What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer network
- Operating system
His primary areas of study are Computer network, Wireless sensor network, Distributed computing, Cloud computing and Quality of service. The Computer network study combines topics in areas such as Wireless network and Throughput. His Wireless sensor network research includes elements of Wireless, Particle swarm optimization, Sensor node, Key distribution in wireless sensor networks and Node.
The concepts of his Distributed computing study are interwoven with issues in The Internet, Shared mesh, Cloud communications, Traffic generation model and Dynamic network analysis. His Cloud computing research incorporates themes from Network traffic simulation, Scalability, Catastrophe theory, Dynamic priority scheduling and Workflow management system. As a part of the same scientific study, he usually deals with the Quality of service, concentrating on Resource allocation and frequently concerns with Nash equilibrium, Provisioning, Channel allocation schemes and Traffic shaping.
His most cited work include:
- A game-theoretic method of fair resource allocation for cloud computing services (360 citations)
- Steganalysis of LSB matching using differences between nonadjacent pixels (312 citations)
- VMPlanner: Optimizing virtual machine placement and traffic flow routing to reduce network power costs in cloud data centers (185 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Computer network, Distributed computing, Artificial intelligence, Wireless sensor network and Real-time computing. His research in Computer network intersects with topics in Wireless, Wireless network and Throughput. His Distributed computing research is multidisciplinary, incorporating perspectives in Overhead, Resource allocation, Quality of service, The Internet and Cloud computing.
His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning, Computer vision and Pattern recognition. His Wireless sensor network research integrates issues from Node, Key distribution in wireless sensor networks, Algorithm and Cluster analysis. His study of Mobile wireless sensor network is a part of Key distribution in wireless sensor networks.
He most often published in these fields:
- Computer network (28.38%)
- Distributed computing (21.18%)
- Artificial intelligence (18.56%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (18.56%)
- Algorithm (8.95%)
- Deep learning (4.59%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Algorithm, Deep learning, Big data and Computer security. His Artificial intelligence study deals with Pattern recognition intersecting with Cluster analysis. His work deals with themes such as Data modeling, Overhead, Distributed computing and Speedup, which intersect with Big data.
His research on Overhead also deals with topics like
- Correctness most often made with reference to Set,
- Verifiable secret sharing that intertwine with fields like Computer network. His research in Computer network is mostly focused on Wireless sensor network. Naixue Xiong combines subjects such as Wireless and Reinforcement learning with his study of Distributed computing.
Between 2019 and 2021, his most popular works were:
- BD-VTE: A Novel Baseline Data based Verifiable Trust Evaluation Scheme for Smart Network Systems (26 citations)
- KNN-BLOCK DBSCAN: Fast Clustering for Large-Scale Data (17 citations)
- An Effective Early Message Ahead Join Adaptive Data Aggregation Scheme for Sustainable IoT (12 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer network
- Operating system
His main research concerns Computer network, Artificial intelligence, Big data, Deep learning and Verifiable secret sharing. Many of his studies on Computer network apply to Wireless as well. His study in the field of Semi-supervised learning, k-nearest neighbors algorithm and Cluster analysis is also linked to topics like Crop yield.
His Verifiable secret sharing research is multidisciplinary, relying on both Overhead, Distributed computing, Correctness, Set and Encryption. His studies deal with areas such as Swarm intelligence, Interconnection and Robustness as well as Distributed computing. Naixue Xiong has included themes like Authentication scheme and Resilience in his Wireless sensor network study.
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