SIG on Green Computing and Data Processing

Scope and Objectives

Cloud Computing offers users a flexible access to computing and data resources from Data Centers. The increasing popularity of Cloud Computing has created demands for deployment of large scale Data Centers for various purposes such as economy, manageability, and operational efficiency. As these large scale Data Centers will require more energy to operate, energy efficiency of Data Centers becomes a critical issue so that Data Centers can continue to scale up in order to meet the increasing demands of Cloud Computing services.

The SIG will focus on issues related to energy efficiency in Data Center Networking and Cloud Computing. Data Centers are energy-intensive facilities. In the aspect of IT equipment in Data Centers, the main contributors of energy consumption are servers, storage and networking. Minimizing energy consumption yet delivering requested quality of Cloud Computing services can be achieved by optimizing usages of servers, storage and networking. Several techniques can be considered to optimize server usages. Techniques such as server provisioning and virtualization with application awareness are some examples that can lead to lower wastages in server resource utilization and higher sharing of common infrastructure.

Besides, storage devices are another main contributor of energy consumption. Storage devices also generate significant amount of heat which requires further energy for cooling. Storage virtualization and optimal data placement in heterogeneous storage devices will be some potential solutions to improve storage access performance and increase storage utilization.

Finally, in the aspect of networking, reducing over-connectivity and increasing network utilization will be key focuses. The recent trend in I/O consolidation using solutions such as FCoE achieves reduced redundancy in storage area networks which results in a simple and efficient storage area network infrastructure. Moreover, it is also demonstrated that software defined networking approach enables energy optimization of networking in Data Centers. More efforts should be devoted in this area to further reduce the energy in Data Center Networking.

In summary, this SIG will focus on energy efficiency in Data Centers and Cloud Computing. The main sub-areas of interest include, but not limited to,

• Server energy efficiency
• Storage energy efficiency
• Networking energy efficiency
• Joint optimization among ICT, power distribution and cooling
• Data center virtualization
• Cloud computing
• Energy-efficient application optimization for green cloud computing
• Energy-efficient software architecture for green cloud computing
• Power Analytics for green data center and cloud computing

1. Beylot Andre-Luc, ENSEEIHT, France
2. Monique Becker, TELECOM SudParis, France
3. Jianlong Cao, Hong Kong PolyTechnical University, Hong Kong
4. Ana Rosa Cavalli, TELECOM & Management SudParis, France
5. Periklis Chatzimisios, Alexander Technological Educational Institution of Thessaloniki, Greece
6. Jiann-Liang Chen, National Taiwan University of Science and Technology
7. Min Chen, HUST, China
8. Dah-Ming Chiu, Chinese University of Hong Kong, Hong Kong
9. Riadh Dhaou, INPT, France
10. Hiroshi Esaki, The University of Tokyo, Japan
11. Xing Fang, Huawei Technologies, China
12. Chuan Heng Foh, Nanyang Technological University, Singapore
13. Xiaoming Fu, Georg-August-University of Goettingen, Germany
14. Kyle Guan, Bell Laboratories, USA
15. Burak Kantarci, University of Ottawa, Canada
16. Khin Mi Mi, Data Storage Institute, Singapore
17. Dan Kilper, Bell Laboratories, USA
18. Chin-Feng Lai, Ilan University, Taiwan
19. Wenjun Liao, National Taiwan University, Taiwan
20. Francis Lee, Nanyang Technological University, Singapore
21. Ronnie Lee, Infocomm Development Authority, Singapore
22. Tony Lee, Shanghai Jiaotong University, China
23. Maozhen (Rick) Li, Brunel University, UK
24. Keok Tong Ling, Infocomm Development Authority, Singapore
25. Bin Liu, Tsinghua University, China
26. Adam Wierman, CalTech, USA
27. Michel Marot, TELECOM SudParis, France
28. Jaime Lloret Mauri, Polytechnic University of Valencia, Spain
29. Geyong Min, University of Bradford, UK
30. Rong Pan, Cisco, USA
31. Cathryn Peoples, University of Ulster, UK
32. Chris Phillips, University of London, UK
33. Balaji Prabhakar, Stanford University, USA
34. Chunming Qiao, University at Buffalo, the State University of New York, USA
35. Kok Chuan Toh, Nanyang Technological University, Singapore
36. Zhili Sun, University of Surrey, UK
37. Hai Le Vu, Swinburne University of Technology, Australia
38. Xinbing Wang, Shanghai Jiaotong University, China
39. Yonggang Wen, Nanyang Technological University, Singapore
40. Di Wu, Sun-Yat-Shen University, China
41. Jinsong Wu, Bell Laboratories, China
42. Kun Yang, University of Essex, UK
43. Yang Yang, Shanghai Research Center for Wireless Communications, China
44. Jiang Zhu, Cisco, USA
45. Jinzy Zhu, Huawei Technologies, China
46. Xiaoqing Zhu, Cisco, USA
47. Moshe Zukerman, City University of Hong Kong, Hong Kong
48. Zuqing Zhu, University of Science and Technology of China, China
49. Chau Yuen, Singapore University of Technology and Design, Singapore
50. Joel Rodrigues, University of Beira Interior, Portugal
51. RangaRao Venkatesha Prasad, Delft University of Technology, Netherlands