: Thant Zin Oo, Nguyen H. Tran, Shaolei Ren, Choong Seon Hong
: A Survey on Coordinated Power Management in Multi-Tenant Data Centers
: Springer-Verlag
: 9783319660622
: 1
: CHF 85.20
:
: Elektronik, Elektrotechnik, Nachrichtentechnik
: English
: 176
: Wasserzeichen/DRM
: PC/MAC/eReader/Tablet
: PDF
This book investigates the coordinated power management of multi-tenant data centers that account for a large portion of the data center industry. The authors include discussion of their quick growth and their electricity consumption, which has huge economic and environmental impacts. This book covers the various coordinated management solutions in the existing literature focusing on efficiency, sustainability, and demand response aspects. First, the authors provide a background on the multi-tenant data center covering the stake holders, components, power infrastructure, and energy usage. Then, each power management mechanism is described in terms of motivation, problem formulation, challenges and solution.

Thant Zin Oo received the B.Eng. degree in electrical systems and electronics at Myanmar Maritime University, Thanlyin, Myanmar in 2008 and the B.S. degree in computing and information system from London Metropolitan University, U.K., in 2008, for which he received grant from the British Council. He is currently working towards Ph.D. degree in computer science and engineering from Kyung Hee University, Korea, for which he was awarded a scholarship in 2010. His research interests include wireless communications, network virtualization, data centers, and sustainable energy.

Nguyen H. Tran received the BS degree from Hochiminh City University of Technology and Ph.D. degree from Kyung Hee University, in electrical and computer engineering, in 2005 and 2011, respectively. Since 2012, he has been an Assistant Professor with Department of Computer Science and Engineering, Kyung Hee University. His research interest is to applying analytic techniques of optimization, game theory, and stochastic modeling to cutting-edge applications such as cloud and mobile-edge computing, data centers, heterogeneous wireless networks, and big data for networks. He received the best KHU thesis award in engineering in 2011 and best paper award at IEEE ICC 2016. He is the Editor of IEEE Transactions on Green Communications and Networking. 

Shaolei Ren is an Assistant Professor of Electrical and Computer Engineering at University of California, Riverside. He received his B.E. from Tsinghua University in 2006, M.Phil. from Hong Kong University of Science and Technology in 2008, and Ph.D. from University of California, Los Angeles in 2012, all in electrical and computer engineering. His research interests include cloud computing, data centers, and network economics. He was a recipient of the U.S. NSF Faculty Early Career Development (CAREER) Award in 2015. He also received best paper awards from several conferences, including ACM e-Energy'16, IEEE ICC'16 and IEEE ICC'09.

Choong Seon Hong received the B.S. and M.S. degrees in electronic engineering from Kyung Hee University, Seoul, South Korea, in 1983 and 1985, respectively, and the Ph.D. degree from Keio University, Minato, Japan, in 1997. In 1988, he joined Korea Telecom, where he worked on broadband networks as a Member of Technical Staff. In September 1993, he joined Keio University. He worked for the Telecommunications Network Laboratory, Korea Telecom, as a Senior Member of Technical Staff and the Director of the Networking Research Team until August 1999. Since September 1999, he has been a Professor with the Department of Computer Science and Engineering, Kyung Hee University. His research interests include future Internet, ad hoc networks, network management, and network security. He is a member of ACM, IEICE, IPSJ, KIISE, KICS, KIPS, and OSIA. He has served as the General Chair, a TPC Chair/Member, or an Organizing Committee Member for international conferences such as NOMS, IM, APNOMS, E2EMON, CCNC, ADSN, ICPP, DIM, WISA, BcN, TINA, SAINT, and ICOIN. In addition, he is currently an Associate Editor of the IEEE Transactions on Network and Service Management, International Journal of Network Management, and Journal of Communications and Networks and an Associate Technical Editor of the IEEE Communications Magazine.

Preface5
Acknowledgement6
Contents7
Part I Introduction11
1 Overview12
1.1 Importance of Multi-Tenant Data Centers14
1.1.1 Operator's Perspective14
1.1.2 Tenants' Perspective14
1.2 State-of-the-Art Research on Data Centers16
1.3 Potential of Coordinated Power Management17
1.3.1 Importance of Coordinated Power Management17
1.3.2 Coordinated Power Management in Multi-Tenant Data Centers18
1.4 Research Directions for Multi-Tenant Data Centers18
1.5 Sustainable Multi-Tenant Data Centers18
1.6 Multi-Tenant Data Center Demand Response19
1.6.1 What is Data Center Demand Response?19
1.6.2 Why Multi-Tenant Data Center Demand Response?20
2 Preliminaries21
2.1 Multi-Tenant Data Center21
2.2 Electrical Systems22
2.2.1 Power Usage Effectiveness23
2.2.2 Electricity Supply23
2.2.3 Electricity Demand24
2.2.4 Electricity Bill24
2.3 Carbon Footprint25
2.4 Inconvenience to Tenants27
2.4.1 Delay Performance Cost27
2.4.2 Other Costs27
Part II Sustainable Multi-Tenant Data Center29
3 Background30
3.1 Motivation30
3.2 Issues31
3.3 Challenges31
3.4 Uncertainty32
3.5 On-line Coordination32
4 System Model33
4.1 Problem Formulation33
4.1.1 Minimizing the Operating Cost33
4.1.2 Minimizing the Energy Consumption34
5 Solutions36
5.1 Reducing Cost via Rewards37
5.1.1 Feedback-Based On-Line Optimization38
5.1.2 Simulation and Results39
5.1.2.1 Simulation Settings39
5.1.2.2 Tenants' Response39
5.1.2.3 Simulation Results40
5.1.3 Experiment44
5.1.3.1 Colocation Testbed44
5.1.3.2 Tenants' Response45
5.1.3.3 Experimental Results47
5.2 Minimizing Carbon Footprint in Colocation Data Center (GreenColo)48
5.2.1 Simulation and Results50
5.2.1.1 Simulation Settings50
5.2.1.2 Execution of GreenColo52
5.2.1.3 Tenant Costs52
5.2.1.4 Carbon Footprint Reduction54
5.3 Randomization for Pricing and Auction55
5.3.1 Randomized Pricing Approach55
5.3.1.1 An Off-Line Approximation Algorithm55
5.3.1.2 An On-Line Algorithm56
5.3.2 Randomized Auction Approach57
5.3.2.1 An On-Line Algorithm57
5.3.2.2 A More Intelligent On-Line Algorithm59
5.3.3 Randomized Truthful Auction Mechanism59
5.3.4 Simulation and Results63
5.3.4.1 Simulation Setup63
5.3.4.2 Algorithms for Pricing Approach64
5.3.4.3 Algorithms for Auction Approach67
6 Summary71
Part III Multi-Tenant Data Center Demand Response72
7 Background73
7.1 Motivation73
7.2 Issues74
7.3 Challenges75
8 System Model77
8.1 Problem Formulations77
8.1.1 Maximizing the Total Energy Demand Reduction77
8.1.2 Minimizing the Social Cost of a Multi-Tenant Data Center78
8.1.2.1 Mixed Integer Programming Problem Chen2015PER, Zhang2015INFOCOM78
8.1.2.2 Linear Programming Problem Guo201578
8.1.3 Maximizing the Social Welfare79
8.1.4 Maximizing the Social Cost Savings80
8.1.5 Thermal-Aware Minimization via Backup Energy Storage81
8.1.5.1 Temperature and Heat Recirculation Model81
8.1.5.2 Auction Model82
8.1.6 Contract Design Formulation83
8.1.7 Stackelberg Game Formulation84
8.1.8 Minimizing Social Cost for Geo-Distributed Multi-Tenant Data Centers85
9 Solutions87
9.1 Incentivizing Colocation Tenants for Demand Response (iCODE)87
9.1.1 Simulations and Results89
9.1.1.1 Simulation Setup89
9.1.1.2 Comparison Between iCODE and NDR90
9.1.1.3 Impact of Workload Over-Prediction91
9.1.1.4 Impact of Greediness92
9.2 Truthful Incentive Mechanism (Truth-DR)93
9.2.1 2-Approximation Algorithm94
9.2.2 The Randomized Auction96
(1) Optimal Fractional Solution97
(2) Convex Decomposition97
(3) Winner Determination and Payment98
9.2.3 Simulations and Results99
9.2.3.1 Simulation Setup99
9.2.3.2 Close-to-Minimum Social Cost100
9.2.3.3 Satisfying Energy Reduction Target101
9.2.3.4 Tenants' Non-Negative Utilities101
9.2.3.5 Social Cost Reduction Compared to ``Backup Energy Storage Only''102
9.3 Greening Multi-Tenant Data Center Demand Response (ColoEDR)103
9.3.1 Price-Taking Tenants105
9.3.2 Price-Anticipating T