科學研究：

研究方向：

主要從事先進計算技術及其應用研究。

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在計算技術和應，2009-2011。

2、中國國家自然科學獎基金：對網絡基礎設施的理論和資源優化與動態約束算法，2009-2011。

3、中國教育部的科研基金：引力波數據分析使用開放科學網，2008-2009。

4、國家863高技術研發計劃：大型網絡化數據整合與查詢處理，2008-2009。

5、國家863高技術研發計劃：組織，管理和農業海量知識資源服務，2007-2009。

6、教育部：全國綜合系統開放課程，2007-2010。

7、國家863高技術研發計劃：數字農業知識網格，2006-2010。

8、清華大學研究院：網絡基礎設施的應用啟用，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絡基礎設施，2009。

10、清華大學骨干人才計劃：網絡基礎設施技術，2007-2008。

11、信息科學與技術學院清華大學：網絡基礎設施技術，2006 -2008。

12、LIGO的部署數據網格，網格，使社區引力波分析，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（IST）項目:GEMSS：網格仿真功能的醫療服務，2002 -2004。

15、NEC支持的項目：相關譜的集群和網格作業調度，2002-2004。

16、貿易和工業�。∕ETI）日本網絡計算項目部：優化利用網格Datafarm對接構象，2002-2003。

17、美國航天局艾姆斯研究中心：面向計算網格系統管理工具發展，2001-2002。

18、華威研究生院主席特別研究獎學金:基于Agent的網格計算資源管理，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：為北京管理科學和技術委員會管理信息系統，1995-1996。

科研成果：

資料更新中……

發明專利：

1、提高分布式系統性能調優速度的方法 曹軍威; 張帆 清華大學 【中國專利】清華大學 2009-12-23

論文專著：

發表論文110余篇，出版專著10余部。

出版專著：

1《多代理系統理論、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《復雜系統的面向對象建模、分析與設計》范玉順，曹軍威清華大學出版社，2000年9。

3《網絡基礎設施技術及應用》Nova科學出版社，2009年。

4《網絡基礎設施與應用技術》新科學出版社，2009年。

5《網格數據流》Nova科學出版社，2008年。

6《對于大規模分布式環境中的性能預測技術研究》Nova科學出版社，2007年。

7《績效評估的自組織網格計算代理》Nova科學出版社，2007年。

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

發表論文：

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.

103. Agile Data Streaming for Grid Applications. W. Zhang, J. Cao, Y. Zhong, L. Liu, and C. Wu. Proc. 2nd Int. Workshop on Personalization in Grid and Service Computing, conj. 7th Int. Conf. on Grid and Cooperative Computing, Shenzhen, China, 739-746, 2008.

104. Agent-based Resource Management for Grid Computing. J. Cao, D. P. Spooner, J. D. Turner, S. A. Jarvis, D. J. Kerbyson, S. Saini and G. R. Nudd. Proc. 2nd Int. Workshop on Agent based Cluster and Grid Computing, conj. 2nd IEEE/ACM Int. Symp. on Cluster Computing and the Grid, Berlin, Germany, 350-351, 2002. (short paper)

105. Agent-Based Grid Load Balancing Using Performance-Driven Task Scheduling. J. Cao, D. P. Spooner, S. A. Jarvis, S. Saini and G. R. Nudd. Proc. 17th IEEE Int. Parallel & Distributed Processing Symp., Nice, France, 49, 2003.

106. Agent-Aided Software Engineering of High Performance Applications. J. Cao. Proc. 12th Int. Conf. on Software & Systems Engineering and their Applications, Paris, France, 1999.

107. Adjacent Matrix based Deduction for Grid Workflow Applications. F. Zhang, J. Cao, L. Liu, and C. Wu. Proc. 1st Int. Conf. on Networking and Distributed Computing, Hangzhou, China, 349-356, 2010.

108. A Transaction Definition Language for Java Application Response Measurement. J. D. Turner, D. P. Spooner, J. Cao, S. A. Jarvis, D. N. Dillenberger and G. R. Nudd. J. Computer Resource Management, 105, 55-65, 2002.

109. A Search for Gravitational Waves Associated with the August 2006 Timing Glitch of the Vela Pulsar. LIGO Scientific Collaboration and S. Buchner. Physical Review D, 83(4), 042001(13), 2010.

110. A Joint Search for Gravitational Wave Bursts with AURIGA and LIGO. AURIGA Collaboration and LIGO Scientific Collaboration. Classical and Quantum Gravity, 25(9), 095004(16), 2008.

111. A Finite Element Based Tool Chain for the Planning and Simulation of Maxillo-Facial Surgery. J. G. Schmidt, G. Berti, J. Fingberg, J. Cao, and G. Wollny. Proc. 4th European Congress on Computational Methods in Applied Sciences and Engineering, Jyvaskyla, Finland, 2004. (also as Technical Report LR-04-197, NEC Corporation, 2004)

中文：

1 云制造——面向服務的網絡化制造新模式 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品先進制造系統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; 清華大學信息技術研究院; 北京慧點科技開發有限公司 【期刊】計算機集成制造系統 2010-01-15

2 集成平臺運控系統代理模型研究 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-CIMS 1999-06-30

3 新一代 CIMS應用集成平臺系統體系結構 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專業委員會第六屆學術年會暨863計劃“深空探測與空間實驗技術”重大項目學術研討會論文集 2009-12-01

榮譽獎勵：

1、2008年入選教育部新世紀優秀人才支持計劃。

資料更新中……

媒體報道：

曹軍威：物聯時代的新探索

曹軍威 博士，現任清華大學信息技術研究院研究員、院務委員會副主任，美國麻省理工學院訪問科學家。長期致力于基礎架構科學、技術與應用研究。從事應用集成、網格計算、海量數據分析、云計算、物聯網、智能電網等方面的基礎研究、成果轉化和產業合作，致力于從基礎架構的獨特視角總結其中的一般規律，開發共性關鍵技術，并在教育、制造、電力、石化等行業獲得廣泛應用。

物聯網被認為是繼計算機、互聯網之后，世界信息產業的第三次浪潮，它集傳感、通信、網絡、計算、控制技術為一體，應用領域遍及國民經濟和社會服務的各個方面，如智能電網、智能交通、現代物流、數字醫療、節能環保、精準農業等，成為我國未來發展的戰略新興產業。

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

“數聯”到“物聯”的跨越

技術的最新挑戰往往最先出現在重大科學前沿問題的探索過程中，比如Web的發明源于歐洲核子研究中心CERN。在回國工作之前，曹軍威曾經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據分析工作。當時，美國提出新一輪的基礎架構化將以信息技術為引擎，主要指基于分布計算機、信息和通信技術的基礎架構，稱為信息基礎架構（Cyberinfrastructure），其對于知識經濟的重要性可以與傳統基礎架構對工業經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據，采樣頻率最高達每秒16000次，匯集成上PB（1000TB）量級的引力波數據，需要分布在美國和歐洲十幾個節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據分析提供服務，這本身就是一個廣域范圍內集傳感、通信、存儲、計算等為一體的復雜系統，是未來信息基礎架構的典型代表。

2006年，曹軍威回國后組織創建了清華大學LIGO工作組。在他的帶領下，工作組在引力波科學研究和LIGO實時數據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，引力波數據分析結果發表在Nature等國際期刊上。

在數字世界中，已經有一些類似現實世界中基礎架構的成功例子，比如通過簡短的E-mail地址就可以實現通信；通過簡單的域名就可以登錄相應的Web主頁。這些實現了數字世界中的信息共享。而今數字世界的互聯發展進一步提出了與物理系統實時交互的需求，傳統基礎架構要實現深度互聯也必須以信息技術為引擎，從“數聯”到“物聯”的發展便成為必然。

物聯網系統運行中涉及一組關鍵過程，包括物理狀態感知、信息表示、信息傳輸、分析決策和控制執行。物理狀態感知主要是傳感器網通過有線和無線的網絡傳感數據。操作執行主要由數字控制系統負責完成。物聯網中，傳感器和控制器的分布很廣且數據量巨大。過去10年，對物聯網的研究大部分都集中于感知層的無線網絡技術，但是，如何把各層網絡通信與應用軟件緊密地融合在一起，從而開發出高性能的物聯網應用，仍然是一個巨大的挑戰。曹軍威和他的研究團隊認為，物聯網發展的內在動因是新一輪的基礎架構化進程對數字和物理資源深度互聯的需求。

深化基礎架構研究

在物聯網技術興起的今天，曹軍威根據十多年的科研和實踐經驗，指出要想加速物聯網相關技術的基礎架構化進程，基礎理論與方法的研究迫在眉睫�；�礎架構是如此重要，但迄今為止對于基礎架構的論述還主要停留在定性描述的層面或者局限于特定領域，還沒有對基礎架構通用共有的特性進行定量、科學和系統的深入研究�；�礎架構學（Infrastructurology）是對不同基礎架構的通用共有規律進行深入研究的科學，目的是為當前以物聯網為代表的新一輪基礎架構化進程提供堅實的理論依據、切實的方法指導和具體的技術實現。

看似是不同行業產業的前沿問題，實際上從基礎架構化的角度進行詮釋時都是相通的。定量、科學、系統地研究基礎架構主要從時間和空間兩個維度上研究基礎架構共通的演進規律。這是之前任何單一學科或研究領域所未曾涉及的。曹軍威認識到：一方面基礎架構的形成需要時間，需要不斷成熟的技術作為支撐，同時還受到經濟、政治、文化等非技術因素的影響，但從整體上看還是有一定的規律可以探索，一旦掌握了這些規律，便可以更好地指導和加速新的基礎架構化進程；另一方面，基礎架構的空間分布也是有規律可循的，最為直觀的是大多數成熟的基礎架構都采用分層樹狀結構，比如電網就分為輸電、供電、配電等幾個層次，互聯網上的Domain Name Service也是采用樹狀結構等。當然，基礎架構學本身還是一門應用基礎科學。相較于系統論或復雜性理論研究都是以一般意義上的系統為研究對象，基礎架構雖然也是復雜系統，但還是具有許多自身的特點，需要結合和運用基礎理論，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架構學的研究流于空泛，以特定領域、技術或應用作為切入點和著手點是必經之路。

為了推動基礎架構學發展，進而在物聯網技術及其應用方面有所貢獻，曹軍威迅速組建并發展起一支由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。曹軍威發表文章110余篇，為國內外同行引用2200余次，申請專利6項，并入選2008年教育部新世紀優秀人才支持計劃。

物聯網與智能電網

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

智能電網把現代先進的傳感—通信—網絡—計算—控制技術應用于電力系統以達到最大限度地提高設備效率，提高安全可靠性，節能減排，提高用戶的供電質量，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可持續發展的。智能電網的提出正是國家能源戰略和安全的需要。

智能電網包括三個層次：第一層次，實現對電網運行狀態、資產設備狀態和客戶用電信息的實時、全面和詳細監視，消除監測盲點，提高電網可觀測性；第二層次，提供先進的信息技術手段，實現對電力企業信息的傳輸和集成；第三層次，在信息集成的基礎上進行高級分析，實現提高可靠性、降低成本、提高收益和效率的目標。實際上這跟物聯網的基本結構是不謀而合的。物聯網技術應用于智能電網不是名詞游戲，也不是概念炒作，它是現代電力系統發展的內在需求和必然趨勢，是現代電力系統的發展新階段，將引發一系列新概念、新思路、新平臺、新前景，為電力系統技術的進步帶來大的變革。

電能是即時平衡的，過去電網靠“以不變應萬變”來達到動態平衡，于是大量冗余造成浪費，現在充分發揮物聯網的監控作用，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計到運行的巨大變革。如果基于物聯網技術，使得測量和通訊問題（指令下行僅數十毫秒）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定措施，如暫態穩定、頻率穩定、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，如果廣泛采用物聯網技術，可以把電力系統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，可望消除監測盲點，這樣，電力系統一些重要參數的隨機性、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”的一系列經典難題有可能得到解決。

面對電力物聯網所帶來的巨大發展空間，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“物聯網基礎理論和設計方法研究”項目的資助，負責實現電力物聯網仿真驗證平臺，為物聯網理論和方法研究提供支撐環境。他們發現，實現電力物聯網的主要挑戰在于廣域電網是一個復雜大系統，硬件設備、廣域網絡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，傳統解決問題的方法已經不能從實質上解決廣域電網監控的“精”和“準”的問題，需要依賴物聯網新技術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、海量數據的采集、傳輸與存儲，變參數、變約束、多時間尺度下的數據分析與決策和變故障情況，以及變執行機構的分層系統控制技術等。曹軍威和他的團隊堅信，把現代信息技術廣泛引入到電力系統確實可以解決以前認為無法解決的問題，產生空前巨大的經濟、社會效益。

電力系統是傳統基礎架構的典型代表，新一輪基礎架構化進程提出了智能電網的要求，而要實現電力系統發電和用電的互動，實現廣域電網感知到控制全過程的緊密耦合和深度互聯，引入物聯網技術勢在必行。物聯網是從“數聯”向“物聯”延伸的產物，其產業發展離不開具體行業應用的依托和支持，實現電力物聯網是其中重要的發展方向。曹軍威和他的團隊會沿著這個方向堅定地走下去，探索和嘗試將物聯網和智能電網有機結合，力爭在基礎研究、成果轉化和產業合作等方面作出新的貢獻。

文章來源：《科學時報》 2011-03-08