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Chen-Hao Chan

dblp:184/3908 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Emerging computing paradigms · 77% Performance modeling and evaluation · 23%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Emerging computing paradigms
molecular communication
0.312017
Performance Evaluation of Leader-Follower-Based Mobile Molecular Communication Networks for Target Detection Applications · IEEE Trans. Commun. 2017
Performance modeling and evaluation › simulation
simulation-based evaluation
0.112017
Performance Evaluation of Leader-Follower-Based Mobile Molecular Communication Networks for Target Detection Applications · IEEE Trans. Commun. 2017

Methods — techniques the papers use, named apart from their topics

mathematical modeling · 0.3computer simulation · 0.3
YearPublicationVenuePosition
2017 Performance Evaluation of Leader-Follower-Based Mobile Molecular Communication Networks for Target Detection Applications
abstract
This paper proposes a leader-follower-based model of mobile molecular communication networks for target detection applications. The proposed model divides the application functionalities of molecular communication networks into two types of mobile bio-nanomachine: leader and follower bio-nanomachines. Leader bio-nanomachines distribute in the environment to detect a target and create an attractant gradient around the target. Follower bio-nanomachines move according to the attractant gradient established by leader bio-nanomachines; they approach the target and perform necessary functionalities, such as releasing drug molecules. This paper develops mathematical expressions for the proposed model, describes wet laboratory experiments designed to estimate model parameters, and performs biologically realistic computer simulation experiments to evaluate the performance of the proposed model. The main contributions of this paper are to demonstrate the functional division of molecular communication networks, which will facilitate the design and development of molecular communication networks. Furthermore, insight into the application-level performance of molecular communication networks will be provided based on the proposed model.
Tadashi Nakano, Yutaka Okaie, Shouhei Kobayashi, Takako Koujin, Chen-Hao Chan, Yu-Hsiang Hsu, Takuya Obuchi, Takahiro Hara, Yasushi Hiraoka, Tokuko Haraguchi
IEEE Trans. Commun.5