In traditional schemes, obtaining a robust topology requires high connectivity. We chose random undirected and directed network topologies for comparison to showcase the

advantages of entropy and connectivity.

DOI Link: 
10.21227/2012-yf19
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[1] yan sun, "Dataset for Extremality: Degree-based Entropy of Underlying Digraph for Internet of Things", IEEE Dataport, 2023. [Online]. Available: http://dx.doi.org/10.21227/2012-yf19. Accessed: Jan. 28, 2025.
@data{2012-yf19-23,
doi = {10.21227/2012-yf19},
url = {http://dx.doi.org/10.21227/2012-yf19},
author = {yan sun },
publisher = {IEEE Dataport},
title = {Dataset for Extremality: Degree-based Entropy of Underlying Digraph for Internet of Things},
year = {2023} }
TY - DATA
T1 - Dataset for Extremality: Degree-based Entropy of Underlying Digraph for Internet of Things
AU - yan sun
PY - 2023
PB - IEEE Dataport
UR - 10.21227/2012-yf19
ER -
yan sun. (2023). Dataset for Extremality: Degree-based Entropy of Underlying Digraph for Internet of Things. IEEE Dataport. http://dx.doi.org/10.21227/2012-yf19
yan sun, 2023. Dataset for Extremality: Degree-based Entropy of Underlying Digraph for Internet of Things. Available at: http://dx.doi.org/10.21227/2012-yf19.
yan sun. (2023). "Dataset for Extremality: Degree-based Entropy of Underlying Digraph for Internet of Things." Web.
1. yan sun. Dataset for Extremality: Degree-based Entropy of Underlying Digraph for Internet of Things [Internet]. IEEE Dataport; 2023. Available from : http://dx.doi.org/10.21227/2012-yf19
yan sun. "Dataset for Extremality: Degree-based Entropy of Underlying Digraph for Internet of Things." doi: 10.21227/2012-yf19