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Xiaoyan Hong
Researcher at University of Alabama
Publications - 149
Citations - 6826
Xiaoyan Hong is an academic researcher from University of Alabama. The author has contributed to research in topics: Wireless ad hoc network & Optimized Link State Routing Protocol. The author has an hindex of 33, co-authored 149 publications receiving 6650 citations. Previous affiliations of Xiaoyan Hong include University of California & Rice University.
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Proceedings ArticleDOI
Hybrid landmark routing in ad hoc networks with heterogeneous group mobility
TL;DR: This paper proposes a hybrid landmark routing (hybrid LANMAR) scheme which takes advantages of group mobility to improve network scalability, while at the same time supporting individual mobility efficiently, and results show that hybrid LANMAR can greatly improvenetwork scalability in heterogeneous motion scenarios.
Proceedings ArticleDOI
Delay analysis of Wireless Ad Hoc networks: Single vs. multiple radio
TL;DR: An experimental methodology to obtain an estimate of average intra-node delay and inter- node delay for packets of variable payload size in both single radio and multi-radio environment without the constraint of clock synchronization between the nodes is presented.
Proceedings ArticleDOI
BioStaR: A Bio-inspired Stable Routing for Cognitive Radio Networks
Mohammad A. Hoque,Xiaoyan Hong +1 more
TL;DR: This work includes designing a routing protocol named Bio-inspired Stable Routing (BioStaR) that increases route stability by maximizing the Spectrum Opportunity (SOP) and also minimizes the channel switching delay and signaling overhead.
Proceedings ArticleDOI
Experimental evaluation of LANMAR, a scalable ad-hoc routing protocol
TL;DR: The implementation of LANMAR, a scalable routing protocol that was developed at UCLA as part of large-scale ad hoc network architecture for autonomous unattended agents under ONR support, is described and the results and lessons learned are described.
Journal ArticleDOI
A distributed framework for network-wide traffic monitoring and platoon information aggregation using V2V communications
TL;DR: As expected, the accuracy of both speed and density estimation increases with MPR for any given traffic scenario, and the density estimation is more sensitive to MPR, and is more accurate under low demand and high MPR scenarios.