Probabilistic Flooding and Largest Eigenvalue/Principal Eigenvector

Probabilistic flooding was also studied borrowing tools from algebraic graph theory.

Coverage as a function of the forwarding probability q for various Geometric Random Graphs (GRG: rc = 0.3, 0.4, 0.5) and Erdos-Renyi (ER: p = 0.2, 0.3, 0.4) topologies. The particular values of 4/d , 4/λ1 , 1/d and 1/λ1 are also depicted. Apparently, for q>4/λ1 full coverage is a achieved Under probabilistic Flooding, while for q<1/λ1 coverage is negligible.


[5] Konstantinos Oikonomou, George Koufoudakis, Sonia Aïssa, Ioannis Stavrakakis, “Probabilistic Flooding Performance Analysis Exploiting Graph Spectra Properties”, In IEEE/ACM Transactions on Networking, 2022.
[4] Andreana Stylidou, Alexandros Zervopoulos, Aikaterini Georgia Alvanou, George Koufoudakis, Georgios Tsoumanis, Konstantinos Oikonomou, “Evaluation of Epidemic-Based Information Dissemination in a Wireless Network Testbed”, In Technologies, vol. 8, no. 3, 2020.
[3] George Koufoudakis, Konstantinos Oikonomou, Sonia Aïssa, Ioannis Stavrakakis, “Analysis of Spectral Properties for Efficient Coverage Under Probabilistic Flooding”, In 2018 IEEE 19th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM) (IEEE WoWMoM 2018), Chania, Crete, Greece, pp. 1-9, 2018.
[2] George Koufoudakis, Konstantinos Oikonomou, Konstantinos Giannakis, Sonia Aïssa, “Probabilistic Flooding Coverage Analysis for Efficient Information Dissemination in Wireless Networks”, In Computer Networks, vol. 140, pp. 51 – 61, 2018.
[1] Konstantinos Oikonomou, George Koufoudakis, Sonia Aïssa, “Probabilistic Flooding Coverage Analysis in Large Scale Wireless Networks”, In 2012 19th International Conference on Telecommunications (ICT), pp. 1-6, 2012.