H
Haoyu Tan
Researcher at Hong Kong University of Science and Technology
Publications - 34
Citations - 1122
Haoyu Tan is an academic researcher from Hong Kong University of Science and Technology. The author has contributed to research in topics: Communication channel & Scalability. The author has an hindex of 11, co-authored 34 publications receiving 1028 citations.
Papers
More filters
Proceedings ArticleDOI
MR-DBSCAN: An Efficient Parallel Density-Based Clustering Algorithm Using MapReduce
TL;DR: This paper proposes an efficient parallel density-based clustering algorithm and implements it by a 4-stages MapReduce paradigm and adopts a quick partitioning strategy for large scale non-indexed data.
Proceedings ArticleDOI
Finding time period-based most frequent path in big trajectory data
TL;DR: A new path finding query which finds the most frequent path (MFP) during user-specified time periods in large-scale historical trajectory data and proposes efficient search algorithms together with novel indexes to speed up the processing of TPMFP.
Journal ArticleDOI
MR-DBSCAN: a scalable MapReduce-based DBSCAN algorithm for heavily skewed data
TL;DR: MR-DBSCAN is presented, a scalable DBSCAN algorithm using MapReduce that achieves desirable load balancing even in the context of heavily skewed data and proposes a novel data partitioning method based on computation cost estimation.
Proceedings ArticleDOI
Side channel: bits over interference
TL;DR: An interesting observation that by generating intended patterns, some simultaneous transmissions can be successfully decoded without degrading the effective throughput in original transmission is observed, and a DC-MAC is proposed to leverage this "free” coordination channel for efficient medium access in a multiple-user wireless network.
Journal ArticleDOI
Chip Error Pattern Analysis in IEEE 802.15.4
TL;DR: This paper conducts a systematic analysis on errors occurring at chip level and proposes Simple Rule, a simple yet effective method based on the chip error patterns to infer the link condition with an accuracy of over 96 percent in evaluations.