W
Wai-Choong Wong
Researcher at National University of Singapore
Publications - 254
Citations - 3816
Wai-Choong Wong is an academic researcher from National University of Singapore. The author has contributed to research in topics: Network packet & Throughput. The author has an hindex of 29, co-authored 254 publications receiving 3580 citations. Previous affiliations of Wai-Choong Wong include Institute for Infocomm Research Singapore & Bell Labs.
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Journal ArticleDOI
Rate-Distortion-Authentication Optimized Streaming of Authenticated Video
TL;DR: This paper proposes an Rate-Distortion-Authentication (R-D-A) optimized streaming technique for authenticated video that substantially outperforms both prior (authentication-unaware) R-D optimized streaming techniques and data stream authentication techniques.
Proceedings ArticleDOI
Packet reservation multiple access in a metropolitan microcellular radio environment
TL;DR: The author examines the performance of a packet reservation multiple access (PRMA) protocol in a metropolitan microcellular radio environment using computer simulations and performance comparisons with other protocols are carried out.
Journal ArticleDOI
An Analysis Framework for Interuser Interference in IEEE 802.15.6 Body Sensor Networks: A Stochastic Geometry Approach
TL;DR: An extended Matern point process is proposed to model the complex spatial distribution of the interfering BSNs caused by the hybrid MAC defined in IEEE 802.15.6.
Proceedings ArticleDOI
An Optimized Content-Aware Authentication Scheme for Streaming JPEG-2000 Images Over Lossy Networks
TL;DR: An optimized content-aware authentication scheme for JPEG-2000 streams over lossy networks, where a received packet is consumed only when it is both decodable and authenticated, achieves its design goal in that the rate-distortion curve of the authenticated image is very close to the R-D curve when no authentication is required.
Proceedings ArticleDOI
Access point placement for fingerprint-based localization
TL;DR: A novel method for placing the APs is proposed, which aims to minimize the total number of similar fingerprints (SFs) over the entire array of training locations, which will increase the diversity of RSS array and hence improve localization accuracy.