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Ying Chen 0008

dblp:21/5521-8 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0002-7769-216XORCID · verified

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

Computer networks · 1 · 1 first-author · 1 since 2021

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 networks
1 paper
Wireless networking · 56% Cellular and mobile networks · 44%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Cellular and mobile networks › device-to-device communication
device-to-device networks
0.512021
On the Capacity of Fractal D2D Social Networks with Hierarchical Communications · IEEE Trans. Mob. Comput. 2021
Wireless networking
network capacity
0.512021
On the Capacity of Fractal D2D Social Networks with Hierarchical Communications · IEEE Trans. Mob. Comput. 2021

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

asymptotic analysis · 0.5
YearPublicationVenuePosition
2021 On the Capacity of Fractal D2D Social Networks with Hierarchical Communications
abstract
The maximum capacity of fractal D2D (device-to-device) social networks with both direct and hierarchical communications is studied in this paper. Specifically, the fractal networks are characterized by the direct social connection and the self-similarity. First, for a fractal D2D social network with direct social communications, it is proved that the maximum capacity is$ \Theta (\frac{1}{\sqrt{n\,\log n}})$if a user communicates with one of his/her direct contacts randomly, where$ n$denotes the total number of users in the network, and it can reach up to$ \Theta (\frac{1}{\log n})$if any pair of social contacts with distance$ d$communicate according to the probability in proportion to$ d^{-\beta }$. Second, since users might get in touch with others without direct social connections through the inter-connected multiple users, the fractal D2D social network with these hierarchical communications is studied as well, and the related capacity is further derived. Our results show that this capacity is mainly affected by the correlation exponent$\epsilon$of the fractal structure. The capacity is reduced in proportional to$ \frac{1}{{\log n}}$if$ 2<\epsilon <3$, while the reduction coefficient is$ \frac{1}{n}$if$ \epsilon >3$.
Ying Chen 0008, Rongpeng Li, Zhifeng Zhao, Honggang Zhang 0001
IEEE Trans. Mob. Comput.1