An improved stochastic modeling of opportunistic routing in vehicular CPS

Zeng, Deze, Guo, Song, Barnawi, Ahmed, Yu, Shui and Stojmenovic, Ivan 2015, An improved stochastic modeling of opportunistic routing in vehicular CPS, IEEE transactions on computers, vol. 64, no. 7, pp. 1819-1829, doi: 10.1109/TC.2014.2349509.

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Title An improved stochastic modeling of opportunistic routing in vehicular CPS
Author(s) Zeng, Deze
Guo, Song
Barnawi, Ahmed
Yu, ShuiORCID iD for Yu, Shui
Stojmenovic, Ivan
Journal name IEEE transactions on computers
Volume number 64
Issue number 7
Start page 1819
End page 1829
Total pages 11
Publisher IEEE
Place of publication Piscataway, N.J.
Publication date 2015-07-01
ISSN 0018-9340
Keyword(s) Science & Technology
Computer Science, Hardware & Architecture
Engineering, Electrical & Electronic
Computer Science
Vehicular cyber-physical system
epidemic routing
random linear network coding
stochastic analysis
Summary Vehicular Cyber-Physical System (VCPS) provides CPS services via exploring the sensing, computing and communication capabilities on vehicles. VCPS is deeply influenced by the performance of the underlying vehicular network with intermittent connections, which make existing routing solutions hardly to be applied directly. Epidemic routing, especially the one using random linear network coding, has been studied and proved as an efficient way in the consideration of delivery performance. Much pioneering work has tried to figure out how epidemic routing using network coding (ERNC) performs in VCPS, either by simulation or by analysis. However, none of them has been able to expose the potential of ERNC accurately. In this paper, we present a stochastic analytical framework to study the performance of ERNC in VCPS with intermittent connections. By novelly modeling ERNC in VCPS using a token-bucket model, our framework can provide a much more accurate results than any existing work on the unicast delivery performance analysis of ERNC in VCPS. The correctness of our analytical results has also been confirmed by our extensive simulations.
Language eng
DOI 10.1109/TC.2014.2349509
Field of Research 080109 Pattern Recognition and Data Mining
0803 Computer Software
0805 Distributed Computing
1006 Computer Hardware
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, IEEE
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