The scientist’s investigation covers issues in Computer network, Wireless, Cognitive radio, Wireless network and Communication channel. His Computer network research is multidisciplinary, relying on both Telecommunications and Throughput. Ping Wang has included themes like Network architecture, Electric power, Wireless sensor network and Transmission in his Wireless study.
The concepts of his Cognitive radio study are interwoven with issues in Transmitter, Energy harvesting, Energy and Common value auction. His work carried out in the field of Wireless network brings together such families of science as Relay and Transmitter power output. His Mobile computing research integrates issues from Cloudlet and Mobile telephony.
His main research concerns Computer network, Wireless, Wireless network, Service provider and Cognitive radio. His Computer network research includes elements of Throughput and Communication channel. His work in Wireless addresses issues such as Electronic engineering, which are connected to fields such as Transmission.
His Service provider research incorporates themes from Stackelberg competition, Incentive, Computer security and Operations research. Ping Wang has researched Cognitive radio in several fields, including Scheduling and Mathematical optimization. His work in Wireless sensor network covers topics such as Key distribution in wireless sensor networks which are related to areas like Wi-Fi array.
His primary scientific interests are in Incentive, Stackelberg competition, Vibration, Wireless and Service provider. His work in Stackelberg competition addresses subjects such as Backward induction, which are connected to disciplines such as Social network. His Vibration study combines topics from a wide range of disciplines, such as Frequency response, Energy harvesting and Automotive engineering.
Ping Wang combines subjects such as Relay, Electronic engineering, Computer network and Task with his study of Wireless. His studies in Computer network integrate themes in fields like Service delivery framework and Game theory. His studies deal with areas such as Profit and Artificial intelligence as well as Service provider.
Ping Wang spends much of his time researching Vibration, Random vibration, Systems architecture, Edge computing and Rationality. The Random vibration study combines topics in areas such as Generator, Mechanical engineering and Electric power. His Edge computing research is multidisciplinary, incorporating perspectives in Edge device, Backward induction and Distributed computing.
His Distributed computing study integrates concerns from other disciplines, such as Service, Enhanced Data Rates for GSM Evolution, Hash function, Resource and Protocol. Among his Rationality studies, you can observe a synthesis of other disciplines of science such as Wireless, Reinforcement learning, Data science, Federated learning and Social Welfare. His work is dedicated to discovering how Wireless, Incentive compatibility are connected with Profit and other disciplines.
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.
A survey of mobile cloud computing: architecture, applications, and approaches
Hoang T. Dinh;Chonho Lee;Dusit Niyato;Ping Wang.
Wireless Communications and Mobile Computing (2013)
Wireless Networks With RF Energy Harvesting: A Contemporary Survey
Xiao Lu;Ping Wang;Dusit Niyato;Dong In Kim.
IEEE Communications Surveys and Tutorials (2015)
Wireless Charging Technologies: Fundamentals, Standards, and Network Applications
Xiao Lu;Ping Wang;Dusit Niyato;Dong In Kim.
IEEE Communications Surveys and Tutorials (2016)
Machine-to-machine communications for home energy management system in smart grid
Dusit Niyato;Lu Xiao;Ping Wang.
IEEE Communications Magazine (2011)
A Dynamic Offloading Algorithm for Mobile Computing
Dong Huang;Ping Wang;D. Niyato.
IEEE Transactions on Wireless Communications (2012)
A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks
Wenbo Wang;Dinh Thai Hoang;Peizhao Hu;Zehui Xiong.
IEEE Access (2019)
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Nguyen Cong Luong;Dinh Thai Hoang;Shimin Gong;Dusit Niyato.
IEEE Communications Surveys and Tutorials (2019)
Applications, Architectures, and Protocol Design Issues for Mobile Social Networks: A Survey
Nipendra Kayastha;Dusit Niyato;Ping Wang;Ekram Hossain.
Proceedings of the IEEE (2011)
Ambient Backscatter Communications: A Contemporary Survey
Nguyen Van Huynh;Dinh Thai Hoang;Xiao Lu;Dusit Niyato.
IEEE Communications Surveys and Tutorials (2018)
When Mobile Blockchain Meets Edge Computing
Zehui Xiong;Yang Zhang;Dusit Niyato;Ping Wang.
IEEE Communications Magazine (2018)
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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