S
Shan Lin
Researcher at Stony Brook University
Publications - 112
Citations - 3824
Shan Lin is an academic researcher from Stony Brook University. The author has contributed to research in topics: Wireless sensor network & Network packet. The author has an hindex of 26, co-authored 104 publications receiving 3471 citations. Previous affiliations of Shan Lin include University of Virginia & Nanjing University.
Papers
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Proceedings ArticleDOI
ATPC: adaptive transmission power control for wireless sensor networks
TL;DR: ATPC is presented, a lightweight algorithm of Adaptive Transmission Power Control for wireless sensor networks that employs a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time and is robust even with environmental changes over time.
Proceedings ArticleDOI
Realistic and Efficient Multi-Channel Communications in Wireless Sensor Networks
TL;DR: A novel tree-based multichannel scheme for data collection applications, which allocates channels to disjoint trees and exploits parallel transmissions among trees and outperforms other schemes in dense networks with a small number of channels is proposed.
ALARM-NET: Wireless Sensor Networks for Assisted-Living and Residential Monitoring
Anthony D. Wood,G. Virone,T. Doan,Qiuhua Cao,Leo Selavo,Yafeng Wu,Lei Fang,Zhimin He,Shan Lin,John A. Stankovic +9 more
TL;DR: The correctness, robustness, and extensibility of the system architecture is shown through a scenario-based evaluation of the integrated ALARM-NET system, as well as performance data for individual software components.
Journal ArticleDOI
ATPC: Adaptive Transmission Power Control for Wireless Sensor Networks
Shan Lin,Fei Miao,Jingbin Zhang,Gang Zhou,Lin Gu,Tian He,John A. Stankovic,Sang H. Son,George J. Pappas +8 more
TL;DR: ATPC is presented, a lightweight algorithm for Adaptive Transmission Power Control in wireless sensor networks that employs a feedback-based transmission power control algorithm to dynamically maintain individual link quality over time and is robust even with environmental changes over time.
Journal ArticleDOI
Taxi Dispatch With Real-Time Sensing Data in Metropolitan Areas: A Receding Horizon Control Approach
Fei Miao,Shuo Han,Shan Lin,John A. Stankovic,Desheng Zhang,Sirajum Munir,Hua Huang,Tian He,George J. Pappas +8 more
TL;DR: A receding horizon control (RHC) framework to dispatch taxis is presented, which incorporates highly spatiotemporally correlated demand/supply models and real-time Global Positioning System location and occupancy information and is compatible with a wide variety of predictive models and optimization problem formulations.