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.