Geyong Min mainly investigates Distributed computing, Computer network, Server, Edge computing and Big data. His studies in Distributed computing integrate themes in fields like Network performance, Resource allocation, Quality of service, Scheduling and Cloud computing. The study incorporates disciplines such as Key management and Computer security, Data integrity, Computer security model in addition to Cloud computing.
Many of his studies on Computer network involve topics that are commonly interrelated, such as Wi-Fi. Geyong Min combines subjects such as Computation offloading, Edge device, Networking hardware and Reinforcement learning with his study of Server. Geyong Min has researched Edge computing in several fields, including Data modeling, Scalability, Task analysis and Upload.
His primary areas of study are Computer network, Distributed computing, Quality of service, Wireless and Real-time computing. In his study, Local area network is inextricably linked to Throughput, which falls within the broad field of Computer network. His Distributed computing study incorporates themes from Network performance, Queueing theory, Server, Scheduling and Interconnection.
His studies examine the connections between Queueing theory and genetics, as well as such issues in Queue, with regards to Packet loss. His Server research integrates issues from Scalability and Edge computing. The concepts of his Quality of service study are interwoven with issues in Network congestion, Resource allocation, Frame, Telecommunications network and Provisioning.
His primary areas of investigation include Distributed computing, Computer network, Server, Edge computing and Wireless. His research in Distributed computing intersects with topics in Energy consumption, Quality of service, Network topology, Cloud computing and Reinforcement learning. His work in Quality of service covers topics such as Resource allocation which are related to areas like Service.
His work deals with themes such as Efficient energy use and Vehicular ad hoc network, which intersect with Computer network. His study in Server is interdisciplinary in nature, drawing from both Network architecture, Scalability, Virtual network and Latency. His studies in Edge computing integrate themes in fields like Data modeling and Edge device.
His primary scientific interests are in Distributed computing, Server, Computer network, Edge computing and Cloud computing. Geyong Min has included themes like Energy consumption, Quality of service, The Internet, Scheduling and Reinforcement learning in his Distributed computing study. His research in Quality of service tackles topics such as Resource allocation which are related to areas like Communication channel.
He combines subjects such as Scalability, Throughput and Networking hardware with his study of Server. His Computer network study frequently draws connections between adjacent fields such as Vehicular ad hoc network. The Edge computing study combines topics in areas such as Wireless, Task analysis, Data modeling and Upload.
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.
Identity-Based Remote Data Integrity Checking With Perfect Data Privacy Preserving for Cloud Storage
Yong Yu;Man Ho Au;Giuseppe Ateniese;Xinyi Huang.
IEEE Transactions on Information Forensics and Security (2017)
Advanced internet of things for personalised healthcare systems
Jun Qi;Po Yang;Geyong Min;Oliver Amft.
High Performance Computing for Cyber Physical Social Systems by Using Evolutionary Multi-Objective Optimization Algorithm
Gai-Ge Wang;Xingjuan Cai;Zhihua Cui;Geyong Min.
IEEE Transactions on Emerging Topics in Computing (2020)
Fuzzy Identity-Based Data Integrity Auditing for Reliable Cloud Storage Systems
Yannan Li;Yong Yu;Geyong Min;Willy Susilo.
IEEE Transactions on Dependable and Secure Computing (2019)
Enabling Collaborative Edge Computing for Software Defined Vehicular Networks
Kai Wang;Hao Yin;Wei Quan;Geyong Min.
IEEE Network (2018)
A Tensor-Based Approach for Big Data Representation and Dimensionality Reduction
Liwei Kuang;Fei Hao;Laurence T. Yang;Man Lin.
IEEE Transactions on Emerging Topics in Computing (2014)
Minimizing Movement for Target Coverage and Network Connectivity in Mobile Sensor Networks
Zhuofan Liao;Jianxin Wang;Shigeng Zhang;Jiannong Cao.
IEEE Transactions on Parallel and Distributed Systems (2015)
A Framework of Fog Computing: Architecture, Challenges, and Optimization
Yang Liu;Jonathan E. Fieldsend;Geyong Min.
IEEE Access (2017)
Energy-aware scheduling of virtual machines in heterogeneous cloud computing systems
Hancong Duan;Chao Chen;Geyong Min;Yu Wu.
Future Generation Computer Systems (2017)
An Intelligent Information Forwarder for Healthcare Big Data Systems With Distributed Wearable Sensors
Ping Jiang;Jonathan Winkley;Can Zhao;Robert Munnoch.
IEEE Systems Journal (2016)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: