization with Location Update Constraint 192

        10.5 Cost Optimization with Terminal Paging Constraint 196

        10.6 Numerical Data 201

        10.7 Concluding Remarks 206

        References / 206

        11. A Framework for Semiautomatic Explicit Parallelization 209
        Ritu Arora, Purushotham Bangalore, and Marjan Mernik

        11.1 Introduction 209

        11.2 Explicit Parallelization Using MPI 210

        11.3 Building Blocks of FraSPA 211

        11.4 Evaluation of FraSPA through Case Studies 215

        11.5 Lessons Learned 221

        11.6 Related Work 222

        11.7 Summary 224

        References 224

        12. Fault Tolerance and Transmission Reliability in Wireless Networks 227
        Wolfgang W. Bein and Doina Bein

        12.1 Introduction: Reliability Issues in Wireless and Sensor Networks 227

        12.2 Reliability and Fault Tolerance of Coverage Models for Sensor Networks 230

        12.3 Fault-Tolerant k-Fold Pivot Routing in Wireless Sensor Networks 238

        12.4 Impact of Variable Transmission Range in All-Wireless Networks 244

        12.5 Conclusions and Open Problems 250

        References / 251

        13. Optimizing and Tuning Scientifi c Codes 255
        Qing Yi

        13.1 Introduction 255

        13.2 An Abstract View of the Machine Architecture 256

        13.3 Optimizing Scientifi c Codes 256

        13.4 Empirical Tuning of Optimizations 262

        13.5 Related Work 272

        13.6 Summary and Future Work 273

        Acknowledgments 273

        References 273

        14. Privacy and Confi dentiality in Cloud Computing 277
        Khaled M. Khan and Qutaibah Malluhi

        14.1 Introduction 277

        14.2 Cloud Stakeholders and Computational Assets 278

        14.3 Data Privacy and Trust 280

        14.4 A Cloud Computing Example 281

        14.5 Conclusion 288

        Acknowledgments 288

        References 288

        15. Reputation Management Systems for Peer-to-Peer Networks 291
        Fang Qi, Haiying Shen, Harrison Chandler, Guoxin Liu, and Ze Li

        15.1 Introduction 291

        15.2 Reputation Management Systems 292

        15.3 Case Study of Reputation Systems 307

        15.4 Open Problems 316

        15.5 Conclusion 316

        Acknowledgments 317

        References 317

        16. Toward a Secure Fragment Allocation of Files in Heterogeneous Distributed Systems 321
        Yun Tian, Mohammed I. Alghamdi, Xiaojun Ruan, Jiong Xie, and Xiao Qin

        16.1 Introduction 321

        16.2 Related Work 323

        16.3 System and Threat Models 325

        16.4 S-FAS: A Secure Fragment Allocation Scheme 327

        16.5 Assurance Models 329

        16.6 Sap Allocation Principles and Prototype 332

        16.7 Evaluation of System Assurance and Performance 333

        16.8 Conclusion 339

        Acknowledgments 341

        References 341

        17. Adopting Compression in Wireless Sensor Networks 343
        Xi Deng and Yuanyuan Yang

        17.1 Introduction 343

        17.2 Compression in Sensor Nodes 345

        17.3 Compression Effect on Packet Delay 348

        17.4 Online Adaptive Compression Algorithm 350

        17.5 Performance Evaluations 360

        17.6 Summary 362

        References 363

        18. GFOG: Green and Flexible Opportunistic Grids 365
        Harold Castro, Mario Villamizar, German Sotelo, Cesar O. Diaz, Johnatan Pecero, Pascal Bouvry, and Samee U. Khan

        18.1 Introduction 365

        18.2 Related Work 366

        18.3 UnaGrid Infrastructure 369

        18.4 Energy Consumption Model 372

        18.5 Experimental Results 374

        18.6 Conclusions and Future Work 382

        References 382

        19. Maximizing Real-Time System Utilization by Adjusting Task Computation Times 387
        Nasro Min-Allah, Samee Ullah Khan, Yongji Wang, Joanna Kolodziej, and Nasir Ghani

        19.1 Introduction 387

        19.2 Expressing Task Schedulability in Polylinear Surfaces 389

        19.3 Task Execution Time Adjustment Based on the P-Bound 391

        19.4 Conclusions 393

        Acknowledgments 393

        References 393

        20. Multilevel Exploration of the Optimization Landscape through Dynamical Fitness for Grid Scheduling 395
        Joanna Kolodziej

        20.1 Introduction 395

        20.2 Statement of the Problem 397

        20.3 General Characteristics of the Optimization Landscape 399

        20.4 Multilevel Metaheuristic Schedulers 402

        20.5 Empirical Analysis 408

        20.6 Conclusions 417

        References 417

        21. Implementing Pointer Jumping for Exact Inference on Many-Core Systems 419
        Yinglong Xia, Nam Ma, and Viktor K. Prasanna

        21.1 Introduction 419

        21.2 Background 420

        21.3 Related Work 422

        21.4 Pointer Jumping-Based Algorithms for Scheduling Exact Inference 423

        21.5 Analysis with Respect to Many-Core Processors 424

        21.6 From Exact Inference to Generic Directed Acyclic Graph (DAG)-Structured Computations 427

        21.7 Experiments 428

        21.8 Conclusions 434

        References 435

        22. Performance Optimization of Scientifi c Applications Using an Autonomic Computing Approach 437
        Ioana Banicescu, Florina M. Ciorba, and Srishti Srivastava

        22.1 Introduction 437

        22.2 Scientifi c Applications and Their Performance 439

        22.3 Load Balancing via DLS 441

        22.4 The Use of Machine Learning in Improving the Performance of Scientifi c Applications 441

        22.5 Design Strategies and an Integrated Framework 445

        22.6 Experimental Results, Analysis, and Evaluation 455

        22.7 Conclusions, Future Work, and Open Problems 462

        Acknowledgments 463

        References 463

        23. A Survey of Techniques for Improving Search Engine Scalability through Profi ling, Prediction, and Prefetching of Query Results 467
        C. Shaun Wagner, Sahra Sedigh, Ali R. Hurson, and Behrooz Shirazi

        23.1 Introduction 467

        23.2 Modeling User Behavior 472

        23.3 Grouping Users into Neighborhoods of Similarity 474

        23.4 Similarity Metrics 481

        23.5 Conclusion and Future Work 497

        Appendix A Comparative Analysis of Comparison Algorithms 498

        Appendix B Most Popular Searches 501

        References 502

        24. KNN Queries in Mobile Sensor Networks 507
        Wei-Guang Teng and Kun-Ta Chuang

        24.1 Introduction 507

        24.2 Preliminaries and Infrastructure-Based KNN Queries 509

        24.3 Infrastructure-Free KNN Queries 511

        24.4 Future Research Directions 519

        24.5 Conclusions 519

        References 520

        25. Data Partitioning for Designing and Simulating Efficient Huge Databases 523
        Ladjel Bellatreche, Kamel Boukhalfa, Pascal Richard, and Soumia Benkrid

        25.1 Introduction 523

        25.2 Background and Related Work 527

        25.3 Fragmentation Methodology 532

        25.4 Hardness Study 535

        25.5 Proposed Selection Algorithms 538

        25.6 Impact of HP on Data Warehouse Physical Design 544

        25.7 Experimental Studies 549

        25.8 Physical Design Simulator Tool 553

        25.9 Conclusion and Perspectives 559

        References 560

        26. Scalable Runtime Environments for Large-Scale Parallel Applications 563
        Camille Coti and Franck Cappello

        26.1 Introduction 563

        26.2 Goals of a Runtime Environment 565

        26.3 Communication Infrastructure 567

        26.4 Application Deployment 571

        26.5 Fault Tolerance and Robustness 577

        26.6 Case Studies 582

        26.7 Conclusion 586

        References 587

        27. Increasing Performance through Optimization on APU 591
        Matthew Doerksen, Parimala Thulasiraman, and Ruppa Thulasiram

        27.1 Introduction 591

        27.2 Heterogeneous Architectures 591

        27.3 Related Work 597

        27.4 OpenCL, CUDA of the Future 600

        27.5 Simple Introduction to OpenCL Programming 604

        27.6 Performance and Optimization Summary 607

        27.7 Application 607

        27.8 Summary 609

        Appendix 609

        References 612

        28. Toward Optimizing Cloud Computing: An Example of Optimization under Uncertainty 613
        Vladik Kreinovich

        28.1 Cloud Computing: Why We Need It and How We Can Make It Most Efficient 613

        28.2 Optimal Server Placement Problem: First Approximation 614

        28.3 Server Placement in Cloud Computing: Toward a More Realistic Model 618

        28.4 Predicting Cloud Growth: Formulation of the Problem and Our Approach to Solving This Problem 620

        28.5 Predicting Cloud Growth: First Approximation 621

        28.6 Predicting Cloud Growth: Second Approximation 622

        28.7 Predicting Cloud Growth: Third Approximation 623

        28.8 Conclusions and Future Work 625

        Acknowledgments 625

        Appendix: Description of Expenses Related to Cloud Computing 626

        References 626

        29. Modeling of Scalable Embedded Systems 629
        Arslan Munir, Sanjay Ranka, and Ann Gordon-Ross

        29.1 Introduction 629

        29.2 Embedded System Applications 631

        29.3 Embedded Systems: Hardware and Software 634

        29.4 Modeling: An Integral Part of the Embedded System Design Flow 638

        29.5 Single- and Multiunit Embedded System Modeling 644

        29.6 Conclusions 654

        Acknowledgments 655

        References 655

        30. Scalable Service Composition in Pervasive Computing 659
        Joanna Siebert and Jiannong Cao

        30.1 Introduction 659

        30.2 Service Composition Framework 660

        30.3 Approaches and Techniques for Scalable Service Composition in PvCE 664

        30.4 Conclusions 671

        References 671

        31. Virtualization Techniques for Graphics Processing Units 675
        Pavan Balaji, Qian Zhu, and Wu-Chun Feng

        31.1 Introduction 675

        31.2 Background 677

        31.3 VOCL Framework 677

        31.4 VOCL Optimizations 682

        31.5 Experimental Evaluation 687

        31.6 Related Work 696

        31.7 Concluding Remarks 696

        References 697

        32. Dense Linear Algebra on Distributed Heterogeneous Hardware with a Symbolic DAG Approach 699
        George Bosilca, Aurelien Bouteiller, Anthony Danalis, Thomas Herault, Piotr Luszczek, and Jack J. Dongara

        32.1 Introduction and Motivation 699

        32.2 Distributed Datafl ow by Symbolic Evaluation 701

        32.3 The DAGuE Datafl ow Runtime 705

        32.4 Datafl ow Representation 709

        32.5 Programming Linear Algebra with DAGuE 716

        32.6 Performance Evaluation 728

        32.7 Conclusion 731

        32.8 Summary 732

        References 733

        33. Fault-Tolerance Techniques for Scalable Computing 737
        Pavan Balaji, Darius Buntinas, and Dries Kimpe

        33.1 Introduction and Trends in Large-Scale Computing Systems 737

        33.2 Hardware Features for Resilience 738

        33.3 Systems Software Features for Resilience 743

        33.4 Application or Domain-Specifi c Fault-Tolerance Techniques 748

        33.5 Summary 753

        References 753

        34. Parallel Programming Models for Scalable Computing 759
        James Dinan and Pavan Balaji

        34.1 Introduction to Parallel Programming Models 759

        34.2 The Message-Passing Interface (MPI) 761

        34.3 Partitioned Global Address Space (PGAS) Models 765

        34.4 Task-Parallel Programming Models 769

        34.5 High-Productivity Parallel Programming Models 772

        34.6 Summary and Concluding Remarks 775

        Acknowledgment 775

        References 775

        35. Grid Simulation Tools for Job Scheduling and Data File Replication 777
        Javid Taheri, Albert Y. Zomaya, and Samee U. Khan

        35.1 Introduction 777

        35.2 Simulation Platforms 779

        35.3 Problem Statement: Data-Aware Job Scheduling (DAJS) 792

        References 795

        Index 799

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