L
Limin Zhang
Researcher at North Dakota State University
Publications - 23
Citations - 1032
Limin Zhang is an academic researcher from North Dakota State University. The author has contributed to research in topics: Social loafing & Social compensation. The author has an hindex of 8, co-authored 23 publications receiving 916 citations. Previous affiliations of Limin Zhang include University of Arizona.
Papers
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Journal ArticleDOI
A literature review on the state-of-the-art in patent analysis
TL;DR: The literature review presents the state-of-the-art in patent analysis and also presents taxonomy of patent analysis techniques and several directions for future research are highlighted.
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An overview of energy efficiency techniques in cluster computing systems
Giorgio Luigi Valentini,Walter Lassonde,Samee U. Khan,Nasro Min-Allah,Sajjad A. Madani,Juan Li,Limin Zhang,Lizhe Wang,Nasir Ghani,Joanna Kolodziej,Hongxiang Li,Albert Y. Zomaya,Cheng-Zhong Xu,Pavan Balaji,Abhinav Vishnu,Fredric Pinel,Johnatan E. Pecero,Dzmitry Kliazovich,Pascal Bouvry +18 more
TL;DR: This survey focuses on the characteristic of two main power management technologies:static power management systems that utilize low-power components to save the energy, and dynamic power management techniques that utilize software and power-scalable components to optimize the energy consumption.
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A survey on resource allocation in high performance distributed computing systems
Hameed Hussain,Saif Ur Rehman Malik,Abdul Hameed,Samee U. Khan,Gage Bickler,Nasro Min-Allah,Muhammad Bilal Qureshi,Limin Zhang,Wang Yong-Ji,Nasir Ghani,Joanna Kolodziej,Albert Y. Zomaya,Cheng-Zhong Xu,Pavan Balaji,Abhinav Vishnu,Fredric Pinel,Johnatan E. Pecero,Dzmitry Kliazovich,Pascal Bouvry,Hongxiang Li,Lizhe Wang,Dan Chen,Ammar Rayes +22 more
TL;DR: In this study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported and the system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.
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Quantitative comparisons of the state-of-the-art data center architectures
Kashif Bilal,Samee U. Khan,Limin Zhang,Hongxiang Li,Khizar Hayat,Sajjad A. Madani,Nasro Min-Allah,Lizhe Wang,Dan Chen,Majid I. Iqbal,Cheng-Zhong Xu,Albert Y. Zomaya +11 more
TL;DR: This paper has implemented and simulated the state of the art DCN models in this paper, namely: (a) legacy DCN architecture, (b) switch‐based, and (c) hybrid models, and compared their effectiveness by monitoring the network: throughput and average packet delay.
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A survey on context-aware recommender systems based on computational intelligence techniques
TL;DR: This survey aims to encompass the state-of-the-art context-aware recommender systems based on the Computational Intelligence techniques, and discusses the strengths and weaknesses of each of the CI techniques used in context- AwareRecommender systems.