Opportunistic: Routing Distribution, Broadcasts, Transmissions and Receptions in an Opportunistic Network
This repository contains the Opportunistic R package, which provides user-friendly functions to access the methods proposed in the research work titled “A novel theoretical probabilistic model for opportunistic routing with applications in energy consumption for WSNs” by Galarza et al. (2021) [1].
To use the Opportunistic R package, you need to have R software installed on your system. If you don’t have it, you can download it from the R project website. Alternatively, you can compile R online using platforms such as RStudio cloud or Google Colab.
Once you have R installed, you can install the Opportunistic package by running the following code in the R console:
# Install from CRAN
library(Opportunistic)
# Or the development version from GitHub
# install.packages("devtools")
devtools::install_github("chedgala/Opportunistic")After installing the package, you can load it using the following command:
library(Opportunistic)The package provides three main functions:
-
routes(p, delta): This function returns the different possible routes, their frequency, and their respective probabilities when considering uncertain probabilities lying on the intervalp ± delta. It is based on the theoretical framework developed in the research work. -
Expected(p): This function calculates the probability of successful transmissions and the expected number of transmissions, receptions, and broadcasts for the given vector of probabilitiesp. -
MonteCarlo(p, M): This function estimates the probability of successful transmissions, as well as the expected number of transmissions, receptions, and broadcasts using Monte Carlo simulations. The parameterMspecifies the number of simulations to perform.
For more information on the usage and capabilities of the Opportunistic R package, please refer to the package documentation and the original research work [1].
This section shows how to access the methods proposed in this work through available user functions.
library(Opportunistic)
#An N=5 Opportunistic system with probabilities
> p <- c(0.85, 0.72, 0.50, 0.28, 0.05)
> routes(p) # routes distribution
Freq Probability Value
route 1 1 p1^5 0.44371
route 2 4 p1^3*p2 0.44217
route 3 3 p1*p2^2 0.44064
route 4 3 p1^2*p3 0.36125
route 5 2 p2*p3 0.36
route 6 2 p1*p4 0.238
route 7 1 p5 0.05
Total 16#An N=5 Opportunistic system with probabilities
> p <- c(0.85, 0.72, 0.50, 0.28, 0.05)
> True = Expected(p)
###########################################
Opportunistic Model - Theoretical results
###########################################
Number of Hops N: 5
Probabilities: 0.85, 0.72, 0.5, 0.28, 0.05
1 2 3 4 5
Success Probability 0.85 0.922 0.958 0.974 0.979
Exp Transmissions 1.00 2.850 6.143 11.773 21.135
Exp Receptions 0.85 2.293 4.631 8.362 14.226
Exp Broadcast 1.00 1.850 3.293 5.631 9.362#An N=5 Opportunistic system with probabilities
> p <- c(0.85, 0.72, 0.50, 0.28, 0.05)
> Estimated = MonteCarlo(p,M=10^6)
###########################################
Opportunistic Model - Monte Carlo results
###########################################
Number of Hops N: 5
Probabilities: 0.85, 0.72, 0.5, 0.28, 0.05
Simulations M: 1e+06
|===========================================| 100%
Monte Carlo
Probability System 0.979
Exp Transmissions 21.129
Exp Receptions 14.220
Exp Broadcast 9.358The Opportunistic R package was developed by Christian E. Galarza (maintainer) and Jonathan M. Palma.
Contributions to the software are welcome. If you find a bug or have an idea for an enhancement, please open an issue or submit a pull request.
If you have any questions, feel free to open an issue or send an email to the repository owner.
This software is open source under the MIT License. Please see the LICENSE file for more information.
[1] Galarza, C. E., Palma, J. M., Morais, C. F., Utria, J., Carvalho, L. P., Bustos, D., & Oliveira, R. C. (2021). A novel theoretical probabilistic model for opportunistic routing with applications in energy consumption for WSNs. Sensors, 21(23), 8058.