Green Communications E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
This book provides a comprehensive view of green communications considering all areas of ICT including wireless and wired networks. It analyses particular concepts and practices, addressing holistic approaches in future networks considering a system perspective. It makes full use of tables, illustrations, performance graphs, case studies and examples making it accessible for a wide audience.
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Veröffentlichungsjahr: 2015
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Table of Contents
Cover
Title Page
Copyright
List of Contributors
Preface
List of Abbreviations
Chapter 1: Introduction
1.1 Origins of Green Communications
1.2 Energy Efficiency in Telecommunication Systems: Then and Now
1.3 Telecommunication System Model and Energy Efficiency
1.4 Energy Saving Concepts
1.5 Quantifying Energy Efficiency in ICT
1.6 Conclusions
References
Chapter 2: Green Communication Concepts, Energy Metrics and Throughput Efficiency for Wireless Systems
2.1 Introduction
2.2 Broadband Access Evolution
2.3 Cell Site Power Consumption Modeling
2.4 Power and Energy Metrics
2.5 Energy and Throughput Efficiency in LTE Radio Access Networks
2.6 Conclusions
References
Chapter 3: Energy-Efficiency Metrics and Performance Trade-Offs of GREEN Wireless Networks
3.1 Introduction
3.2 Energy-Efficiency Metrics
3.3 Performance Trade-Offs
3.4 Conclusion
Acknowledgments
References
Chapter 4: Embodied Energy of Communication Devices: Modeling Embodied Energy for Communication Devices
4.1 Introduction
4.2 The Extended Energy Model
4.3 Embodied/Operating Energy of a BS in Cellular Network – A Case Study
4.4 The Cell Number/Coverage Trade-Off
4.5 Discussion and Future Challenges
Acknowledgments
References
Chapter 5: Energy-Efficient Base Stations
5.1 Introduction
5.2 BS Architecture
5.3 Base Station Energy Consumption
5.4 Evolutions Towards Green Base Stations
References
Chapter 6: Energy-Efficient Mobile Network Design and Planning
6.1 Introduction
6.2 Deployment: Optimization of Cell Size
6.3 Network Design and Planning for Urban Areas
6.4 Network Design and Planning for Rural Areas
6.5 Conclusions and Future Works
References
Chapter 7: Green Radio
7.1 Energy-Efficient Design for Single-User Communications
7.2 Energy-Efficient Design for Multiuser Communications
7.3 Summary and Future Work
References
Single-user References
Multiuser MIMO References
OFDMA References
Cognitive radio References
Relay References
Chapter 8: Energy-Efficient Operation and Management for Mobile Networks
8.1 Principles
8.2 Architectures
8.3 Implementation Examples
8.4 Derivation of Area Blocking Probability
References
Chapter 9: Green Home and Enterprise Networks
9.1 Home and Enterprise Networks Today
9.2 Home and Enterprise Networks in the Context of Green Wireless Networking
9.3 Possible Savings in the Current Home and Enterprise Network Landscape
9.4 Possible Savings in Future Home and Enterprise Network
9.5 Conclusions and Future Outlook
References
Chapter 10: Towards Delay-Tolerant Cognitive Cellular Networks
10.1 Introduction
10.2 Scenarios and Applications
10.3 Previous Research
10.4 System Model and Energy Saving Schemes
10.5 Numerical Investigations
10.6 Conclusions and Future Research
References
Further Reading
Chapter 11: Green MTC, M2M, Internet of Things
11.1 Introduction
11.2 Green M2M Solutions for M2M
11.3 Green M2M Applications
11.4 Open Research Topics
11.5 Conclusions
Acknowledgements
References
Chapter 12: Energy Saving Standardisation in Mobile and Wireless Communication Systems
12.1 Introduction
12.2 Next Generation Mobile Networks (NGMN)
12.3 3rd Generation Partnership Project (3GPP)
12.4 GSM Association (GSMA)
12.5 European Telecommunications Standards Institute (ETSI)
12.6 Alliance for Telecommunication Industry Solutions (ATIS)
12.7 IEEE 802.11/Wi-Fi
12.8 Conclusions
References
Chapter 13: Green Routing/Switching and Transport
13.1 Energy-Saving Strategies for Backbone Networks
13.2 Switch-Off ILP Formulations
13.3 Switch-Off Algorithms
13.4 Table Lookup Bypass
13.5 Conclusion
References
Chapter 14: Energy Efficiency in Ethernet
14.1 Introduction to Ethernet
14.2 Energy-Efficient Ethernet (IEEE 802.3az)
14.3 Ethernet Energy Consumption Trends and Savings Estimates
14.4 Future Directions of Energy Efficiency in Ethernet
14.5 Conclusions
References
Chapter 15: Green Optical Networks: Power Savings versus Network Performance
15.1 Introduction
15.2 Device-Specific Energy Characteristics
15.3 Energy Saving for Optical Access Networks Based on WDM PONs
15.4 Energy Saving for WDM Core Networks
15.5 Summary
References
Chapter 16: Energy-Efficient Networking in Modern Data Centers
16.1 Introduction
16.2 Energy Efficiency in Data Center Networks
16.3 A Joint Energy Management Solution
16.4 Performance Evaluation
16.5 Concluding Remarks
References
Chapter 17: SDN-Enabled Energy-Efficient Network Management
17.1 Introduction
17.2 Background: Concepts for Network Operation
17.3 Energy-Efficient Network Management Practices
17.4 Energy-Efficient Network Management Enablers
17.5 Conclusions
References
Chapter 18: Energy-Efficient Protocol Design
18.1 Introduction
18.2 General Approaches to Power Management of Edge Devices
18.3 Remotely Controlled Activation and Deactivation
18.4 Proxying
18.5 Context-Aware Power Management
18.6 Power-aware Protocols and Applications
18.7 Conclusions
References
Chapter 19: Information-Centric Networking: The Case for an Energy-Efficient Future Internet Architecture
19.1 Introduction
19.2 Popular Content-Centric Enhancements
19.3 ICN: Motivation
19.4 ICN: Background and Related Work
19.5 ICN: Energy Efficiency
19.6 Summary
References
Chapter 20: Energy Efficiency Standards for Wireline Communications
20.1 Introduction
20.2 Energy-Efficient Network Equipment
20.3 Network-Based Energy Conservation
20.4 Energy-Aware Network Planning
20.5 Energy Saving Management
20.6 Energy-Efficiency Metrics, Measurements, and Testing
20.7 Conclusions
References
Chapter 21: Conclusions
21.1 Summary
21.2 Green Communication Effects on Current Networks
21.3 Future Developments
References
Index
End User License Agreement
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Guide
Cover
Table of Contents
Preface
Begin Reading
List of Illustrations
Chapter 1: Introduction
Figure 1.1 Telecommunication system emissions between 2002 and 2020 showing wireless and wireline contributions [9]
Figure 1.2 Green and energy efficiency ICT targets introduced by the major telecommunication operators around the globe
Figure 1.3 Energy efficiency forecast by GreenTouch innovation [7]
Figure 1.4 Telecommunication system model
Figure 1.5 Example of normalized traffic variation over a daily period
Chapter 2: Green Communication Concepts, Energy Metrics and Throughput Efficiency for Wireless Systems
Figure 2.1 Load activity factor for residential area
Figure 2.2 Power consuming units of a macrocell base station site
Figure 2.3 Energy and throughput Figure of merit for a macrocell RAN. (a) , (b) , (c)
Figure 2.4 Energy and throughput Figure of merit for a small-cell RAN. (a) , (b) , (c)
Chapter 4: Embodied Energy of Communication Devices: Modeling Embodied Energy for Communication Devices
Figure 4.1 Embodied and operating energies of house, car, and electronic/ICT device during their lifetimes
Figure 4.2 The proportion of embodied and operating energy during BS's lifetime, breakdowns, and trends
Figure 4.3 The simulation scenario topology
Figure 4.4 The optimal energy consumption of cellular network with respect to number of BSs (a) or cell sizes (b)
Figure 4.5 The ECR (a) and energy efficiency (b) of cellular network, covering the same area with different number of BSs
Chapter 5: Energy-Efficient Base Stations
Figure 5.1 3GPP LTE architecture
Figure 5.2 Schematic BS architecture
Figure 5.3 Radio head schematic architecture
Figure 5.4 Types of base stations (BS) (sectors and carriers). Single-sector (a) versus tri-sector (b) versus multi-carrier or multi-technology (c) BS
Figure 5.5 Types of BS (single cabinet versus RRH versus in-a-box)
Figure 5.6 Per component energy consumption breakdown for different types of BSs
Figure 5.7 Mobile traffic variation profiles from [17] (label EARTH D2.3), [18, 20] (label GreenTouch Doc2), and [19] (label ETSI TS 102 706 V1.3.1)
Figure 5.8 Example of BS power consumption as function of traffic load
Figure 5.9 Coverage tax: impact of signalling and control channels on LTE frame
Figure 5.10 Power consumption profiles for different types of base station (year 2010 values) – Courtesy of European Community's 7th Framework Program FP7 project EARTH – Legend: CO = Cooling, PS = power supply, DC = DC–DC converters, BB = baseband processing, RF = RF transceiver (w/o PA), PA = power amplifier
Figure 5.11 Power model profiles for different BS types (macro, micro and femto)
Figure 5.12 Principle of envelope tracking power amplifier (ETPA)
Figure 5.13 BS architecture evolutions: massive-MIMO and Cloud-RAN
Figure 5.14 Distributed versus centralized massive-MIMO
Chapter 6: Energy-Efficient Mobile Network Design and Planning
Figure 6.1 Cell definition
Figure 6.2 Normalized spatial traffic variation model
Figure 6.3 Blocking probability
Figure 6.4 Energy savings and daily traffic profile (a) daily traffic profile (b) energy savings
Figure 6.5 BS deployment
Figure 6.6 Azimuth antenna patterns
Figure 6.7 Power consumption breakdown
Figure 6.8
G
factor
map (upper left: 3 sectors, pathloss only; upper right: 3 sectors, pathloss + shadowing; lower left: sector 1 is switched off, pathloss only; lower right: sector 1 is switched off, pathloss + shadowing)
Figure 6.10 (a) Traffic demand and blocking probability, (b) coverage and saving ratio
Figure 6.9 Cumulative distribution function (CDF) of
G
factor
Figure 6.11 HetNet with micro cells at the edge of macro cells
Figure 6.12 Area power consumption gain
Figure 6.13 SINR map with 2 and 4 relay nodes in each sector
Figure 6.14 Energy efficiency: (a) one RN, (b) 4 RNs in (1) short, (2) middle, and (3) long BS-RN distance
Figure 6.15 Traffic distribution with two hotspots covered by the RNs
Figure 6.16 Overall ECI in the hotspot scenario with different deployments]
Figure 6.17 Control/data plane splitting
Chapter 7: Green Radio
Figure 7.1 Quasi-concavity of the energy-efficiency function
Figure 7.2 Sum energy efficiency of a two-user OFDMA system,
Chapter 8: Energy-Efficient Operation and Management for Mobile Networks
Figure 8.1 Traffic dynamics both in time domain and spatial domain
Figure 8.2 Conceptual Figure of the framework TANGO
Figure 8.3 Our vision on the new paradigm of a ubiquitous radio network
Figure 8.4 The architecture of CHORUS framework
Figure 8.5 Example of CHORUS operation procedures
Figure 8.6 CHORUS application for BS collaboration, where is the cluster size. (a) Architecture of dynamic BS clustering under CHORUS framework. (b) Average sum-rate with dynamic BS clustering. (c) Feedback overhead. (d) Calculation complexity. (simulation Figure from Ref. [17])
Figure 8.7 CHORUS application for smart dynamic BS energy saving. (a) Architecture of cell zooming under CHORUS framework. (b) Number of active BSs compared with average traffic intensity in time space with different traffic configurations
Figure 8.8 CHORUS application for smart caching assisted by relays. (a) Relay caching scheme in cellular network. (b) Cumulative average of transmission energy consumption, where we compare the optimal policy and a proposed heuristic with the baseline policy without relay caching, and the energy consumption lower bound to any policy is achieved when all the necessary contents are pre-stored in the relay
Figure 8.9 Cell zooming operations in cellular networks: (a) Cells with original size; (b) Central cell zooms in when load increases; (c) Central cell zooms out when load decreases; (d) Central cell sleeps and neighboring cells zoom out; (e) Central cell sleeps and neighboring cells transmit cooperatively
Figure 8.10 Framework of cell zooming
Figure 8.11 Techniques to implement cell zooming: (a). Cell zooms in or zooms out with physical adjustments; (b). Cells zoom out through BS cooperation and relaying
Figure 8.12 The process of cell zooming algorithms
Figure 8.13 Traffic distribution in the tested cellular network layout
Figure 8.14 Energy outage trade-off of centralized and distributed cell zooming algorithms
Figure 8.15 Cellular network architecture. The cell radius is and the maximum coverage radius is , which indicates the overlapped network structure. When some BSs turn to sleep, the active BSs extend their actual coverage from their own cells to the neighbors with sleeping BSs
Figure 8.16 System operation over time. The network keeps a constant state in each time interval , and operates action at each time spot
Figure 8.17 Simulation layout and traffic distribution. Three hotspots are formed and move along the dashed line anticlockwise every 24 hours a cycle. The highest load is , and the others are , respectively
Figure 8.18 Number of active BSs compared with average traffic intensity in time space
Figure 8.19 Traffic distribution in spatial domain
Figure 8.20 BS state distribution in spatial domain
Figure 8.21 System blocking probability variation versus time
Figure 8.22 Comparison of proposed DP BS sleeping algorithm and uniform BS sleeping algorithm
Figure 8.23 System blocking probability and dropping probability versus switching cost . LB: proposed load balancing based BS selection and user handover algorithm; SS: strongest signal based algorithm
Figure 8.24 Cumulative distribution function of mode holding time with different switching cost (J/switch)
Chapter 9: Green Home and Enterprise Networks
Figure 9.1 A typical home network scenario
Figure 9.2 Typical enterprise network scenario (simplified version)
Chapter 10: Towards Delay-Tolerant Cognitive Cellular Networks
Figure 10.1 The bit rate of mobile users within the coverage of the base station (BS) ring range
Figure 10.2 Operation and background power state of DRAM
Figure 10.3 Access for SUs modeled as an M/M/K/L queuing system
Figure 10.4 Transmission strategy for different data size under delay constraints
Figure 10.5 Energy cost from different distances to the BS (a) 400 meters to Base Station (b) 800 meters to Base Station
Figure 10.6 Importance of delay constraint in the overall energy cost
Figure 10.7 The selection from cellular BS and Wi-Fi AP
Figure 10.8 Saved energy consumption of the proposed over one month compared to the always streaming scheme
Figure 10.9 The selection from cellular BS, Wi-Fi, and TVWS AP
Figure 10.10 Battery life for different mobile applications (a) Video play back (b) Audio play back
Chapter 11: Green MTC, M2M, Internet of Things
Figure 11.1 High-level architecture for M2M according to ETSI
Figure 11.2 Example of DRX cycle
Figure 11.3 DRX mechanism in LTE
Figure 11.4 Examples of cooperative communications
Figure 11.5 Four types of D2D communications
Figure 11.6 Example of automotive applications
Figure 11.7 Example of smart metering application
Figure 11.8 Example of smart grid architecture
Chapter 12: Energy Saving Standardisation in Mobile and Wireless Communication Systems
Figure 12.1 Energy efficiency triggering for releasing and activating resources at the eNB [1]
Figure 12.2 3GPP workgroups involved in energy saving (with the related topics)
Figure 12.3 3GPP SA5 fundamental ES use cases
Figure 12.4 Detailed operation of (a) the legacy PSM and (b) the U-APSD protocols
Figure 12.5 Detailed operation of the Notice of Absence protocol in Wi-Fi Direct
Chapter 13: Green Routing/Switching and Transport
Figure 13.1 IP-over-WDM network architecture
Figure 13.2 Simplified model of an IP router
Figure 13.3 General scheme of an IP line card
Figure 13.4
E
versus
p
Figure 13.5 Optimal solution of flow-based (FLOW) and destination-based formulations (DBF) in a 12-node network scenario
Figure 13.6 Graphical representation of a router with TLB enabled on all line cards
Figure 13.7 Example of paths modification in a network with a LC in TLB mode
Chapter 14: Energy Efficiency in Ethernet
Figure 14.1 Illustration of the low power idle mode defined in energy-efficient Ethernet
Figure 14.2 Energy consumption versus link load for 1000BASE-T (a) and 10GBASE-T (b)
Chapter 15: Green Optical Networks: Power Savings versus Network Performance
Figure 15.1 Energy profile of Tx
Figure 15.2 Packet delays
Figure 15.3 Energy profiles when exploiting traffic diversity
Figure 15.4 Average high-priority packet delays when exploiting traffic diversity
Figure 15.5 Power versus blocking, a trade-off example: power minimization strategy
Figure 15.6 Power versus blocking, a trade-off example: path hop minimization strategy
Figure 15.7 Comparison of RWA approaches
Figure 15.8 Blocking probability versus offered network load when minimizing power consumption and resource utilization
Figure 15.9 Average power saving versus offered network load
Chapter 16: Energy-Efficient Networking in Modern Data Centers
Figure 16.1 Energy efficiency considerations in the data center
Figure 16.2 Network topologies considered in the context of energy efficiency. (a) Common date center network topology 6 10. (b) Fat tree topology, based on 6 10. (c) Elastic tree (fat tree subset), based on 10. (d) Flattened butterfly topology for 64 nodes based on 3
Figure 16.3 Overview of the proposed approach
Figure 16.4 Switch energy model
Figure 16.5 Energy consumption
E
of network equipment in kW h for various scenarios
Chapter 17: SDN-Enabled Energy-Efficient Network Management
Figure 17.1 SDN concept sketch
Figure 17.2 SDN/NFV functional composition
Figure 17.3 LCP–PMP interactions (from LCP control action (a) to its implementation on the physical component (b))
Figure 17.4 LCP–NCP interactions
Figure 17.5 SDN-based NCPs
Figure 17.6 SDN/NFV-based energy-efficient network architecture
Figure 17.7 GAL–NCP–LCP communications in the SDN framework
Figure 17.8 The hierarchical architecture of a multichassis network device
Chapter 18: Energy-Efficient Protocol Design
Figure 18.1 General approaches to power management of Internet edge devices
Figure 18.2 Power management proxy operation scheme
Figure 18.3 EE-BitTorrent operation scheme
Figure 18.4 TCP connection splitting mechanism
Chapter 19: Information-Centric Networking: The Case for an Energy-Efficient Future Internet Architecture
Figure 19.1 Message flow highlighting the name-based data retrieval in ICN. Requested data can be obtained from one of the multiple sources of the data. In this case, the data can be obtained from the cache of an ICN router, from a CDN service, from other clients, or directly from the original publisher (see Step-4). Step-2 shows that the Interest is added to the Pending Interest/Request Table (PIT), and in Step-6 we can observe that the data is stored in the cache of the router before being forwarded
Figure 19.2 Message flow for obtaining data in a standard IP and ICN environment. (a) IP message flow: A standard HTTP Get command for data doc1.txt issued from a client to a server. The server receives the request even if other sources of that data exist closer to the client. (b) ICN message flow: A standard ICN Get command for data doc1.txt being issued to the ICN network and the first hop ICN router directing it to a closer source for that data
Figure 19.3 Message flow comparing the case of multiple simultaneous HTTP Get versus ICN Get. (a) IP message flow: Multiple simultaneous HTTP requests for the same data doc1.txt is forwarded to the server. Therefore the server responds with M+1 copies of the same data. (b) ICN message flow: Multiple simultaneous ICN requests for the same data doc1.txt is added to the Pending Request Table and only one ICN request is forwarded to the closest source
Figure 19.4 Message flow comparing a standard HTTP Get versus ICN Get. (a) IP message flow: Multiple requests for the same data doc1.txt is being forwarded to the server. The server therefore responds with a copy of the data for every single request received. (b) ICN message flow: Multiple requests for the same data doc1.txt is being served by the first hop ICN router because it has the data in its cache after the first interaction
Figure 19.5 Message flow comparing a continuous HTTP Get versus ICN Get in the presence of a new data source (at Time
X
). (a) IP message flow: The requests are sent to the original server even after a new source for the data appears. (b) ICN message flow: The requests are forwarded to the CDN source after time
X
because it is closer in a seamless fashion
Figure 19.6 Message flow comparing a continuous HTTP Get versus ICN Get in the absence of the initial data source (at time
X
). (a) IP message flow: The connection is terminated once the source switches off after
X
minutes. (b) ICN message flow: The requests are forwarded to the CDN source after time
X
seamlessly
Figure 19.7 Message flow comparing a HTTP Get versus ICN Get when the node moves from one base-station/operator/location to another (at time
X
). (a) IP message flow: Though the client has moved, the connection to the initial data source is still maintained, resulting in inefficient usage. (b) ICN message flow: The requests are forwarded to the CDN source that is closer to the new location seamlessly
Chapter 20: Energy Efficiency Standards for Wireline Communications
Figure 20.1 An overview of the BBF mobile Backhaul architecture based on Ref. [6]
Figure 20.2 ITU-T energy control framework [Y.3021]
Chapter 21: Conclusions
Figure 21.1 Splitting data and signalling
List of Tables
Chapter 1: Introduction
Table 1.1 Traffic projections between 2010 and 2020 for the mobile access, wireline access and core networks modeled by GreenTouch for the Mature Market segment [7]
Chapter 2: Green Communication Concepts, Energy Metrics and Throughput Efficiency for Wireless Systems
Table 2.1 CAGR for devices and traffic per device
Table 2.2 LTE BS site power consumption estimates based on 2010 vendor data
Table 2.3 BTS technology parameters
Table 2.4 HetNet versus small cell—energy and throughput gains
Chapter 4: Embodied Energy of Communication Devices: Modeling Embodied Energy for Communication Devices
Table 4.1 The constituents of initial embodied energy for materials and processes during the production of a general BS
Chapter 5: Energy-Efficient Base Stations
Table 5.1 Macro/micro/pico/femto
Table 5.2 BS power profile parameters
Chapter 8: Energy-Efficient Operation and Management for Mobile Networks
Table 8.1 Handover performance with different switching cost
Chapter 10: Towards Delay-Tolerant Cognitive Cellular Networks
Table 10.1 YouTube video statistics per digital devices
Table 10.2 Probabilities and energy consumptions in different area
Table 10.3 Simulation results
Chapter 12: Energy Saving Standardisation in Mobile and Wireless Communication Systems
Table 12.1 ES related efforts in 3GPP's standardisation
Table 12.2 Combinations of RATs for inter-RAT ES
Chapter 13: Green Routing/Switching and Transport
Table 13.1 Main features of the flow-based algorithms
Table 13.2 Main features of the destination-based algorithms
Chapter 14: Energy Efficiency in Ethernet
Table 14.1 Minimum wake, sleep, frame transmission times, and single frame efficiencies for different link speeds
Table 14.2 1000BASE-T link counts by device type (millions; United States only, 2010)
Table 14.3 10GBASE-T link counts by device type (millions; United States only, 2010)
Table 14.4 Assumptions and results for EEE savings (United States only, 2010 stock)
Chapter 15: Green Optical Networks: Power Savings versus Network Performance
Table 15.1 Power consumption values of optical access network equipment
Table 15.2 Power consumption values of optical core network equipment
Table 15.3 Average power saved per request (%) as a function of the network load and
α
Table 15.4 Blocking probability as a function of the network load and
α
Chapter 18: Energy-Efficient Protocol Design
Table 18.1 List of proxy-based solutions
Chapter 20: Energy Efficiency Standards for Wireline Communications
Table 20.1 PoE PD classification and power supply
Green Communications
Principles, Concepts And Practice
Edited by
Konstantinos Samdanis, Peter Rost, Andreas Maeder, Michela Meo and Christos Verikoukis
This edition first published 2015
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List of Contributors
Muhammad Ali Imran
, Institute for Communication Systems (ICS), University of Surrey, Guildford, Surrey, UK
Luis Alonso
, Department of Signal Theory and Communications, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
Jesus Alonso-Zarate
, Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Barcelona, Spain
Giuseppe Anastasi
, Department of Information Engineering, University of Pisa, Pisa, Italy
Mayutan Arumaithurai
, Institute of Computer Science, Computer Networks Group, University of Goettingen, Goettingen, Germany
Michael Bennett
, Lawrence Berkeley National Laboratory, Vallejo, USA
Raffaele Bolla
, Department of Electrical, Electronic and Telecommunications Engineering, and Naval Architecture (DITEN), University of Genoa, Genoa, Italy; National Inter-university Consortium for Telecommunications (CNIT), University of Genoa Research Unit, Genoa, Italy
Simone Brienza
, Department of Information Engineering, University of Pisa, Pisa, Italy
Roberto Bruschi
, National Inter-university Consortium for Telecommunications (CNIT), University of Genoa Research Unit, Genoa, Italy
Łukasz Budzisz
, Telecommunication Networks Group, Technische Universität Berlin, Berlin, Germany
Alessandro Carrega
, Department of Electrical, Electronic and Telecommunications Engineering, and Naval Architecture (DITEN), University of Genoa, Genoa, Italy; National Inter-university Consortium for Telecommunications (CNIT), University of Genoa Research Unit, Genoa, Italy
C. Cavdar
, Communication Systems Department, KTH Royal Institute of Technology, Kista, Sweden
I. Cerutti
, Institute of Communication, Information and Perception Technologies, Scuola Superiore Sant'Anna, Pisa, Italy
J. Chen
, Communication Systems Department, KTH Royal Institute of Technology, Kista, Sweden
Min Chen
, Huazhong University of Science and Technology, Wuhan, Hubei, China
Luca Chiaraviglio
, DIET Department, University of Rome “Sapienza”, Rome, Italy
Ken Christensen
, University of South Florida, Florida, USA
Antonio Cianfrani
, DIET Department, University of Rome “Sapienza”, Rome, Italy
Angelo Coiro
, DIET Department, University of Rome “Sapienza”, Rome, Italy
Alberto Conte
, Alcatel-Lucent Bell Labs, Centre de Villarceaux, Nozay, France
Franco Davoli
, Department of Electrical, Electronic and Telecommunications Engineering, and Naval Architecture (DITEN), University of Genoa, Genoa, Italy; National Inter-university Consortium for Telecommunications (CNIT), University of Genoa Research Unit, Genoa, Italy
Mischa Dohler
, Centre for Telecommunications Research, King's College London (KCL), London, UK
Dominique Dudkowski
, NEC Europe Ltd., NEC Laboratories Europe, Heidelberg, Germany
Simon Fletcher
, NEC Telecom MODUS Ltd, Surrey, UK
Vasilis Friderikos
, Centre for Telecommunications Research, King's College London, London, UK
Xiaohu Ge
, Huazhong University of Science and Technology, Wuhan, Hubei, China
Toru Hasegawa
, Information Networking, Osaka University, Osaka, Japan
Peer Hasselmeyer
, NEC Europe Ltd., NEC Laboratories Europe, Heidelberg, Germany
Nageen Himayat
, Intel Corporation, Intel Labs, Santa Clara, USA
Tobias Hoßfeld
, University of Würzburg, Communication Networks, Würzburg, Germany; University of Duisburg-Essen, Modeling of Adaptive Systems, Essen, Germany
Iztok Humar
, Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia
Taewon Hwang
, Yonsei University, Department of Electrical and Electronic Engineering, Seoul, Korea
Michael Jarschel
, University of Würzburg, Communication Networks, Würzburg, Germany; Nokia Networks, Munich, Germany
Minho Jo
, Korea University, Seoul, Korea
Thomas Kessler
, Deutsche Telekom AG, Darmstadt, Germany
Younggap Kwon
, Yonsei University, Department of Electrical and Electronic Engineering, Seoul, Korea
Andres Laya
, KTH Royal Institute of Technology, Kista, Sweden
Marco Listanti
, DIET Department, University of Rome “Sapienza”, Rome, Italy
Giuseppe Lo Re
, DICGIM, University of Palermo, Palermo, Italy
Andreas Maeder
, NEC Europe Ltd, Heidelberg, Germany
Juan Antonio Maestro
, Universidad Antonio de Nebrija, Madrid, Spain
Michela Meo
, Politecnico di Torino, Torino, Italy
Guowang Miao
, KTH Royal Institute of Technology, Communications Department, Stockholm, Sweden
A. Mohammad
, Electrical Engineering Department, Linköping University, Linköping, Sweden
P. Monti
, Communication Systems Department, KTH Royal Institute of Technology, Kista, Sweden
D. C. Mur
, NEC Europe Ltd, Heidelberg, Germany
Zhisheng Niu
, Department of Electronic Engineering, Tsinghua University, Beijing, China
Bruce Nordman
, Lawrence Berkeley National Laboratory, Vallejo, USA
Timothy O'Farrell
, University of Sheffield, Department of Electronic and Electrical Engineering, Sheffield, UK
Marco Ortolani
, DICGIM, University of Palermo, Palermo, Italy
Hyunsung Park
, Yonsei University, Department of Electrical and Electronic Engineering, Seoul, Korea
Manuel Paul
, Deutsche Telekom AG, Berlin, Germany
Marco Polverini
, DIET Department, University of Rome “Sapienza”, Rome, Italy
G. Punz
, NEC Europe Ltd, Heidelberg, Germany
Yinan Qi
, Institute for Communication Systems (ICS), University of Surrey, Guildford, Surrey, UK
Kadangode K. Ramakrishnan
, Riverside Computer Science and Engineering, University of California, Riverside, USA
Marco Di Renzo
, Paris-Saclay University, Laboratory of Signals and Systems, CNRS – CentraleSupelec – University Paris-Sud XI, Gif-sur-Yvette, Paris, France
Pedro Reviriego
, Universidad Antonio de Nebrija, Madrid, Spain
Peter Rost
, NEC Europe Ltd, Heidelberg, Germany
Konstantinos Samdanis
, NEC Europe Ltd, Heidelberg, Germany
Rahim Tafazolli
, Institute for Communication Systems (ICS), University of Surrey, Guildford, Surrey, UK
L. Velasco
, Department of Computers Architecture, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain
Christos Verikoukis
, Telecommunications Technological Centre of Catalonia, Barcelona, Spain
P. Wiatr
, Communication Systems Department, KTH Royal Institute of Technology, Kista, Sweden
Rolf Winter
, NEC Europe Ltd., Heidelberg, Germany
Adam Wolisz
, Telecommunication Networks Group, Technische Universität Berlin, Berlin, Germany
L. Wosinska
, Communication Systems Department, KTH Royal Institute of Technology, Kista, Sweden
Lin Xiang
, Huazhong University of Science and Technology, Wuhan, Hubei, China
Jing Zhang
, Huazhong University of Science and Technology, Wuhan, Hubei, China
Bi Zhao
, Centre for Telecommunications Research, King's College London, London, UK
Sheng Zhou
, Department of Electronic Engineering, Tsinghua University, Beijing, China
Preface
Energy efficiency and green communications aim at addressing the quest for sustainability regarding power resources and environmental conditions. For telecommunication service providers, energy efficiency merely means cost reduction, in terms of capital and operational expenditures. For government bodies and regulators, energy efficiency and green communications is a duty to strengthen corporate responsibility towards the environment and motivate an ecological generation of network equipment and systems.
Energy efficiency evolved into a significant parameter of equipment design, architecture and management of telecommunication systems but has not been taken into account until the Kyoto Protocol early in 1997, which raised concerns regarding global warming. Initial efforts concentrated on network edge equipment and peripherals, communication protocols and then progressively on wireless radio and cellular systems as well as on fixed networks. Nowadays, after a steep increase of studies, innovation and practice, energy efficiency and green communications are entering a mature phase, with established solutions addressing particular aspects of a telecommunication system.
Despite such momentum, the potential for energy conservation is still huge especially since advanced services and applications are increasing the complexity of network usage and the demand for enhanced capacity, speed and network resources, driving the growth of network infrastructure deployment. In addition, such earlier approaches prepared the ground for further advance contributions that consider different equipment design features, a combination of communication protocols and holistic network mechanisms that are more sophisticated and comprehensive since they take into account several diverse aspects and cross-layer issues of a telecommunication system.
In structuring the material contained in this book, our goal is to elaborate the fundamentals of energy efficiency and green communications exploring the main challenges, mechanisms and practice considering both wireless and wireline systems. Wireless and wireline communications are organized into two different corresponding sections that address equipment, management, architecture, communication protocols, applications and different deployment aspects. Each chapter is organized in a tutorial nature that contains well-established solutions and the main associated findings in a way that is easy for the reader to follow, providing also a list of references for the interested reader to explore further. In closing each section, a dedicated chapter summarizes the current advances related to the main standardization bodies and list all related specifications and studies in an effort to enhance the view of the reader regarding the adoption and exploitation of such research technologies into industry products and solutions and to provide the basics for standardization engineers who wish to enter the field.
Often a choice had to be made about including certain concepts, evolving research areas and mechanisms, but given the limited space, the focus remained on material that enable the reader to understand the basics in order to innovate the development of more advance solutions. We hope that this book can serve the reader as a first orientation and as a tool for experts to dive deeper into this new vigorous and fascinating area.
Konstantinos Samdanis NEC Europe Ltd
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
Lesen Sie weiter in der vollständigen Ausgabe!
