Probabilistic Flooding Coverage Analysis for Efficient Information Dissemination in Wireless Networks (bibtex)
by George Koufoudakis, Konstantinos Oikonomou, Konstantinos Giannakis, Sonia Aïssa
Abstract:
Abstract Information dissemination under Probabilistic flooding is revisited here in an attempt to realize full coverage in modern wireless networks and at the same time avoid unnecessary transmissions that waste valuable resources. Approaches like traditional flooding, are not suitable in these typically large scale and inherently dynamic environments due to the large number of transmitted information messages. Probabilistic flooding is capable of pruning unnecessary transmissions, while maintaining a large proportion of the network nodes covered. In this paper, an algebraic-based approach is employed to derive an estimation regarding the particular threshold probability value that would allow for high network coverage and reduced number of sent information messages. For the analysis' purposes, coverage is studied here and eventually modeled as a polynomial; its higher root being related to the threshold probability. By studying this polynomial's roots, the paper's contribution is twofold: (i) results existing in the open literature are confirmed; and (ii) an algorithm is introduced here to estimate the threshold probability. Simulation results confirm the analytical findings and in addition, they demonstrate that the estimated value derived here regarding threshold probability, is suitable for achieving high coverage and reducing the number of transmitted information messages.
Reference:
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.
Bibtex Entry:
@article{koufoudakis2018probabilistic,
	Abstract = {Abstract Information dissemination under Probabilistic flooding is revisited here in an attempt to realize full coverage in modern wireless networks and at the same time avoid unnecessary transmissions that waste valuable resources. Approaches like traditional flooding, are not suitable in these typically large scale and inherently dynamic environments due to the large number of transmitted information messages. Probabilistic flooding is capable of pruning unnecessary transmissions, while maintaining a large proportion of the network nodes covered. In this paper, an algebraic-based approach is employed to derive an estimation regarding the particular threshold probability value that would allow for high network coverage and reduced number of sent information messages. For the analysis' purposes, coverage is studied here and eventually modeled as a polynomial; its higher root being related to the threshold probability. By studying this polynomial's roots, the paper's contribution is twofold: (i) results existing in the open literature are confirmed; and (ii) an algorithm is introduced here to estimate the threshold probability. Simulation results confirm the analytical findings and in addition, they demonstrate that the estimated value derived here regarding threshold probability, is suitable for achieving high coverage and reducing the number of transmitted information messages.},
	Author = {Koufoudakis, George and Oikonomou, Konstantinos and Giannakis, Konstantinos and A{\"i}ssa, Sonia},
	Doi = {10.1016/j.comnet.2018.05.005},
	Issn = {1389-1286},
	Journal = {Computer Networks},
	Keywords = {own, sonia, refereed, exceptional, olinet},
	Pages = {51 - 61},
	Title = {{{Probabilistic Flooding Coverage Analysis for Efficient Information Dissemination in Wireless Networks}}},
	Volume = {140},
	Year = {2018},
	Bdsk-Url-1 = {https://doi.org/10.1016/j.comnet.2018.05.005}}
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