Liu Shijun
Gender:Male
Education Level:With Certificate of Graduation for Doctorate Study
Alma Mater:Shandong University
Scientific Research
Working-Papers
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Shijun Liu is a professor of the School of Software at Shandong University, China. He obtained his BS degrees in oceanography from Ocean University of China, and MS and PhD degree in computer science from Shandong University, China. From July, 2012 to July, 2013, he worked as a visiting scholar at College of Computing, Georgia Institute of Technology, USA. He is a senior member of IEEE;a member of China Computer Federation TC on Service Computing, TC on Cooperative Computing and CCF Task Force on Big Data (CCF TCSC, CCF TCCC and CCF TFBD), a member of IFIP WG5.8, and a member of China National Technical Committee for Automation Systems and Integration Standardization.
His current research interests center around Services Computing, Cooperative Computing and Big Data with a focus on enterprise services computing and manufacturing big data. He has published 4 books and over 170 papers in journals and conferences and obtained many academic awards including the Nation Scientific and Technological Progress Award in 2002.
Paper Publications
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郑冰冰. A truthful mechanism for optimally purchasing iaas instances and scheduling parallel jobs in service clouds. 16th International Conference on Service-Oriented Computing, ICSOC 2018, 11236 LNCS, 651-659, 2025.
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刘明宇. Collaborative Storage for Tiered Cloud and Edge: A Perspective of Optimizing Cost and Latency. IEEE Transactions on Mobile Computing, 1-18, 2025.
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屈娅婷. Predict industry merger waves utilizing supply network information. Journal of Ambient Intelligence and Humanized Computing, 2024.
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刘明宇. Collaborative Storage for Tiered Cloud and Edge: A Perspective of Optimizing Cost and Latency. IEEE Transactions on Mobile Computing, 2024.
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杨昊. Faster or Cheaper: A Q-learning based cost-effective mixed cluster scaling method for achieving low tail latencies. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING THEORY METHODS AND APPLICATIONS, 264, 2024.
Patents
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