D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 44 Citations 9,957 323 World Ranking 2065 National Ranking 208

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Computer network
  • The Internet

Ming Zhao focuses on Virtual machine, Virtualization, Operating system, Resource allocation and Server. His study in Virtual machine is interdisciplinary in nature, drawing from both Virtual prototyping, Capacity planning, Real-time computing and Dynamic priority scheduling. His Virtualization research includes themes of Iterative and incremental development and Distributed computing.

Ming Zhao has researched Operating system in several fields, including Layer and Key. His biological study spans a wide range of topics, including Data modeling, Database, Quality of service, Memory management and Reservation. The various areas that he examines in his Server study include Process, Provisioning and Data center.

His most cited work include:

  • From virtualized resources to virtual computing grids: the In-VIGO system (215 citations)
  • Experimental study of virtual machine migration in support of reservation of cluster resources (173 citations)
  • On the Use of Fuzzy Modeling in Virtualized Data Center Management (168 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of investigation include Operating system, Distributed computing, Virtual machine, Virtualization and Cloud computing. His Distributed computing study integrates concerns from other disciplines, such as Node, Quality of service, Job scheduler and Network File System. Ming Zhao combines subjects such as Overhead and Resource allocation with his study of Virtual machine.

The Resource allocation study combines topics in areas such as Database and Autonomic computing. His Virtualization research incorporates themes from Utility computing, Provisioning and Latency. His Cloud computing research integrates issues from Computer security and Deep learning, Artificial intelligence.

He most often published in these fields:

  • Operating system (33.33%)
  • Distributed computing (33.33%)
  • Virtual machine (27.78%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (11.11%)
  • Operating system (33.33%)
  • Metadata (5.56%)

In recent papers he was focusing on the following fields of study:

The scientist’s investigation covers issues in Artificial intelligence, Operating system, Metadata, Computer data storage and Cache. His work is connected to Memory footprint, Flash memory and Virtual machine, as a part of Operating system. His Metadata research incorporates elements of File system and Server.

His research integrates issues of Temporal isolation among virtual machines, Virtualization, Bandwidth allocation, I/O scheduling and Scheduling in his study of Server. His Workflow research is multidisciplinary, relying on both Edge computing and Distributed computing. His studies deal with areas such as Data deduplication and Enhanced Data Rates for GSM Evolution as well as Distributed computing.

Between 2018 and 2021, his most popular works were:

  • Exploring the Use of Synthetic Gradients for Distributed Deep Learning across Cloud and Edge Resources (7 citations)
  • GFCache: a Greedy Failure Cache Considering Failure Recency and Failure Frequency for an Erasure-coded Storage System (5 citations)
  • SmartDedup: Optimizing deduplication for resource-constrained devices (4 citations)

In his most recent research, the most cited papers focused on:

  • Operating system
  • Computer network
  • The Internet

His primary areas of investigation include Data deduplication, Deep learning, Artificial intelligence, Resource constrained and Distributed computing. His work deals with themes such as Mode, Hash function, Embedded system and Encryption, which intersect with Data deduplication. His Deep learning study combines topics in areas such as Enhanced Data Rates for GSM Evolution, Human–computer interaction, Computational science, Hardware acceleration and Cloud computing.

In general Artificial intelligence study, his work on Edge computing and Artificial neural network often relates to the realm of Personalization, thereby connecting several areas of interest.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

An overview of advances in biomass gasification

Vineet Singh Sikarwar;Ming Zhao;Ming Zhao;Peter Clough;Joseph Yao.
Energy and Environmental Science (2016)

401 Citations

From virtualized resources to virtual computing grids: the In-VIGO system

Sumalatha Adabala;Vineet Chadha;Puneet Chawla;Renato Figueiredo.
grid computing (2005)

320 Citations

Influence of annealing temperature on the properties of titanium oxide thin film

Ya Q. Hou;Da Ming Zhuang;Gong Zhang;Ming Zhao.
Applied Surface Science (2003)

302 Citations

Opportunities and challenges in sustainable treatment and resource reuse of sewage sludge: A review

Abdul Raheem;Vineet Singh Sikarwar;Jun He;Wafa Dastyar.
Chemical Engineering Journal (2017)

283 Citations

A review of techno-economic models for the retrofitting of conventional pulverised-coal power plants for post-combustion capture (PCC) of CO2

Ming Zhao;Andrew I. Minett;Andrew T. Harris.
Energy and Environmental Science (2013)

244 Citations

A review on sustainable microalgae based biofuel and bioenergy production: Recent developments

Abdul Raheem;Abdul Raheem;Pepijn Prinsen;Arun K. Vuppaladadiyam;Arun K. Vuppaladadiyam;Ming Zhao;Ming Zhao.
Journal of Cleaner Production (2018)

230 Citations

On the Use of Fuzzy Modeling in Virtualized Data Center Management

Jing Xu;Ming Zhao;J. Fortes;R. Carpenter.
international conference on autonomic computing (2007)

229 Citations

Change-point problems in software and hardware reliability

Ming Zhao.
Communications in Statistics-theory and Methods (1993)

218 Citations

Simulation of sea-land breezes and a discussion of their implications on the transport of air pollution during a multi-day ozone episode in the Pearl River Delta of China

Aijun Ding;Aijun Ding;Tao Wang;Ming Zhao;Tijian Wang.
Atmospheric Environment (2004)

214 Citations

Biomass-based chemical looping technologies: the good, the bad and the future

Xiao Zhao;Hui Zhou;Vineet Singh Sikarwar;Ming Zhao.
Energy and Environmental Science (2017)

196 Citations

Best Scientists Citing Ming Zhao

Wei-Hsin Chen

Wei-Hsin Chen

National Cheng Kung University

Publications: 29

José A. B. Fortes

José A. B. Fortes

University of Florida

Publications: 29

Edward J. Anthony

Edward J. Anthony

Cranfield University

Publications: 28

Chunfei Wu

Chunfei Wu

Queen's University Belfast

Publications: 28

Xun Hu

Xun Hu

University of Jinan

Publications: 26

Vasilije Manovic

Vasilije Manovic

Cranfield University

Publications: 24

Guanyi Chen

Guanyi Chen

Tianjin University of Commerce

Publications: 22

Aijun Ding

Aijun Ding

Nanjing University

Publications: 20

Tao Wang

Tao Wang

Hong Kong Polytechnic University

Publications: 19

Qiang Wang

Qiang Wang

Beijing Forestry University

Publications: 17

Tijian Wang

Tijian Wang

Nanjing University

Publications: 16

Hai Jin

Hai Jin

Huazhong University of Science and Technology

Publications: 16

Xian-Yong Wei

Xian-Yong Wei

China University of Mining and Technology

Publications: 15

Young-Kwon Park

Young-Kwon Park

Seoul National University

Publications: 15

Pau Loke Show

Pau Loke Show

University of Nottingham Malaysia Campus

Publications: 15

Paul T. Williams

Paul T. Williams

University of Leeds

Publications: 15

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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