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Lee, Kyunghan
Mobile Systems and Networking Lab. (MSN)
Research Interests
  • Low-latency network, cloud computing, 5G network, mobile machine learning

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On Stochastic Confidence of Information Spread in Opportunistic Networks

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Title
On Stochastic Confidence of Information Spread in Opportunistic Networks
Author
Kim, YooraLee, KyunghanShroff, Ness B.
Issue Date
2016-04
Publisher
IEEE COMPUTER SOC
Citation
IEEE TRANSACTIONS ON MOBILE COMPUTING, v.15, no.4, pp.909 - 923
Abstract
Predicting spreading patterns of information or virus has been a popular research topic for which various mathematical tools have been developed. These tools have mainly focused on estimating the average time of spread to a fraction (e.g.,α) of the agents, i.e., so-called average -completion time E(T). We claim that understanding stochastic confidence on the time T rather than only its average gives more comprehensive knowledge on the spread behavior and wider engineering choices. Obviously, the knowledge also enables us to effectively accelerate or decelerate a spread. To demonstrate the benefits of understanding the distribution of spread time, we introduce a new metric G, that denotes the time required to guarantee completion (i.e., penetration) with probability . Also, we develop a new framework characterizing G, for various spread parameters such as number of seeders, contact rates between agents, and heterogeneity in contact rates. We apply our technique to a large-scale experimental vehicular trace and show that it is possible to allocate resources for acceleration of spread in a far more elaborated way compared to conventional average-based mathematical tools.
URI
https://scholarworks.unist.ac.kr/handle/201301/17081
URL
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7105373
DOI
10.1109/TMC.2015.2431711
ISSN
1536-1233
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