by George Koufoudakis, Konstantinos Oikonomou, Sonia Aïssa, Ioannis Stavrakakis
Abstract:
Information dissemination plays a crucial role in modern network environments being an integral part of various vital processes (e.g., service discovery, data collection, routing). Probabilistic flooding has been proposed as a suitable alternative to blind flooding in order to reduce unnecessary transmissions and save valuable network resources. Under probabilistic flooding, an information message, initially located at some network node (i.e., the initiator node), is transmitted to neighbor nodes according to a forwarding probability attempting to reach all network nodes. This paper employs elements from algebraic graph theory to model probabilistic flooding behavior and derive analytical results regarding coverage (i.e., the number of nodes that have received the information message) and a lower bound of the forwarding probability allowing for global network outreach. It is also shown here, that for any value of the forwarding probability larger than this lower bound, (i) coverage under probabilistic flooding, is proportional to the initiator's node eigenvector centrality; and (ii) the probability for a node to receive the information message is proportional to the particular node's eigenvector centrality. Simulations performed for various topologies demonstrate the effectiveness of the proposed analytical model and support the analytical results.
Reference:
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.
Bibtex Entry:
@inproceedings{koufoudakis2018analysis,
abstract = {Information dissemination plays a crucial role in modern network
environments being an integral part of various vital processes (e.g.,
service discovery, data collection, routing). Probabilistic flooding has
been proposed as a suitable alternative to blind flooding in order to
reduce unnecessary transmissions and save valuable network resources. Under
probabilistic flooding, an information message, initially located at some
network node (i.e., the initiator node), is transmitted to neighbor nodes
according to a forwarding probability attempting to reach all network
nodes. This paper employs elements from algebraic graph theory to model
probabilistic flooding behavior and derive analytical results regarding
coverage (i.e., the number of nodes that have received the information
message) and a lower bound of the forwarding probability allowing for
global network outreach. It is also shown here, that for any value of the
forwarding probability larger than this lower bound, (i) coverage under
probabilistic flooding, is proportional to the initiator's node eigenvector
centrality; and (ii) the probability for a node to receive the information
message is proportional to the particular node's eigenvector centrality.
Simulations performed for various topologies demonstrate the effectiveness
of the proposed analytical model and support the analytical results.},
address = {Chania, Crete, Greece},
author = {Koufoudakis, George and Oikonomou, Konstantinos and A{\"i}ssa, Sonia and Stavrakakis, Ioannis},
booktitle = {2018 IEEE 19th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM) (IEEE WoWMoM 2018)},
date-modified = {2022-05-04 11:45:16 +0300},
doi = {10.1109/WoWMoM.2018.8449800},
keywords = {own, sonia, exceptional, refereed, olinet, R:ID:LE,R:SA},
month = {6},
pages = {1-9},
title = {{{Analysis of Spectral Properties for Efficient Coverage Under Probabilistic Flooding}}},
year = {2018},
Bdsk-Url-1 = {https://doi.org/10.1109/WoWMoM.2018.8449800}}