What is he best known for?
The fields of study he is best known for:
- Operating system
- Computer network
- The Internet
Meikang Qiu focuses on Cloud computing, Distributed computing, Computer security, Computer network and Embedded system.
His research integrates issues of Network architecture and Cyber-physical system in his study of Cloud computing.
His Distributed computing research includes elements of Resource allocation, Quality of service, Memory model, Scheduling and Computer security model.
His research on Computer security often connects related topics like Big data.
His study focuses on the intersection of Computer network and fields such as Wireless with connections in the field of Mobile device, Power management and Communications security.
His Embedded system study also includes
- Registered memory, which have a strong connection to Cache-only memory architecture and Computer memory,
- Interleaved memory which is related to area like Random access memory and Parallel computing.
His most cited work include:
- Health-CPS: Healthcare Cyber-Physical System Assisted by Cloud and Big Data (410 citations)
- Dynamic energy-aware cloudlet-based mobile cloud computing model for green computing (330 citations)
- Online optimization for scheduling preemptable tasks on IaaS cloud systems (302 citations)
What are the main themes of his work throughout his whole career to date?
Meikang Qiu mainly focuses on Cloud computing, Distributed computing, Computer security, Computer network and Scheduling.
His Cloud computing research focuses on Big data and how it relates to Data science.
Meikang Qiu works mostly in the field of Distributed computing, limiting it down to topics relating to Real-time computing and, in certain cases, Wireless sensor network, as a part of the same area of interest.
His studies deal with areas such as Cloud computing security and Financial services as well as Computer security.
His studies in Computer network integrate themes in fields like Wireless and Wireless network.
The various areas that he examines in his Scheduling study include Embedded system and Parallel computing.
He most often published in these fields:
- Cloud computing (25.30%)
- Distributed computing (24.11%)
- Computer security (14.42%)
What were the highlights of his more recent work (between 2018-2021)?
- Cloud computing (25.30%)
- Artificial intelligence (6.86%)
- Computer security (14.42%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Cloud computing, Artificial intelligence, Computer security, Distributed computing and Deep learning.
Meikang Qiu is interested in Edge computing, which is a field of Cloud computing.
His Distributed computing research includes themes of Cloud storage, Enhanced Data Rates for GSM Evolution and General-purpose computing on graphics processing units.
His work is dedicated to discovering how Machine learning, Volume are connected with Computer network and other disciplines.
His Feature extraction research focuses on subjects like Big data, which are linked to Dynamic data and Key.
His study in Encryption is interdisciplinary in nature, drawing from both Security analysis and End user.
Between 2018 and 2021, his most popular works were:
- Privacy-Preserving Energy Trading Using Consortium Blockchain in Smart Grid (172 citations)
- Cost-Aware Multimedia Data Allocation for Heterogeneous Memory Using Genetic Algorithm in Cloud Computing (107 citations)
- Block-DEF: A secure digital evidence framework using blockchain (103 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- The Internet
His primary areas of investigation include Cloud computing, Big data, Computer security, Distributed computing and Artificial intelligence.
His research integrates issues of Sorting, Key and Task, Parallel computing in his study of Cloud computing.
His Big data research integrates issues from Knowledge-based systems, Dynamic data and Knowledge graph.
His Distributed computing research is multidisciplinary, incorporating elements of Multi access, Mobile computing, General-purpose computing on graphics processing units and Fog computing.
His research in Artificial intelligence focuses on subjects like Machine learning, which are connected to Domain, Feature extraction and Anomaly detection.
Meikang Qiu works mostly in the field of Deep learning, limiting it down to topics relating to Vehicular ad hoc network and, in certain cases, Computer network.
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