Large-scale Distributed Systems and Energy Efficiency

Name: Large-scale Distributed Systems and Energy Efficiency | A Holistic View
Brand: Wiley
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A Holistic View

Jean-Marc Pierson(Autor*in)

Wiley (Verlag)

Erschienen am 5. März 2015

336 Seiten

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Inhalt

Cover
Contents
Preface
Acknowledgment
Chapter 1 Introduction to Energy Efficiency in Large-Scale Distributed Systems
1.1 Energy Consumption Status
1.2 Target of the Book
1.3 The Cost Action IC0804
1.3.1 Birth of the Action
1.3.2 Development of the Action
1.3.3 End and Future of the Action
1.4 Chapters Preview
Acknowledgement
References
Chapter 2 Hardware Leverages for Energy Reduction in Large-Scale Distributed Systems
2.1 Introduction
2.1.1 Motivation for Energy-Aware Distributed Computing
2.2 Processor
2.2.1 Context
2.2.2 Advanced Configuration and Power Interface (ACPI)
2.2.3 Vendors
2.2.4 General-Purpose Graphics Processing Unit (GPGPU)
2.2.5 ARM Architecture
2.3 Memory (DRAM)
2.3.1 Context
2.3.2 Power Consumption
2.3.3 Energy Efficiency Techniques
2.3.4 Vendors
2.4 Disk/Flash
2.4.1 Spindle Speed
2.4.2 Seek Speed
2.4.3 Power Modes
2.4.4 Power Consumption
2.4.5 Solid-State Drive (SDD)
2.5 Fan
2.6 Power Supply Unit
2.7 Network Infrastructure
2.7.1 Current Scenario
2.7.2 New Energy-Oriented Model
2.7.3 Current Advances in Networking
2.7.4 Adaptive Link Rate (ALR)
2.7.5 Low Power Idle (LPI)
2.7.6 Energy-Aware Dynamic RWA Framework
2.7.7 Energy-Aware Network Attacks
References
Chapter 3 Green Wired Networks
3.1 Economic Incentives and Green Tariffing
3.1.1 Regulatory, Economic, and Microeconomic Measures
3.1.2 Pricing Theory in Relation to Green Policies
3.1.3 COST Action Results
3.2 Network Components
3.2.1 Router
3.2.2 Network Interface Card
3.2.3 Reconfigurable Optical Add-Drop Multiplexer
3.2.4 Digital Subscriber Line Access Multiplexer
3.3 Architectures
3.3.1 Access Networks
3.3.2 Carrier Networks
3.3.3 Grid Overlay Networks
3.4 Traffic Considerations
3.5 Energy-Saving Mechanisms
3.5.1 Static Mechanisms
3.5.2 Dynamic Mechanisms
3.6 Challenges
3.7 Summary
References
Chapter 4 Green Wireless-Energy Efficiency in Wireless Networks
4.1 Introduction
4.2 Metrics and Trade-Offs in Wireless Networks
4.2.1 Metrics
4.2.2 Energy Optimization Trade-Offs
4.2.3 Summary
4.3 Measurement Methodology
4.3.1 Energy Measurement Testbeds
4.3.2 Energy Estimation Techniques
4.3.3 Energy Measurements versus Estimation
4.3.4 Summary
4.4 Energy Efficiency and QoE in Wireless Access Networks
4.4.1 Energy Issues in Cellular Networks
4.4.2 Energy Efficiency and QoE in Wireless Mesh Networks
4.4.3 Reducing Energy Consumption of the End User Device
4.4.4 Energy Measurements Revealing Video QoE Issues
4.4.5 Energy Issues in Environmental WMNs
4.4.6 Summary
4.5 Energy-Efficient Medium Access in Wireless Sensor Networks
4.5.1 MaxMAC -- An Energy-Efficient MAC Protocol
4.5.2 Real-World Testbed Experiments with MaxMAC
4.5.3 Summary
4.6 Energy-Efficient Connectivity in Ad-Hoc and Opportunistic Networks
4.6.1 Ad-Hoc Networking
4.6.2 Opportunistic and Delay-Tolerant Networking
4.6.3 Summary
4.7 Summary and Conclusions
References
Chapter 5 Power modeling
5.1 Introduction
5.2 Measuring Power
5.2.1 External Power Meters
5.2.2 Internal Power Meters
5.3 Performance Indicators
5.3.1 Source Instrumentation
5.3.2 Binary Instrumentation
5.3.3 Performance Monitoring Counters
5.3.4 Operating System Events
5.3.5 Virtual Machine Performance
5.4 Interaction between Power and Performance
5.4.1 Central Processing Unit (CPU)
5.4.2 Memory
5.4.3 Input/Output (I/O)
5.4.4 Network
5.4.5 Idle States
5.5 Power Modeling Procedure
5.5.1 Variable Selection
5.5.2 Training Data Collection
5.5.3 Learning from Data
5.5.4 Event Correlation
5.5.5 Model Evaluation Concepts
5.5.6 Power Estimation Errors
5.5.7 Related Work
5.6 Use-Cases
5.6.1 Applications
5.6.2 Single-Core Systems
5.6.3 Multi-core and Multiprocessor
5.6.4 Distributed Systems
5.7 Available Software
5.8 Conclusion
References
Chapter 6 Green Data Centers
6.1 Introduction
6.2 Overview of Energy Consumption of Hardware Infrastructure in Data Center
6.2.1 Energy Consumption Rankings and Metrics
6.2.2 Processing: CPU, GPU, and memory
6.2.3 Storage
6.2.4 Communicating Elements
6.3 Middleware Solutions that Regulate and Optimize the Energy Consumption in Data Centers
6.3.1 An Overview of the Middleware
6.3.2 System Modeling
6.3.3 Control Mechanisms
6.3.4 A Use Case of Leveraging Energy Efficiency in Data Centers
6.4 Data Center Network Architectures
6.4.1 Architectures
6.4.2 Power Consumption of Data Center Architectures
6.4.3 Additional Proposals for Energy-Efficient Data Centers
6.5 Solutions for Cooling and Heat Control in Data Center
6.5.1 Mechanical-Based Approaches
6.5.2 Software-Based Approaches
Acknowledgments
References
Chapter 7 Energy Efficiency and High-Performance Computing
7.1 Introduction
7.2 Overview of HPC Components and Latest Trends Toward Energy Efficiency
7.2.1 Architecture of the Current HPC Facilities
7.2.2 Overview of the Main HPC Components
7.2.3 HPC Performance and Energy Efficiency Evaluation
7.3 Building the Path to Exascale Computing
7.3.1 The Exascale Challenge: Hardware and Architecture Issues
7.3.2 Energy Efficiency and Resource and Job Management System (RJMS)
7.3.3 Energy-Aware Software
7.3.4 A Methodology for Energy Reduction in HPC
7.4 Energy Efficiency of Virtualization and Cloud Frameworks over HPC Workloads
7.5 Conclusion: Open Challenges
Acknowledgments
References
Chapter 8 Scheduling and Resource Allocation
8.1 Introduction: Energy-Aware Scheduling
8.2 Use of Linear Programming in Energy-Aware Scheduling
8.2.1 Finding the Optimal Solution Using a Linear Program
8.2.2 Benefits and Limitations of LP
8.3 Heuristics in Large Instances
8.3.1 Energy-Aware Greedy Algorithms
8.3.2 Vector Packing
8.3.3 Improving Fast Algorithms
8.4 Comparing Allocation Heuristics for Energy-Aware Scheduling
8.4.1 Problem Formulation
8.4.2 Allocation Heuristics
8.4.3 Results
8.5 Energy-Aware Task Allocation in Mobile Environments
8.5.1 Reference Architecture
8.5.2 Task Allocation Strategy
8.5.3 Task Allocation Algorithm
8.5.4 Performance Results
8.6 An Energy-Aware Scheduling Strategy for Allocating Computational Tasks in a Fully Decentralized Way
8.6.1 Decentralized Resources in Cloud: Overview
8.6.2 Cooperative Scheduling Anti-Load Balancing Algorithm for Cloud (CSAAC)
8.6.3 Simulation Results
8.6.4 Evaluation
8.7 Cost-Aware Scheduling with Smart Grids
8.7.1 Cost-Aware Scheduling
8.7.2 Cost-Aware Scheduling Using DE
8.7.3 Comparison of DE with Other Approaches
8.8 Heterogeneity, Cooling, DVFS, and Migration
8.8.1 Lever Interactions
8.8.2 Infrastructures
8.8.3 Resource Allocation as a Whole
8.9 Conclusions
References
Chapter 9 Energy Efficiency in P2P Systems and Applications
9.1 Introduction
9.2 General Approaches to Energy Efficiency
9.2.1 Sleep/Wakeup Approaches
9.2.2 Hierarchical Approaches
9.2.3 Resource Allocation
9.3 Energy Efficiency in File-Sharing Applications
9.3.1 Client-Server versus P2P File Sharing
9.3.2 Energy Efficiency in P2P File Sharing
9.3.3 Energy Efficiency in BitTorrent
9.3.4 Energy Efficiency in Other File-Sharing Protocols
9.4 Energy Efficiency in P2P Epidemic Protocols
9.5 Conclusions
References
Chapter 10 Toward Sustainability for Large-Scale Computing Systems: Environmental, Economic, and Standardization Aspects
10.1 Introduction
10.2 Green IT for Innovation and Innovation for Green IT
10.2.1 Defining Green IT and Its Link with Sustainability
10.2.2 Differences between Academia and Companies
10.2.3 Describing the Loop between Academia and Industry
10.3 Standardization Landscape in Green IT
10.3.1 Different Standardization Levels
10.3.2 Standardization Bodies
10.3.3 Regulations
10.3.4 Industry Groups and Professional Bodies
10.3.5 Analysis of the Standardization Actors
10.4 Modeling Actors of Innovation in Green IT and their Links
10.4.1 Researcher
10.4.2 Universities
10.4.3 Technology Transfer Office (TTO)
10.4.4 Industry
10.4.5 Funding Organization
10.4.6 Standardization Body
10.4.7 Links between Actors
10.4.8 Rating the Relationships between Actors
10.5 Using the Modeling for Deciding
10.5.1 Methodology to be Developed
10.6 Conclusion
Acknowledgment
References
Author Index
Subject Index
Wiley Series on Parallel and Distributed Computing
EULA

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