專家信息：

曹軍威，男，博士，現(xiàn)任清華大學信息技術(shù)研究院研究員、院長助理。

教育及工作經(jīng)歷：

2009年至今清華大學天體物理中心兼任教授。

2007年至今清華大學信息技術(shù)研究院助理院長。

2007年至今天體物理和空間研究Kavli研究所LIGO的實驗室研究聯(lián)盟。

2006年至今清華大學信息技術(shù)研究院教授。

2004年至2006年麻省理工學院空間研究中心LIGO的實驗室研究科學家。

2002年至2004年德國C＆C的研究實驗室研究員。

2001年至2002年華威大學計算機科學系研究員。

2001年英國Warwick大學計算機博士畢業(yè)。

1991年至1998年清華大學自動化系本科、碩士畢業(yè)。

社會兼職：

資料更新中……

科學研究：

研究方向：

主要從事先進計算技術(shù)及其應用研究。

承擔科研項目情況：

負責或參加完成10多項國家科技863計劃、教育部、自然科學基金、973和橫向研究項目。

1、教育部：Elop在計算技術(shù)和應，2009-2011。

2、中國國家自然科學獎基金：對網(wǎng)絡(luò)基礎(chǔ)設(shè)施的理論和資源優(yōu)化與動態(tài)約束算法，2009-2011。

3、中國教育部的科研基金：引力波數(shù)據(jù)分析使用開放科學網(wǎng)，2008-2009。

4、國家863高技術(shù)研發(fā)計劃：大型網(wǎng)絡(luò)化數(shù)據(jù)整合與查詢處理，2008-2009。

5、國家863高技術(shù)研發(fā)計劃：組織，管理和農(nóng)業(yè)海量知識資源服務(wù)，2007-2009。

6、教育部：全國綜合系統(tǒng)開放課程，2007-2010。

7、國家863高技術(shù)研發(fā)計劃：數(shù)字農(nóng)業(yè)知識網(wǎng)格，2006-2010。

8、清華大學研究院：網(wǎng)絡(luò)基礎(chǔ)設(shè)施的應用啟用，2008-2010。

9、中國自然科學基金委員會：以往項目中國美研討會網(wǎng)絡(luò)基礎(chǔ)設(shè)施，2009。

10、清華大學骨干人才計劃：網(wǎng)絡(luò)基礎(chǔ)設(shè)施技術(shù)，2007-2008。

11、信息科學與技術(shù)學院清華大學：網(wǎng)絡(luò)基礎(chǔ)設(shè)施技術(shù)，2006 -2008。

12、LIGO的部署數(shù)據(jù)網(wǎng)格，網(wǎng)格，使社區(qū)引力波分析，2004-2006。

13、奧運- FLEMM：基于OGSA的FlexX /分子力學，2003-2004。

14、歐盟信息社會技術(shù)（IST）項目:GEMSS：網(wǎng)格仿真功能的醫(yī)療服務(wù)，2002 -2004。

15、NEC支持的項目：相關(guān)譜的集群和網(wǎng)格作業(yè)調(diào)度，2002-2004。

16、貿(mào)易和工業(yè)�。∕ETI）日本網(wǎng)絡(luò)計算項目部：優(yōu)化利用網(wǎng)格Datafarm對接構(gòu)象，2002-2003。

17、美國航天局艾姆斯研究中心：面向計算網(wǎng)格系統(tǒng)管理工具發(fā)展，2001-2002。

18、華威研究生院主席特別研究獎學金:基于Agent的網(wǎng)格計算資源管理，1999-2001。

19、方法和性能建模，測量，分析，評價和預測工具，1999-1999。

20、國家863高技術(shù)重點研究項：一個計算機集成制造中的應用平臺，1996-1998。

21、BMCST - MIS系統(tǒng)：為北京管理科學和技術(shù)委員會管理信息系統(tǒng)，1995-1996。

科研成果：

資料更新中……

發(fā)明專利：

1、提高分布式系統(tǒng)性能調(diào)優(yōu)速度的方法 曹軍威; 張帆 清華大學 【中國專利】清華大學 2009-12-23

論文專著：

發(fā)表論文110余篇，出版專著10余部。

出版專著：

1《多代理系統(tǒng)理論、方法與應用》范玉順，曹軍威 北京 [海德堡]；清華大學出版社；施普林格出版，2002年。

2《復雜系統(tǒng)的面向?qū)ο蠼�模、分析與設(shè)計》范玉順，曹軍威清華大學出版社，2000年9。

3《網(wǎng)絡(luò)基礎(chǔ)設(shè)施技術(shù)及應用》Nova科學出版社，2009年。

4《網(wǎng)絡(luò)基礎(chǔ)設(shè)施與應用技術(shù)》新科學出版社，2009年。

5《網(wǎng)格數(shù)據(jù)流》Nova科學出版社，2008年。

6《對于大規(guī)模分布式環(huán)境中的性能預測技術(shù)研究》Nova科學出版社，2007年。

7《績效評估的自組織網(wǎng)格計算代理》Nova科學出版社，2007年。

8《引力波數(shù)據(jù)分析：對工作流程的科學分析技術(shù)的使用為例》施普林格出版社，2007年。

發(fā)表論文：

英文：

1. VOMES: a Virtual Organization Membership Evaluation System. J. Cao and Z. Wang. (submitted)

2. Use of Agent-based Service Discovery for Resource Management in Metacomputing Environment. J. Cao, D. J. Kerbyson and G. R. Nudd. Proc. 7th Int. Euro-Par Conf., Manchester, UK, LNCS 2150, 882-886, 2001. (research note)

3. Upper Limits on Gravitational Wave Emission from 78 Radio Pulsars. LIGO Scientific Collaboration, M. Kramer, and A. G. Lyne. Physical Review D, 76(4), 042001(20), 2007.

4. Upper Limits from LIGO and TAMA Detectors on the Rate of Gravitational Wave Bursts. LIGO Scientific Collaboration and TAMA Collaboration. Physical Review D, 72(12), 122004(16), 2005.

5. Upper Limit Map of a Background of Gravitational Waves. LIGO Scientific Collaboration. Physical Review D, 76(8), 082003(11), 2007.

6. The Open Science Grid. R. Pordes for the Open Science Grid Consortium. Proc. Computing in High Energy and Nuclear Physics Conf., Interlaken, Switzerland, 2004.

7. The Einstein@Home Search for Periodic Gravitational Waves in LIGO S4 Data. LIGO Scientific Collaboration. Physical Review D, 79(2), 022001(29), 2009.

8. Technology Challenges of Cyberinfrastructure (in Chinese). J. Cao. Int. Academic Development, 5(2), 32-36, 2010.

9. System Architecture of New CIMS Application Integration Platform (in Chinese). J. Cao, Y. Fan and C. Wu. J. Tsinghua University, 39(7), 68-71, 1999. (also in Proc. 5th China CIMS Conference, Chengdu, PRC, 1998)

10. Storage Aware Resource Allocation for Grid Data Streaming Pipelines. W. Zhang, J. Cao, Y. Zhong, L. Liu, and C. Wu. Proc. 2008 IEEE Int. Conf. on Networking, Architecture, and Storage, Chongqing, China, 179-180, 2008. (short paper)

11. Status of LCGT. LCGT Collaboration. Classical and Quantum Gravity, 27(8), 084004(8), 2010.

12. Stacked Search for Gravitational Waves from the 2006 SGR 1900+14 Storm. LIGO Scientific Collaboration. The Astrophysical J. Letters, 701(2), L68-L74, 2009.

13. Self-Organizing Agents for Grid Load Balancing. J. Cao. Proc. 5th IEEE/ACM Int. Workshop on Grid Computing, conj. Supercomputing Conf., Pittsburgh, PA, USA, 388-395, 2004. (also as Technical Report LR-04-205, NEC Corporation, 2004)

14. Searching for a Stochastic Background of Gravitational Waves with LIGO. LIGO Scientific Collaboration. The Astrophysical J., 659(2), 918-930, 2007.

15. Searches for Periodic Gravitational Waves from Unknown Isolated Sources and Scorpius X-1: Results from the Second LIGO Science Run. LIGO Scientific Collaboration. Physical Review D, 76(8), 082001(35), 2007.

16. Searches for Gravitational Waves from Known Pulsars with S5 LIGO Data. LIGO Scientific Collaboration and Virgo Collaboration. The Astrophysical J., 713(1), 671-685, 2010.

17. Search of S3 LIGO Data for Gravitational Wave Signals from Spinning Black Hole and Neutron Star Binary Inspirals. LIGO Scientific Collaboration. Physical Review D, 78(4), 042002(19), 2008.

18. Search for High Frequency Gravitational Wave Bursts in the First Calendar Year of LIGO's Fifth Science Run. LIGO Scientific Collaboration. Physical Review D, 80(10), 102002(14), 2009.

19. Search for Gravitational-wave Inspiral Signals Associated with Short Gamma-Ray Bursts during LIGO's Fifth and Virgo's First Science Run. LIGO Scientific Collaboration and Virgo Collaboration. The Astrophysical J., 715(2), 1453-1461, 2010.

20. Search for Gravitational-wave Bursts in the First Year of the Fifth LIGO Science Run. LIGO Scientific Collaboration. Physical Review D, 80(10), 102001(26), 2009.

21. Search for Gravitational-wave Bursts in LIGO Data from the Fourth LSC Science Run. LIGO Scientific Collaboration. Classical and Quantum Gravity, 24(22), 5343-5369, 2007.

22. Search for Gravitational-wave Bursts Associated with Gamma-ray Bursts using Data from LIGO Science Run 5 and Virgo Science Run 1. LIGO Scientific Collaboration and Virgo Collaboration. The Astrophysical J., 715(2), 1438-1452, 2010.

23. Search for Gravitational Waves from Low Mass Compact Binary Coalescence in 186 Days of LIGO's Fifth Science Run. LIGO Scientific Collaboration. Physical Review D, 80(4), 047101(8), 2009.

24. Search for Gravitational Waves from Low Mass Binary Coalescences in the First Year of LIGO's S5 Data. LIGO Scientific Collaboration. Physical Review D, 79(12), 122001(14), 2009.

25. Search for Gravitational Waves from Compact Binary Coalescence in LIGO and Virgo Data from S5 and VSR1. LIGO Scientific Collaboration and Virgo Collaboration. Physical Review D, 82(10), 102001(11), 2010.

26. Search for Gravitational Waves from Binary Inspirals in S3 and S4 LIGO Data. LIGO Scientific Collaboration. Physical Review D, 77(6), 062002(13), 2008.

27. Search for Gravitational Waves from Binary Black Hole Inspirals in LIGO Data. LIGO Scientific Collaboration. Physical Review D, 73(6), 062001(17), 2006.

28. Search for Gravitational Waves Associated with 39 Gamma-Ray Bursts Using Data from the Second, Third, and Fourth LIGO Runs. LIGO Scientific Collaboration. Physical Review D, 77(6), 062004(22), 2008.

29. Search for Gravitational Wave Ringdowns from Perturbed Black Holes in LIGO S4 Data. LIGO Scientific Collaboration. Physical Review D, 80(6), 062001(9), 2009.

30. Search for Gravitational Wave Radiation Associated with the Pulsating Tail of the SGR 1806-20 Hyperflare of 27 December 2004 using LIGO. LIGO Scientific Collaboration. Physical Review D, 76(6), 062003(12), 2007.

31. Search for Gravitational Wave Bursts in LIGO's Third Science Run. LIGO Scientific Collaboration. Classical and Quantum Gravity, 23(8), S29-S39, 2006.

32. Search for Gravitational Wave Bursts from Soft Gamma Repeaters. LIGO Scientific Collaboration, S. Barthelmy, N. Gehrels, K. C. Hurley, and D. Palmer. Physical Review Letters, 101(21), 211102(6), 2008.

33. Search for Gravitational Wave Bursts from Six Magnetars. LIGO Scientific Collaboration and Virgo Collaboration. (submitted)

34. Scheduling Remote Access to Scientific Instruments in Cyberinfrastructure for Education and Research. J. Yin, J. Cao, Y. Wang, L. Liu, and C. Wu. Proc. 7th IEEE/ACM Int. Symp. on Cluster Computing and the Grid, Rio de Janeiro, Brazil, 426-433, 2007.

35. Scheduling Data Blocks for Concurrent and Storage-aware Grid Data Streaming. W. Zhang, J. Cao, Y. Zhong, L. Liu, and C. Wu. Int. J. Grid and Utility Computing, 2011.

36. Research of Operation Administration System Agents of Integration Platform (in Chinese). J. Cao, Y. Fan and C. Wu. CIMS, 5(3), 39-43, 1999.

37. Remote Computing Resource Management from Small Devices by Utilising WSRF. S. Huang, M. VanHilst, J. Cao, and J. Mangs. Int. J. Computer Aided Engineering and Technology, Special Issue on Smart Homes: Technologies and Applications, 2(2-3), 199-217, 2010.

38. Redundant Virtual Machines Management in Virtualized Cloud Platform. F. Zhang, J. Cao, C. Hong, L. Liu and C. Wu. Int. J. Modeling, Simulation, and Scientific Computing, 2011.

39. Real-time Gravitational-wave Burst Search for Multi-messenger Astronomy. J. Cao and J. Li. Int. J. Modern Physics D, 2011.

40. Queue Scheduling and Advance Reservations with COSY. J. Cao and F. Zimmermann. Proc. 18th IEEE Int. Parallel & Distributed Processing Symp., Santa Fe, NM, USA, 63, 2004. (also as Technical Report LR-03-189, NEC Corporation, 2003)

41. Qualification Evaluation in Virtual Organizations Based on Fuzzy Analytic Hierarchy Process. F. Zhang, J. Cao, L. Liu, and C. Wu. Proc. 7th Int. Conf. on Grid and Cooperative Computing, Shenzhen, China, 539-547, 2008.

42. Predictions for the Rates of Compact Binary Coalescences Observable by Ground-based Gravitational-wave Detectors. LIGO Scientific Collaboration, Virgo Collaboration, and K Belczynski. Classical and Quantum Gravity, 27(17), 173001(25), 2010.

43. Performance-based Workload Management for Grid Computing. D. P. Spooner, S. A. Jarvis, J. Cao, G. R. Nudd, S. Saini and D. J. Kerbyson. Proc. 3rd Annual Symp. of Los Alamos Computer Science Institute, Santa Fe, NM, USA, 2002.

44. Performance-aware Workflow Management for Grid Computing. D. P. Spooner, J. Cao, S. A. Jarvis, L. He, and G. R. Nudd. The Computer J., Special Focus - Grid Performability, 48(3), 347-357, 2005.

45. Performance Prediction Technology for Agent-based Resource Management in Grid Environments. J. Cao, S. A. Jarvis, D. P. Spooner, J. D. Turner, D. J. Kerbyson and G. R. Nudd. Proc. 11th IEEE Heterogeneous Computing Workshop, conj. 16th IEEE Int. Parallel & Distributed Processing Symp., Fort Lauderdale, FL, USA, 86, 2002.

46. Performance Prediction and its use in Parallel and Distributed Computing Systems. S. A. Jarvis, D. P. Spooner, H. N. Lin Choi Keung, J. Cao, S. Saini, and G. R. Nudd. Future Generation Computer Systems, Special Section on System Performance Analysis and Evaluation, 22(7), 745-754, 2006.

47. Performance Prediction and its use in Parallel and Distributed Computing Systems. S. A. Jarvis, D. P. Spooner, H. N. Lin Choi Keung, J. Cao, S. Saini, and G. R. Nudd. Proc. 2nd Int. Workshop on Performance Modeling, Evaluation, and Optimization of Parallel and Distributed Systems, conj. 17th IEEE Int. Parallel & Distributed Processing Symp., Nice, France, 276, 2003.

48. Performance Prediction and Evaluation. S. Jarvis, M. Coppola, J. Cao, and D. Kerbyson. Proc. 16th Int. Euro-Par Conf. on Parallel Processing, LNCS 6271 PART 1, 86-87, 2010.

49. Performance Optimization of Temporal Reasoning for Grid Workflows Using Relaxed Region Analysis. K. Xu, J. Cao, L. Liu, and C. Wu. Proc. 22nd IEEE Int. Conf. on Advanced Information Networking and Applications Workshops, GinoWan, Okinawa, Japan, 187-194, 2008.

50. Performance Modeling of Parallel and Distributed Computing Using PACE. J. Cao, D. J. Kerbyson, E. Papaefstathiou and G. R. Nudd. Proc. 19th IEEE Int. Performance, Computing and Communications Conf., Phoenix, AZ, USA, 485-492, 2000.

51. Performance Evaluation of an Agent-Based Resource Management Infrastructure for Grid Computing. J. Cao, D. J. Kerbyson and G. R. Nudd. Proc. 1st IEEE/ACM Int. Symp. on Cluster Computing and the Grid, Brisbane, Australia, 311-318, 2001.

52. Ordinal Optimized Scheduling of Scientific Workflows in Elastic Compute Clouds. F. Zhang, J. Cao, K. Hwang, and C. Wu. (submitted)

53. Observation of a Kilogram-scale Oscillator near its Quantum Ground State. LIGO Scientific Collaboration. New Journal of Physics, 11(7), 073032(13), 2009.

54. Modelling of ASCI High Performance Applications Using PACE. J. Cao, D. J. Kerbyson, E. Papaefstathiou and G. R. Nudd. Proc. 15th Annual UK Performance Engineering Workshop, Bristol, UK, 413-424, 1999.

55. Localised Workload Management using Performance Prediction and QoS Contracts. D. P. Spooner, J. Cao, J. D. Turner, H. N. Lin Choi Keung, S. A. Jarvis and G. R. Nudd. Proc. 18th Annual UK Performance Engineering Workshop, Glasgow, UK, 69-80, 2002.

56. Local Grid Scheduling Techniques Using Performance Prediction. D. P. Spooner, S. A. Jarvis, J. Cao, S. Saini and G. R. Nudd. IEE Proceedings - Computers and Digital Techniques, 150(2), 87-96, 2003.

57. LIGO: The Laser Interferometer Gravitational-Wave Observatory. LIGO Scientific Collaboration. Reports on Progress in Physics, 72(7), 076901(25), 2009.

58. Joint LIGO and TAMA300 Search for Gravitational Waves from Inspiralling Neutron Stars. LIGO Scientific Collaboration and TAMA Collaboration. Physical Review D, 73(10), 102002(10), 2006.

59. Implications for the Origin of GRB 070201 from LIGO Observations. LIGO Scientific Collaboration and K. C. Hurley. The Astrophysical J., 681(2), 1419-1430, 2008.

60. Implementation of Grid-enabled Medical Simulation Applications Using Workflow Techniques. J. Cao, J. Fingberg, G. Berti, and J. G. Schmidt. Proc. 2nd Int. Workshop on Grid and Cooperative Computing, Shanghai, China, LNCS 3032, 34-41, 2003. (also as Technical Report LR-03-185, NEC Corporation, 2003)

61. How Are You Feeling? A Social Network Model to Monitor the Health of Post-Operative and Remote Patients. J. J. Mulcahy, S. Huang, J. Cao, and F. Zhang. Proc. IEEE Int. Systems Conf., Montreal, Canada, 2011.

62. High Performance Service Discovery in Large-Scale Multi-Agent and Mobile-Agent Systems. J. Cao, D. J. Kerbyson and G. R. Nudd. Int. J. Software Engineering and Knowledge Engineering, Special Issue on Multi-Agent Systems and Mobile Agents, 11(5), 621-641, 2001.

63. GridFlow: Workflow Management for Grid Computing. J. Cao, S. A. Jarvis, S. Saini and G. R. Nudd. Proc. 3rd IEEE/ACM Int. Symp. on Cluster Computing and the Grid, Tokyo, Japan, 198-205, 2003.

64. Grid Resource Management and Scheduling for Data Streaming Applications. W. Zhang, J. Cao, Y. Zhong, L. Liu, and C. Wu. Computing and Informatics, 29, 1001-1028, 2010.

65. Grid Load Balancing Using Intelligent Agents. J. Cao, D. P. Spooner, S. A. Jarvis, and G. R. Nudd. Future Generation Computer Systems, Special Issue on Intelligent Grid Environment: Principles and Applications, 21(1), 135-149, 2005.

66. Grid Information Services Using Software Agents. H. N. Lin Choi Keung, J. Cao, D. P. Spooner, S. A. Jarvis and G. R. Nudd. Proc. 18th Annual UK Performance Engineering Workshop, Glasgow, UK, 187-198, 2002.

67. Grid Enabled LIGO Data Monitoring. J. Cao, E. Katsavounidis, and J. Zweizig. Proc. IEEE/ACM Supercomputing Conf., Seattle, WA, USA, 2005. (poster, also as LIGO Document No. G050573-00-E, 2005)

68. Fuzzy Allocation of Fine-grained Compute Resources for Grid Data Streaming Applications. W. Zhang, J. Cao, Y. Zhong, L. Liu, and C. Wu. Int. J. Grid and High Performance Computing, 2(4), 1-11, 2010.

69. Flexible Software Systems (in Chinese). J. Cao and Y. Fan. Computer Science, 26(2), 74-77, 1999.

70. First Search for Gravitational Waves from the Youngest Known Neutron Star. LIGO Scientific Collaboration. The Astrophysical J., 722(2), 1504-1513, 2010.

71. First LIGO Search for Gravitational Wave Bursts from Cosmic (Super)strings. LIGO Scientific Collaboration. Physical Review D, 80(6), 062002(11), 2009

72. First Joint Search for Gravitational-wave Bursts in LIGO and GEO600 Data. LIGO Scientific Collaboration. Classical and Quantum Gravity, 25(24), 245008(21), 2008.

73. First Cross-Correlation Analysis of Interferometric and Resonant-Bar Gravitational-Wave Data for Stochastic Backgrounds. LIGO Scientific Collaboration and ALLEGRO Collaboration. Physical Review D, 76(2), 022001(17), 2007.

74. Fast Autotuning Configurations of Parameters in Distributed Computing Systems Using Ordinal Optimization. F. Zhang, J. Cao, L. Liu, and C. Wu. Proc. 38th Int. Conf. on Parallel Processing Workshops, Vienna, Austria, 190-197, 2009.

75. Evaluation of Advertising Effectiveness Using Agent-Based Modeling and Simulation. J. Cao. Proc. 2nd UK Workshop of SIG on Multi-Agent Systems, Bristol, UK, 1999.

76. Enhanced Adaptive Scheduling for the Grid Harvest Service. W. Sliamu, Y. Hou, and J. Cao. Proc. WRI World Congress on Software Engineering, Vol. 1, Xiamen, China, 35-39, 2009.

77. Enabling Access to WSRF from Mobile Devices. J. C. Mangs, S. Huang, and J. Cao. Proc. 4th Int. Conf. on Semantics, Knowledge and Grid, Beijing, China, 392-395, 2008.

78. Einstein@Home Search for Periodic Gravitational Waves in Early S5 LIGO Data. LIGO Scientific Collaboration and D. P. Anderson. Physical Review D, 80(4), 042003(14), 2009.

79. Dynamic Controlling of Data Streaming Applications for Cloud Computing. J. Cao and W. Zhang. (submitted)

80. Dynamic Application Integration Using Agent-Based Operational Administration. J. Cao, D. J. Kerbyson and G. R. Nudd. Proc. 5th Int. Conf. on the Practical Application of Intelligent Agents and Multi-Agent Technology, Manchester, UK, 393-396, 2000.

81. Development of a DMT Monitor for Statistical Tracking of Gravitational-wave Burst Triggers Generated from the Omega Pipeline. J. Li and J. Cao. Proc. 9th Asia-Pacific Int. Conf. on Gravitation and Astrophysics, Wuhan, China, 92-101, 2010.

82. Cost Estimation of Advance Reservations over Queued Jobs: a Quantitative Study. C. Zhao, J. Cao, H. Wu, and F. Zhang. Int. J. Modeling, Simulation, and Scientific Computing, 1(3), 317-332, 2010.

83. Concurrent and Storage-Aware Data Streaming for Data Processing Workflows in Grid Environments. W. Zhang, J. Cao, Y. Zhong, L. Liu, and C. Wu. Tsinghua Science and Technology, 15(3), 335-346, 2010.

84. Committee-based Evaluation and Selection of Grid Resources for QoS Improvement. Z. Wang and J. Cao. Proc. 10th IEEE/ACM Int. Conf. on Grid Computing, Banff, Alberta, Canada, 138-144, 2009.

85. Cloud Manufacturing: a New Service-oriented Networked Manufacturing Model (in Chinese). B. Li, L. Zhang, S. Wang, F. Tao, J. Cao, X. Jiang, X. Song, and X. Chai. CIMS, 16(1), 1-8, 2010.

86. Calibration of the LIGO Gravitational Wave Detectors in the Fifth Science Run. LIGO Scientific Collaboration. Nuclear Instruments and Methods in Physics Research A, 624(1), 223-240, 2010.

87. Block-based Concurrent and Storage-aware Data Streaming for Grid Applications with Lots of Small Files. W. Zhang, J. Cao, Y. Zhong, L. Liu, and C. Wu. Proc. 1st Int. Workshop on Service-Oriented P2P Networks and Grid Systems, conj. 9th IEEE Int. Symp. on Cluster Computing and the Grid, Shanghai, China, 538-543, 2009.

88. Beating the Spin-down Limit on Gravitational Wave Emission from the Crab Pulsar. LIGO Scientific Collaboration. The Astrophysical J. Letters, 683(1), L45-L49, 2008.

89. Astrophysically Triggered Searches for Gravitational Waves: Status and Prospects. LIGO Scientific Collaboration and Virgo Collaboration. Classical and Quantum Gravity, 25(11), 114051(12), 2008.

90. ASTROD Optimized for Gravitational Wave Detection: ASTROD-GW. ASTROD Collaboration. Proc. 38th COSPAR Scientific Assembly, Bremen, Germany, 2010.

91. ASTROD Optimized for Gravitational Wave Detection: ASTROD-GW (in Chinese). ASTROD Collaboration. Proc. 6th Deep-Space Exploration Annual Meeting, Sanya, China, 2009.

92. ARMSim: a Modeling and Simulation Environment for Agent-based Grid Computing. J. Cao. SIMULATION, Special Issue on Modeling and Simulation Applications in Cluster and Grid Computing, 80(4-5), 221-229, 2004.

93. ARMS: an Agent-based Resource Management System for Grid Computing. J. Cao, S. A. Jarvis, S. Saini, D. J. Kerbyson and G. R. Nudd. Scientific Programming, Special Issue on Grid Computing, 10(2), 135-148, 2002.

94. Application of Support Vector Machines to Multivariate Gravitational-wave Veto Analysis. W. Zhen, J. Cao, L. Blackburn, E. Katsavounidis, and X. Wang. Classical and Quantum Gravity, 2011.

95. Application Characterisation Using a Lightweight Transaction Model. D. P. Spooner, J. D. Turner, J. Cao, S. A. Jarvis and G. R. Nudd. Proc. 17th Annual UK Performance Engineering Workshop, Leeds, UK, 215-225, 2001.

96. An Upper Limit on the Stochastic Gravitational-Wave Background of Cosmological Origin. LIGO Scientific Collaboration and Virgo Collaboration. Nature, 460(7258), 990-994, 2009.

97. An Integrated Resource Management and Scheduling System for Grid Data Streaming Applications. W. Zhang, J. Cao, Y. Zhong, L. Liu, and C. Wu. Proc. 9th IEEE/ACM Int. Conf. on Grid Computing, Tsukuba, Japan, 258-265, 2008.

98. AMREF: An Adaptive MapReduce Framework for Real Time Applications. F. Zhang, J. Cao, X. Song, H. Cai, and C. Wu. Proc. 9th Int. Conf. on Grid and Cloud Computing, Nanjing, China, 157-162, 2010.

99. All-sky Search for Periodic Gravitational Waves in LIGO S4 Data. LIGO Scientific Collaboration. Physical Review D, 77(2), 022001(38), 2008.

100. All-sky Search for Gravitational-wave Bursts in the First Joint LIGO-GEO-Virgo Run. LIGO Scientific Collaboration and Virgo Collaboration. Physical Review D, 81(10), 102001(20), 2010.

101. All-sky LIGO Search for Periodic Gravitational Waves in the Early S5 Data. LIGO Scientific Collaboration. Physical Review Letters, 102(11), 111102(6), 2009.

102. AIGO: a Southern Hemisphere Detector for the Worldwide Array of Ground Based Interferometric Gravitational Wave Detectors. AIGO Collaboration. Classical and Quantum Gravity, 27(8), 084005(12), 2010.

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中文：

1 云制造——面向服務(wù)的網(wǎng)絡(luò)化制造新模式 李伯虎; 張霖; 王時龍; 陶飛; 曹軍威; 姜曉丹; 宋曉; 柴旭東 北京航空航天大學復雜產(chǎn)品先進制造系統(tǒng)教育部工程研究中心; 北京仿真中心; 重慶大學機械工程學院; 清華大學信息技術(shù)研究院; 北京慧點科技開發(fā)有限公司 【期刊】計算機集成制造系統(tǒng) 2010-01-15

2 集成平臺運控系統(tǒng)代理模型研究 曹軍威; 范玉順; 吳澄 清華大學自動化系 【期刊】計算機集成制造系統(tǒng)-CIMS 1999-06-30

3 新一代 CIMS應用集成平臺系統(tǒng)體系結(jié)構(gòu) 曹軍威; 范玉順; 吳澄 清華大學自動化系 【期刊】清華大學學報(自然科學版) 1999-07-10

4 柔性軟件系統(tǒng)的概念、方法與實踐 曹軍威; 范玉順 清華大學CIMS工程研究中心; 清華大學CIMS工程研究中心 北京 【期刊】計算機科學 1999-02-15

5 ASTROD空間引力波探測優(yōu)化方案:ASTROD-GW 倪維斗; 門金瑞; 梅曉紅; 雷成明; 董瑤; A.Pulido Paton; 董鵬; 王剛; 黃超光; 龔雪飛; 張楊; 王海濤; 彭秋和; 曹軍威; 王立; 侯欣賓; 張慶祥; 張曉敏; Hansj�謗g Dittus; Jian Guo; Claus Lammerzahl; Diana Shaul; Timothy Sumner 【會議】中國宇航學會深空探測技術(shù)專業(yè)委員會第六屆學術(shù)年會暨863計劃“深空探測與空間實驗技術(shù)”重大項目學術(shù)研討會論文集 2009-12-01

榮譽獎勵：

1、2008年入選教育部新世紀優(yōu)秀人才支持計劃。

資料更新中……

媒體報道：

曹軍威：物聯(lián)時代的新探索

曹軍威 博士，現(xiàn)任清華大學信息技術(shù)研究院研究員、院務(wù)委員會副主任，美國麻省理工學院訪問科學家。長期致力于基礎(chǔ)架構(gòu)科學、技術(shù)與應用研究。從事應用集成、網(wǎng)格計算、海量數(shù)據(jù)分析、云計算、物聯(lián)網(wǎng)、智能電網(wǎng)等方面的基礎(chǔ)研究、成果轉(zhuǎn)化和產(chǎn)業(yè)合作，致力于從基礎(chǔ)架構(gòu)的獨特視角總結(jié)其中的一般規(guī)律，開發(fā)共性關(guān)鍵技術(shù)，并在教育、制造、電力、石化等行業(yè)獲得廣泛應用。

物聯(lián)網(wǎng)被認為是繼計算機、互聯(lián)網(wǎng)之后，世界信息產(chǎn)業(yè)的第三次浪潮，它集傳感、通信、網(wǎng)絡(luò)、計算、控制技術(shù)為一體，應用領(lǐng)域遍及國民經(jīng)濟和社會服務(wù)的各個方面，如智能電網(wǎng)、智能交通、現(xiàn)代物流、數(shù)字醫(yī)療、節(jié)能環(huán)保、精準農(nóng)業(yè)等，成為我國未來發(fā)展的戰(zhàn)略新興產(chǎn)業(yè)。

計算機實現(xiàn)了信息和資源的數(shù)字化，互聯(lián)網(wǎng)使得信息的傳遞和共享成為可能，那么物聯(lián)網(wǎng)發(fā)展的內(nèi)在動因是什么呢？清華大學信息技術(shù)研究院研究員曹軍威和他的團隊一直致力于從基礎(chǔ)架構(gòu)（Infrastructure）的獨特視角開展物聯(lián)網(wǎng)技術(shù)與應用研究，并指出物聯(lián)網(wǎng)興起的內(nèi)在動因是21世紀新一輪基礎(chǔ)架構(gòu)化對資源深度互聯(lián)的需求。

“數(shù)聯(lián)”到“物聯(lián)”的跨越

技術(shù)的最新挑戰(zhàn)往往最先出現(xiàn)在重大科學前沿問題的探索過程中，比如Web的發(fā)明源于歐洲核子研究中心CERN。在回國工作之前，曹軍威曾經(jīng)在美國麻省理工學院空間研究中心工作過兩年多，開展愛因斯坦引力波探測和數(shù)據(jù)分析工作。當時，美國提出新一輪的基礎(chǔ)架構(gòu)化將以信息技術(shù)為引擎，主要指基于分布計算機、信息和通信技術(shù)的基礎(chǔ)架構(gòu)，稱為信息基礎(chǔ)架構(gòu)（Cyberinfrastructure），其對于知識經(jīng)濟的重要性可以與傳統(tǒng)基礎(chǔ)架構(gòu)對工業(yè)經(jīng)濟的支撐作用相比擬。

當時美國建成了世界上精度最高的激光干涉引力波天文臺LIGO，希望能直接探測和驗證愛因斯坦廣義相對論所預言的引力波的存在。天文臺實時采集上萬個傳感器的數(shù)據(jù)，采樣頻率最高達每秒16000次，匯集成上PB（1000TB）量級的引力波數(shù)據(jù)，需要分布在美國和歐洲十幾個節(jié)點的高性能集群計算機，為幾百名LIGO科學合作組織成員進行引力波數(shù)據(jù)分析提供服務(wù)，這本身就是一個廣域范圍內(nèi)集傳感、通信、存儲、計算等為一體的復雜系統(tǒng)，是未來信息基礎(chǔ)架構(gòu)的典型代表。

2006年，曹軍威回國后組織創(chuàng)建了清華大學LIGO工作組。在他的帶領(lǐng)下，工作組在引力波科學研究和LIGO實時數(shù)據(jù)分析方面的工作不斷取得進展，得到國際同行的認可。2009年9月，清華大學成為首個來自中國的LIGO科學合作組織成員，引力波數(shù)據(jù)分析結(jié)果發(fā)表在Nature等國際期刊上。

在數(shù)字世界中，已經(jīng)有一些類似現(xiàn)實世界中基礎(chǔ)架構(gòu)的成功例子，比如通過簡短的E-mail地址就可以實現(xiàn)通信；通過簡單的域名就可以登錄相應的Web主頁。這些實現(xiàn)了數(shù)字世界中的信息共享。而今數(shù)字世界的互聯(lián)發(fā)展進一步提出了與物理系統(tǒng)實時交互的需求，傳統(tǒng)基礎(chǔ)架構(gòu)要實現(xiàn)深度互聯(lián)也必須以信息技術(shù)為引擎，從“數(shù)聯(lián)”到“物聯(lián)”的發(fā)展便成為必然。

物聯(lián)網(wǎng)系統(tǒng)運行中涉及一組關(guān)鍵過程，包括物理狀態(tài)感知、信息表示、信息傳輸、分析決策和控制執(zhí)行。物理狀態(tài)感知主要是傳感器網(wǎng)通過有線和無線的網(wǎng)絡(luò)傳感數(shù)據(jù)。操作執(zhí)行主要由數(shù)字控制系統(tǒng)負責完成。物聯(lián)網(wǎng)中，傳感器和控制器的分布很廣且數(shù)據(jù)量巨大。過去10年，對物聯(lián)網(wǎng)的研究大部分都集中于感知層的無線網(wǎng)絡(luò)技術(shù)，但是，如何把各層網(wǎng)絡(luò)通信與應用軟件緊密地融合在一起，從而開發(fā)出高性能的物聯(lián)網(wǎng)應用，仍然是一個巨大的挑戰(zhàn)。曹軍威和他的研究團隊認為，物聯(lián)網(wǎng)發(fā)展的內(nèi)在動因是新一輪的基礎(chǔ)架構(gòu)化進程對數(shù)字和物理資源深度互聯(lián)的需求。

深化基礎(chǔ)架構(gòu)研究

在物聯(lián)網(wǎng)技術(shù)興起的今天，曹軍威根據(jù)十多年的科研和實踐經(jīng)驗，指出要想加速物聯(lián)網(wǎng)相關(guān)技術(shù)的基礎(chǔ)架構(gòu)化進程，基礎(chǔ)理論與方法的研究迫在眉睫�；�礎(chǔ)架構(gòu)是如此重要，但迄今為止對于基礎(chǔ)架構(gòu)的論述還主要停留在定性描述的層面或者局限于特定領(lǐng)域，還沒有對基礎(chǔ)架構(gòu)通用共有的特性進行定量、科學和系統(tǒng)的深入研究�；�礎(chǔ)架構(gòu)學（Infrastructurology）是對不同基礎(chǔ)架構(gòu)的通用共有規(guī)律進行深入研究的科學，目的是為當前以物聯(lián)網(wǎng)為代表的新一輪基礎(chǔ)架構(gòu)化進程提供堅實的理論依據(jù)、切實的方法指導和具體的技術(shù)實現(xiàn)。

看似是不同行業(yè)產(chǎn)業(yè)的前沿問題，實際上從基礎(chǔ)架構(gòu)化的角度進行詮釋時都是相通的。定量、科學、系統(tǒng)地研究基礎(chǔ)架構(gòu)主要從時間和空間兩個維度上研究基礎(chǔ)架構(gòu)共通的演進規(guī)律。這是之前任何單一學科或研究領(lǐng)域所未曾涉及的。曹軍威認識到：一方面基礎(chǔ)架構(gòu)的形成需要時間，需要不斷成熟的技術(shù)作為支撐，同時還受到經(jīng)濟、政治、文化等非技術(shù)因素的影響，但從整體上看還是有一定的規(guī)律可以探索，一旦掌握了這些規(guī)律，便可以更好地指導和加速新的基礎(chǔ)架構(gòu)化進程；另一方面，基礎(chǔ)架構(gòu)的空間分布也是有規(guī)律可循的，最為直觀的是大多數(shù)成熟的基礎(chǔ)架構(gòu)都采用分層樹狀結(jié)構(gòu)，比如電網(wǎng)就分為輸電、供電、配電等幾個層次，互聯(lián)網(wǎng)上的Domain Name Service也是采用樹狀結(jié)構(gòu)等。當然，基礎(chǔ)架構(gòu)學本身還是一門應用基礎(chǔ)科學。相較于系統(tǒng)論或復雜性理論研究都是以一般意義上的系統(tǒng)為研究對象，基礎(chǔ)架構(gòu)雖然也是復雜系統(tǒng)，但還是具有許多自身的特點，需要結(jié)合和運用基礎(chǔ)理論，采用不同的研究方法進行深入探索。為了避免在開始階段基礎(chǔ)架構(gòu)學的研究流于空泛，以特定領(lǐng)域、技術(shù)或應用作為切入點和著手點是必經(jīng)之路。

為了推動基礎(chǔ)架構(gòu)學發(fā)展，進而在物聯(lián)網(wǎng)技術(shù)及其應用方面有所貢獻，曹軍威迅速組建并發(fā)展起一支由20余人組成的高水平科研團隊。近年來，該團隊獲得國家科技部“973”計劃、“863”計劃、教育部質(zhì)量工程和國家自然科學基金等10余項國家級科研項目的資助。曹軍威發(fā)表文章110余篇，為國內(nèi)外同行引用2200余次，申請專利6項，并入選2008年教育部新世紀優(yōu)秀人才支持計劃。

物聯(lián)網(wǎng)與智能電網(wǎng)

除了在理論層面開展基礎(chǔ)架構(gòu)學研究外，曹軍威和他的團隊一直認為智能電網(wǎng)是物聯(lián)網(wǎng)的第一應用。在廣域范圍內(nèi)實現(xiàn)從感知到控制全過程的緊密耦合和深度互聯(lián)，智能電網(wǎng)在物聯(lián)網(wǎng)應用中的代表性是其他應用所無法替代的。選擇電力物聯(lián)網(wǎng)應用系統(tǒng)可以最大程度地驗證和說明物聯(lián)網(wǎng)技術(shù)的發(fā)展，這也是曹軍威和他的團隊目前的工作重點。

智能電網(wǎng)把現(xiàn)代先進的傳感—通信—網(wǎng)絡(luò)—計算—控制技術(shù)應用于電力系統(tǒng)以達到最大限度地提高設(shè)備效率，提高安全可靠性，節(jié)能減排，提高用戶的供電質(zhì)量，提高可再生能源的利用效率。目前，我國的GDP總量不到全世界的5%，卻耗費全世界30％以上的鋼鐵、47％的水泥，而且增長趨勢不減。照這樣下去，中國能源是不可能實現(xiàn)可持續(xù)發(fā)展的。智能電網(wǎng)的提出正是國家能源戰(zhàn)略和安全的需要。

智能電網(wǎng)包括三個層次：第一層次，實現(xiàn)對電網(wǎng)運行狀態(tài)、資產(chǎn)設(shè)備狀態(tài)和客戶用電信息的實時、全面和詳細監(jiān)視，消除監(jiān)測盲點，提高電網(wǎng)可觀測性；第二層次，提供先進的信息技術(shù)手段，實現(xiàn)對電力企業(yè)信息的傳輸和集成；第三層次，在信息集成的基礎(chǔ)上進行高級分析，實現(xiàn)提高可靠性、降低成本、提高收益和效率的目標。實際上這跟物聯(lián)網(wǎng)的基本結(jié)構(gòu)是不謀而合的。物聯(lián)網(wǎng)技術(shù)應用于智能電網(wǎng)不是名詞游戲，也不是概念炒作，它是現(xiàn)代電力系統(tǒng)發(fā)展的內(nèi)在需求和必然趨勢，是現(xiàn)代電力系統(tǒng)的發(fā)展新階段，將引發(fā)一系列新概念、新思路、新平臺、新前景，為電力系統(tǒng)技術(shù)的進步帶來大的變革。

電能是即時平衡的，過去電網(wǎng)靠“以不變應萬變”來達到動態(tài)平衡，于是大量冗余造成浪費，現(xiàn)在充分發(fā)揮物聯(lián)網(wǎng)的監(jiān)控作用，有可能靠與負荷互動來削“峰”填“谷”和減少熱備用，如果可行將引起從設(shè)計到運行的巨大變革。如果基于物聯(lián)網(wǎng)技術(shù)，使得測量和通訊問題（指令下行僅數(shù)十毫秒）得到解決，通過控制達到瞬間平衡，那么迄今靠“試探”來達到新平衡的各種穩(wěn)定措施，如暫態(tài)穩(wěn)定、頻率穩(wěn)定、低頻/低壓減載控制等都應該重新考慮。過去由于信息傳遞的困難，眾多研究者都力求選用測量本地量作為反饋來達到最好的控制效果，如果廣泛采用物聯(lián)網(wǎng)技術(shù)，可以把電力系統(tǒng)中最佳可觀點的物理量送到最佳可控的控制器去，打破“不可觀”和“不可控”的約束，就會給電力系統(tǒng)的控制帶來革命。信息采集和信息傳遞得到解決，可望消除監(jiān)測盲點，這樣，電力系統(tǒng)一些重要參數(shù)的隨機性、時變性、不可知性等可望克服，使過去只能“靠加大保守性來換取可靠性”的一系列經(jīng)典難題有可能得到解決。

面對電力物聯(lián)網(wǎng)所帶來的巨大發(fā)展空間，曹軍威和他的團隊開始大膽的思考和扎實的探索，并作為子課題負責人，獲得國家“973”計劃“物聯(lián)網(wǎng)基礎(chǔ)理論和設(shè)計方法研究”項目的資助，負責實現(xiàn)電力物聯(lián)網(wǎng)仿真驗證平臺，為物聯(lián)網(wǎng)理論和方法研究提供支撐環(huán)境。他們發(fā)現(xiàn)，實現(xiàn)電力物聯(lián)網(wǎng)的主要挑戰(zhàn)在于廣域電網(wǎng)是一個復雜大系統(tǒng)，硬件設(shè)備、廣域網(wǎng)絡(luò)和負荷用戶等多方面的因素帶來了很大的隨機性和不確定性，傳統(tǒng)解決問題的方法已經(jīng)不能從實質(zhì)上解決廣域電網(wǎng)監(jiān)控的“精”和“準”的問題，需要依賴物聯(lián)網(wǎng)新技術(shù)保證信息傳遞的保真和忠實，軟件編程的忠實和可信等。具體而言，需要研究在線、實時、海量數(shù)據(jù)的采集、傳輸與存儲，變參數(shù)、變約束、多時間尺度下的數(shù)據(jù)分析與決策和變故障情況，以及變執(zhí)行機構(gòu)的分層系統(tǒng)控制技術(shù)等。曹軍威和他的團隊堅信，把現(xiàn)代信息技術(shù)廣泛引入到電力系統(tǒng)確實可以解決以前認為無法解決的問題，產(chǎn)生空前巨大的經(jīng)濟、社會效益。

電力系統(tǒng)是傳統(tǒng)基礎(chǔ)架構(gòu)的典型代表，新一輪基礎(chǔ)架構(gòu)化進程提出了智能電網(wǎng)的要求，而要實現(xiàn)電力系統(tǒng)發(fā)電和用電的互動，實現(xiàn)廣域電網(wǎng)感知到控制全過程的緊密耦合和深度互聯(lián)，引入物聯(lián)網(wǎng)技術(shù)勢在必行。物聯(lián)網(wǎng)是從“數(shù)聯(lián)”向“物聯(lián)”延伸的產(chǎn)物，其產(chǎn)業(yè)發(fā)展離不開具體行業(yè)應用的依托和支持，實現(xiàn)電力物聯(lián)網(wǎng)是其中重要的發(fā)展方向。曹軍威和他的團隊會沿著這個方向堅定地走下去，探索和嘗試將物聯(lián)網(wǎng)和智能電網(wǎng)有機結(jié)合，力爭在基礎(chǔ)研究、成果轉(zhuǎn)化和產(chǎn)業(yè)合作等方面作出新的貢獻。

文章來源：《科學時報》 2011-03-08