H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 62 Citations 15,829 654 World Ranking 1391 National Ranking 791

Research.com Recognitions

Awards & Achievements

2015 - IEEE Fellow For contributions to parallel and distributed computing

2007 - ACM Senior Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Artificial intelligence
  • Computer network

Keqin Li mainly focuses on Distributed computing, Scheduling, Cloud computing, Parallel computing and Dynamic priority scheduling. In his research on the topic of Distributed computing, Differential evolution and Bi objective is strongly related with Workflow. The Scheduling study combines topics in areas such as Symmetric multiprocessor system, Schedule and Heuristic.

The various areas that he examines in his Symmetric multiprocessor system study include Genetic algorithm and Heuristic. His Cloud computing research is multidisciplinary, incorporating perspectives in Quality of service, Computer network, Server and Virtual machine. In his research, Big data is intimately related to Computer cluster, which falls under the overarching field of Parallel computing.

His most cited work include:

  • A genetic algorithm for task scheduling on heterogeneous computing systems using multiple priority queues (227 citations)
  • A genetic algorithm for task scheduling on heterogeneous computing systems using multiple priority queues (227 citations)
  • A Parallel Random Forest Algorithm for Big Data in a Spark Cloud Computing Environment (180 citations)

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

His primary scientific interests are in Distributed computing, Parallel computing, Scheduling, Cloud computing and Algorithm. His Distributed computing research is multidisciplinary, relying on both Frequency scaling, Computer network, Directed acyclic graph and Mobile edge computing. His study in Parallel computing is interdisciplinary in nature, drawing from both Time complexity and Scalability.

His Scheduling research incorporates elements of Symmetric multiprocessor system, Schedule and Mathematical optimization. Keqin Li interconnects Virtual machine, Quality of service, Data center, Encryption and Server in the investigation of issues within Cloud computing. His study connects Fair-share scheduling and Dynamic priority scheduling.

He most often published in these fields:

  • Distributed computing (28.61%)
  • Parallel computing (24.40%)
  • Scheduling (23.14%)

What were the highlights of his more recent work (between 2019-2021)?

  • Cloud computing (22.58%)
  • Distributed computing (28.61%)
  • Artificial intelligence (13.32%)

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

His primary areas of investigation include Cloud computing, Distributed computing, Artificial intelligence, Scheduling and Quality of service. His Cloud computing study combines topics from a wide range of disciplines, such as Virtual machine, Scalability, Resource, Encryption and Server. The concepts of his Distributed computing study are interwoven with issues in Artificial neural network and Enhanced Data Rates for GSM Evolution, Mobile edge computing.

The study incorporates disciplines such as Machine learning and Pattern recognition in addition to Artificial intelligence. His study in Scheduling focuses on Job shop scheduling in particular. Keqin Li combines subjects such as Directed acyclic graph and Task with his study of Quality of service.

Between 2019 and 2021, his most popular works were:

  • Distributed Deep Learning Model for Intelligent Video Surveillance Systems with Edge Computing (59 citations)
  • A Survey of Intrusion Detection for In-Vehicle Networks (38 citations)
  • Minimizing Redundancy to Satisfy Reliability Requirement for a Parallel Application on Heterogeneous Service-Oriented Systems (30 citations)

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

  • Operating system
  • Artificial intelligence
  • Computer network

His primary areas of study are Cloud computing, Distributed computing, Quality of service, Scheduling and Mathematical optimization. His work deals with themes such as Scalability, Server, Encryption and Job shop scheduling, which intersect with Cloud computing. His Distributed computing study combines topics in areas such as Overhead, Computational complexity theory, Wireless sensor network, Approximation algorithm and Directed acyclic graph.

His studies in Quality of service integrate themes in fields like Variation, TOPSIS, Set, Selection and Mahalanobis distance. His biological study spans a wide range of topics, including Artificial neural network, Schedule, Access time and Downtime. As a part of the same scientific study, Keqin Li usually deals with the Mathematical optimization, concentrating on Stackelberg competition and frequently concerns with The Internet.

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.

Top Publications

A genetic algorithm for task scheduling on heterogeneous computing systems using multiple priority queues

Yuming Xu;Kenli Li;Jingtong Hu;Keqin Li;Keqin Li.
Information Sciences (2014)

314 Citations

A Parallel Random Forest Algorithm for Big Data in a Spark Cloud Computing Environment

Jianguo Chen;Kenli Li;Zhuo Tang;Kashif Bilal.
IEEE Transactions on Parallel and Distributed Systems (2017)

262 Citations

Optimal dynamic mobility management for PCS networks

Jie Li;Hisao Kameda;Keqin Li.
IEEE ACM Transactions on Networking (2000)

233 Citations

A Comprehensive Survey of Network Function Virtualization

Bo Yi;Xingwei Wang;Keqin Li;Sajal k. Das.
Computer Networks (2018)

230 Citations

A two dimensional buddy system for dynamic resource allocation in a partitionable mesh connected system

Keqin Li;Kam Hoi Cheng.
conference on scientific computing (1990)

217 Citations

Optimal Multiserver Configuration for Profit Maximization in Cloud Computing

Junwei Cao;Kai Hwang;Keqin Li;Albert Y. Zomaya.
IEEE Transactions on Parallel and Distributed Systems (2013)

210 Citations

A two-dimensional buddy systems for dynamic resource allocation in a partitionable mesh connected system

Keqin Li;Kam-Hoi Cheng.
Journal of Parallel and Distributed Computing (1991)

195 Citations

Optimal Power Allocation and Load Distribution for Multiple Heterogeneous Multicore Server Processors across Clouds and Data Centers

Junwei Cao;Keqin Li;Ivan Stojmenovic.
IEEE Transactions on Computers (2014)

192 Citations

An Energy-Efficient Task Scheduling Algorithm in DVFS-enabled Cloud Environment

Zhuo Tang;Ling Qi;Zhenzhen Cheng;Kenli Li.
grid computing (2016)

188 Citations

Energy-Efficient Stochastic Task Scheduling on Heterogeneous Computing Systems

Kenli Li;Xiaoyong Tang;Keqin Li.
IEEE Transactions on Parallel and Distributed Systems (2014)

160 Citations

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

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Top Scientists Citing Keqin Li

Albert Y. Zomaya

Albert Y. Zomaya

University of Sydney

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Kenli Li

Kenli Li

Hunan University

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Samee U. Khan

Samee U. Khan

Mississippi State University

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Rajkumar Buyya

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University of Melbourne

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Laurence T. Yang

Laurence T. Yang

St. Francis Xavier University

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Jin Wang

Jin Wang

Changsha University of Science and Technology

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Jie Li

Jie Li

Xidian University

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Shi-Jinn Horng

Shi-Jinn Horng

National Taiwan University of Science and Technology

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Xiaolong Xu

Xiaolong Xu

Nanjing University of Information Science and Technology

Publications: 21

Rajiv Ranjan

Rajiv Ranjan

Newcastle University

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MengChu Zhou

MengChu Zhou

New Jersey Institute of Technology

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Shui Yu

Shui Yu

University of Technology Sydney

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Kim-Kwang Raymond Choo

Kim-Kwang Raymond Choo

The University of Texas at San Antonio

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Lizhe Wang

Lizhe Wang

China University of Geosciences

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Qiang He

Qiang He

Swinburne University of Technology

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