What is he best known for?
The fields of study he is best known for:
- Computer network
- Artificial intelligence
- Algorithm
His primary scientific interests are in Wireless sensor network, Computer network, Distributed computing, Energy consumption and Real-time computing.
His research in Wireless sensor network intersects with topics in SQL, Geographic routing, Key distribution in wireless sensor networks, Wireless network and Bottleneck.
His Computer network research includes themes of Wireless and Edge computing.
His Distributed computing research is multidisciplinary, incorporating perspectives in Sensor node, Range query, Service and Cluster analysis.
His studies in Energy consumption integrate themes in fields like Approximation algorithm, Search engine indexing, Routing protocol and Binary space partitioning.
As a part of the same scientific study, he usually deals with the Real-time computing, concentrating on Efficient energy use and frequently concerns with Structural health monitoring.
His most cited work include:
- Rendezvous design algorithms for wireless sensor networks with a mobile base station (271 citations)
- Rendezvous Planning in Wireless Sensor Networks with Mobile Elements (177 citations)
- Dependable Structural Health Monitoring Using Wireless Sensor Networks (147 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Wireless sensor network, Computer network, Distributed computing, Real-time computing and Energy consumption.
Tian Wang interconnects Network performance, Data transmission, Key distribution in wireless sensor networks, Bottleneck and Efficient energy use in the investigation of issues within Wireless sensor network.
In his study, which falls under the umbrella issue of Computer network, Big data is strongly linked to Enhanced Data Rates for GSM Evolution.
His research in Distributed computing tackles topics such as Edge computing which are related to areas like Server.
As part of his studies on Real-time computing, Tian Wang frequently links adjacent subjects like Tracking.
His biological study spans a wide range of topics, including Transmission delay and Scheduling.
He most often published in these fields:
- Wireless sensor network (38.64%)
- Computer network (39.39%)
- Distributed computing (20.45%)
What were the highlights of his more recent work (between 2019-2021)?
- Computer network (39.39%)
- Wireless sensor network (38.64%)
- Distributed computing (20.45%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Computer network, Wireless sensor network, Distributed computing, Enhanced Data Rates for GSM Evolution and Edge computing.
His Computer network study incorporates themes from Energy consumption, Information privacy and Motion planning.
Tian Wang has included themes like Real-time computing, Server, Data transmission and Network packet in his Wireless sensor network study.
His work deals with themes such as Hidden data and Fog computing, which intersect with Real-time computing.
His studies in Distributed computing integrate themes in fields like Scheduling, Computation offloading, Resource allocation and Orchestration.
His study focuses on the intersection of Enhanced Data Rates for GSM Evolution and fields such as Big data with connections in the field of Task and Data security.
Between 2019 and 2021, his most popular works were:
- MTES: An Intelligent Trust Evaluation Scheme in Sensor-Cloud-Enabled Industrial Internet of Things (59 citations)
- Big Data Cleaning Based on Mobile Edge Computing in Industrial Sensor-Cloud (56 citations)
- A novel trust mechanism based on Fog Computing in Sensor–Cloud System (54 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Artificial intelligence
- Algorithm
Tian Wang spends much of his time researching Computer network, Energy consumption, Wireless sensor network, Enhanced Data Rates for GSM Evolution and Real-time computing.
His work on Server as part of general Computer network study is frequently linked to Credibility, therefore connecting diverse disciplines of science.
His Energy consumption research incorporates elements of Edge computing, Trajectory, Trajectory optimization and Greedy algorithm.
His Wireless sensor network study frequently intersects with other fields, such as Big data.
His work in Enhanced Data Rates for GSM Evolution tackles topics such as Distributed computing which are related to areas like Service provider, Structure, Reliability, Service and Orchestration.
His Real-time computing research is multidisciplinary, incorporating elements of Hidden data, Fog computing, Cluster analysis and Transmission.
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