Energy-Efficient Distributed Computing Systems (eBook, PDF)

Redaktion: Zomaya, Albert Y.; Lee, Young Choon

• Format: PDF

Produktbeschreibung

The energy consumption issue in distributed computing systems raises various monetary, environmental and system performance concerns. Electricity consumption in the US doubled from 2000 to 2005. From a financial and environmental standpoint, reducing the consumption of electricity is important, yet these reforms must not lead to performance degradation of the computing systems. These contradicting constraints create a suite of complex problems that need to be resolved in order to lead to 'greener' distributed computing systems. This book brings together a group of outstanding researchers that investigate the different facets of green and energy efficient distributed computing. Key features: * One of the first books of its kind * Features latest research findings on emerging topics by well-known scientists * Valuable research for grad students, postdocs, and researchers * Research will greatly feed into other technologies and application domains

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 856
• Erscheinungstermin: 6. August 2012
• Englisch
• ISBN-13: 9781118341988
• Artikelnr.: 37339428

Autorenporträt

ALBERT Y. ZOMAYA is the Chair Professor of High Performance Computing & Networking in the School of Information Technologies, The University of Sydney. He is a Fellow of the IEEE, the American Association for the Advancement of Science, and the Institution of Engineering and Technology, and a Distinguished Engineer of the ACM. He has authored seven books and some 400 articles in technical journals. YOUNG CHOON LEE, PhD, is with the Centre for Distributed and High Performance Computing, School of Information Technologies, The University of Sydney.

Inhaltsangabe

PREFACE xxix ACKNOWLEDGMENTS xxxi CONTRIBUTORS xxxiii 1 POWER ALLOCATION
AND TASK SCHEDULING ON MULTIPROCESSOR COMPUTERS WITH ENERGY AND TIME
CONSTRAINTS 1 Keqin Li 1.1 Introduction 1 1.2 Preliminaries 5 1.3 Problem
Analysis 10 1.4 Pre-Power-Determination Algorithms 16 1.5
Post-Power-Determination Algorithms 28 1.6 Summary and Further Research 33
References 34 2 POWER-AWARE HIGH PERFORMANCE COMPUTING 39 Rong Ge and Kirk
W. Cameron 2.1 Introduction 39 2.2 Background 41 2.3 Related Work 45 2.4
PowerPack: Fine-Grain Energy Profiling of HPC Applications 48 2.5
Power-Aware Speedup Model 59 2.6 Model Usages 69 2.7 Conclusion 73
References 75 3 ENERGY EFFICIENCY IN HPC SYSTEMS 81 Ivan Rodero and Manish
Parashar 3.1 Introduction 81 3.2 Background and Related Work 83 3.3
Proactive, Component-Based Power Management 88 3.4 Quantifying Energy
Saving Possibilities 91 3.5 Evaluation of the Proposed Strategies 95 3.6
Results 97 3.7 Concluding Remarks 102 3.8 Summary 103 References 104 4 A
STOCHASTIC FRAMEWORK FOR HIERARCHICAL SYSTEM-LEVEL POWER MANAGEMENT 109
Peng Rong and Massoud Pedram 4.1 Introduction 109 4.2 Related Work 111 4.3
A Hierarchical DPM Architecture 113 4.4 Modeling 114 4.5 Policy
Optimization 122 4.6 Experimental Results 125 4.7 Conclusion 130 References
130 5 ENERGY-EFFICIENT RESERVATION INFRASTRUCTURE FOR GRIDS, CLOUDS, AND
NETWORKS 133 Anne-Ce¿ cile Orgerie and Laurent Lefe` vre 5.1 Introduction
133 5.2 Related Works 134 5.3 ERIDIS: Energy-Efficient Reservation
Infrastructure for Large-Scale Distributed Systems 138 5.4 EARI:
Energy-Aware Reservation Infrastructure for Data Centers and Grids 147 5.5
GOC: Green Open Cloud 149 5.6 HERMES: High Level Energy-Aware Model for
Bandwidth Reservation in End-To-End Networks 152 5.7 Summary 158 References
158 6 ENERGY-EFFICIENT JOB PLACEMENT ON CLUSTERS, GRIDS, AND CLOUDS 163
Damien Borgetto, Henri Casanova, Georges Da Costa, and Jean-Marc Pierson
6.1 Problem and Motivation 163 6.2 Energy-Aware Infrastructures 164 6.3
Current Resource Management Practices 167 6.4 Scientific and Technical
Challenges 170 6.5 Energy-Aware Job Placement Algorithms 172 6.6 Discussion
180 6.7 Conclusion 183 References 184 7 COMPARISON AND ANALYSIS OF GREEDY
ENERGY-EFFICIENT SCHEDULING ALGORITHMS FOR COMPUTATIONAL GRIDS 189 Peder
Lindberg, James Leingang, Daniel Lysaker, Kashif Bilal, Samee Ullah Khan,
Pascal Bouvry, Nasir Ghani, Nasro Min-Allah, and Juan Li 7.1 Introduction
189 7.2 Problem Formulation 191 7.3 Proposed Algorithms 193 7.4
Simulations, Results, and Discussion 203 7.5 Related Works 211 7.6
Conclusion 211 References 212 8 TOWARD ENERGY-AWARE SCHEDULING USING
MACHINE LEARNING 215 Josep LL. Berral, In~ igo Goiri, Ramon Nou, Ferran
Julia` , Josep O. Fitö , Jordi Guitart, Ricard Gavaldä , and Jordi Torres
8.1 Introduction 215 8.2 Intelligent Self-Management 218 8.3 Introducing
Power-Aware Approaches 225 8.4 Experiences of Applying ML on Power-Aware
Self-Management 230 8.5 Conclusions on Intelligent Power-Aware
Self-Management 238 References 240 9 ENERGY EFFICIENCY METRICS FOR DATA
CENTERS 245 Javid Taheri and Albert Y. Zomaya 9.1 Introduction 245 9.2
Fundamentals of Metrics 250 9.3 Data Center Energy Efficiency 252 9.4
Available Metrics 260 9.5 Harmonizing Global Metrics for Data Center Energy
Efficiency 267 References 268 10 AUTONOMIC GREEN COMPUTING IN LARGE-SCALE
DATA CENTERS 271 Haoting Luo, Bithika Khargharia, Salim Hariri, and Youssif
Al-Nashif 10.1 Introduction 271 10.2 Related Technologies and Techniques
272 10.3 Autonomic Green Computing: A Case Study 283 10.4 Conclusion and
Future Directions 297 References 298 11 ENERGY AND THERMAL AWARE SCHEDULING
IN DATA CENTERS 301 Gaurav Dhiman, Raid Ayoub, and Tajana S. Rosing 11.1
Introduction 301 11.2 Related Work 302 11.3 Intermachine Scheduling 305
11.4 Intramachine Scheduling 315 11.5 Evaluation 321 11.6 Conclusion 333
References 334 12 QOS-AWARE POWER MANAGEMENT IN DATA CENTERS 339 Jiayu Gong
and Cheng-Zhong Xu 12.1 Introduction 339 12.2 Problem Classification 340
12.3 Energy Efficiency 344 12.4 Power Capping 351 12.5 Conclusion 353
References 356 13 ENERGY-EFFICIENT STORAGE SYSTEMS FOR DATA CENTERS 361
Sudhanva Gurumurthi and Anand Sivasubramaniam 13.1 Introduction 361 13.2
Disk Drive Operation and Disk Power 362 13.3 Disk and Storage Power
Reduction Techniques 366 13.4 Using Nonvolatile Memory and Solid-State
Disks 371 13.5 Conclusions 372 References 373 14 AUTONOMIC
ENERGY/PERFORMANCE OPTIMIZATIONS FOR MEMORY IN SERVERS 377 Bithika
Khargharia and Mazin Yousif 14.1 Introduction 378 14.2 Classifications of
Dynamic Power Management Techniques 380 14.3 Applications of Dynamic Power
Management (DPM) 382 14.4 Autonomic Power and Performance Optimization of
Memory Subsystems in Server Platforms 384 14.5 Conclusion 391 References
391 15 ROD: A PRACTICAL APPROACH TO IMPROVING RELIABILITY OF
ENERGY-EFFICIENT PARALLEL DISK SYSTEMS 395 Shu Yin, Xiaojun Ruan, Adam
Manzanares, and Xiao Qin 15.1 Introduction 395 15.2 Modeling Reliability of
Energy-Efficient Parallel Disks 396 15.3 Improving Reliability of MAID via
Disk Swapping 401 15.4 Experimental Results and Evaluation 405 15.5 Related
Work 411 15.6 Conclusions 412 References 413 16 EMBRACING THE MEMORY AND
I/O WALLS FOR ENERGY-EFFICIENT SCIENTIFIC COMPUTING 417 Chung-Hsing Hsu and
Wu-Chun Feng 16.1 Introduction 417 16.2 Background and Related Work 420
16.3 ß-Adaptation: A New DVFS Algorithm 423 16.4 Algorithm Effectiveness
429 16.5 Conclusions and Future Work 438 References 439 17 MULTIPLE
FREQUENCY SELECTION IN DVFS-ENABLED PROCESSORS TO MINIMIZE ENERGY
CONSUMPTION 443 Nikzad Babaii Rizvandi, Albert Y. Zomaya, Young Choon Lee,
Ali Javadzadeh Boloori, and Javid Taheri 17.1 Introduction 443 17.2 Energy
Efficiency in HPC Systems 444 17.3 Exploitation of Dynamic
Voltage-Frequency Scaling 446 17.4 Preliminaries 448 17.5 Energy-Aware
Scheduling via DVFS 450 17.6 Experimental Results 456 17.7 Conclusion 461
References 461 18 THE PARAMOUNTCY OF RECONFIGURABLE COMPUTING 465 Reiner
Hartenstein 18.1 Introduction 465 18.2 Why Computers are Important 466 18.3
Performance Progress Stalled 472 18.4 The Tail is Wagging the Dog
(Accelerators) 488 18.5 Reconfigurable Computing 494 References 529 19
WORKLOAD CLUSTERING FOR INCREASING ENERGY SAVINGS ON EMBEDDED MPSOCS 549
Ozcan Ozturk, Mahmut Kandemir, and Sri Hari Krishna Narayanan 19.1
Introduction 549 19.2 Embedded MPSoC Architecture, Execution Model, and
Related Work 550 19.3 Our Approach 551 19.4 Experimental Evaluation 560
19.5 Conclusions 564 References 565 20 ENERGY-EFFICIENT INTERNET
INFRASTRUCTURE 567 Weirong Jiang and Viktor K. Prasanna 20.1 Introduction
567 20.2 SRAM-Based Pipelined IP Lookup Architectures: Alternative to TCAMs
571 20.3 Data Structure Optimization for Power Efficiency 573 20.4
Architectural Optimization to Reduce Dynamic Power Dissipation 580 20.5
Related Work 588 20.6 Summary 589 References 589 21 DEMAND RESPONSE IN THE
SMART GRID: A DISTRIBUTED COMPUTING PERSPECTIVE 593 Chen Wang and Martin De
Groot 21.1 Introduction 593 21.2 Demand Response 595 21.3 Demand Response
as a Distributed System 600 21.4 Summary 611 References 611 22 RESOURCE
MANAGEMENT FOR DISTRIBUTED MOBILE COMPUTING 615 Jong-Kook Kim 22.1
Introduction 615 22.2 Single-Hop Energy-Constrained Environment 617 22.3
Multihop Distributed Mobile Computing Environment 635 22.4 Future Work 647
References 647 23 AN ENERGY-AWARE FRAMEWORK FOR MOBILE DATA MINING 653
Carmela Comito, Domenico Talia, and Paolo Trunfio 23.1 Introduction 653
23.2 System Architecture 654 23.3 Mobile Device Components 657 23.4 Energy
Model 659 23.5 Clustering Scheme 664 23.6 Conclusion 670 References 670 24
ENERGY AWARENESS AND EFFICIENCY IN WIRELESS SENSOR NETWORKS: FROM PHYSICAL
DEVICES TO THE COMMUNICATION LINK 673 Flä via C. Delicato and Paulo F.
Pires 24.1 Introduction 673 24.2 WSN and Power Dissipation Models 676 24.3
Strategies for Energy Optimization 683 24.4 Final Remarks 701 References
702 25 NETWORK-WIDE STRATEGIES FOR ENERGY EFFICIENCY IN WIRELESS SENSOR
NETWORKS 709 Flä via C. Delicato and Paulo F. Pires 25.1 Introduction 709
25.2 Data Link Layer 711 25.3 Network Layer 719 25.4 Transport Layer 725
25.5 Application Layer 729 25.6 Final Remarks 740 References 741 26 ENERGY
MANAGEMENT IN HETEROGENEOUS WIRELESS HEALTH CARE NETWORKS 751 Nima Nikzad,
Priti Aghera, Piero Zappi, and Tajana S. Rosing 26.1 Introduction 751 26.2
System Model 753 26.3 Collaborative Distributed Environmental Sensing 755
26.4 Task Assignment in a Body Area Network 760 26.5 Results 771 26.6
Conclusion 784 References 785 INDEX 787