Next Article in Journal
Modeling and Optimisation of a Solar Energy Harvesting System for Wireless Sensor Network Nodes
Previous Article in Journal
Performance Analysis of Maximum Likelihood Estimation for Transmit Power Based on Signal Strength Model
Article Menu

Export Article

Open AccessArticle
J. Sens. Actuator Netw. 2018, 7(3), 39;

Adapting Probabilistic Flooding in Energy Harvesting Wireless Sensor Networks

Department of Informatics, Ionian University, 49100 Corfu, Greece
Author to whom correspondence should be addressed.
Received: 16 July 2018 / Revised: 30 August 2018 / Accepted: 31 August 2018 / Published: 6 September 2018
PDF [1585 KB, uploaded 6 September 2018]


Technological advantages in energy harvesting have been successfully applied in wireless sensor network environments, prolonging network’s lifetime, and, therefore, classical networking approaches like information dissemination need to be readdressed. More specifically, Probabilistic Flooding information dissemination is revisited in this work and it is observed that certain limitations arise due to the idiosyncrasies of nodes’ operation in energy harvesting network environments, resulting in reduced network coverage. In order to address this challenge, a modified version of Probabilistic Flooding is proposed, called Robust Probabilistic Flooding, which is capable of dealing with nodes of about to be exhausted batteries that resume their operation after ambient energy collection. In order to capture the behavior of the nodes’ operational states, a Markov chain model is also introduced and—based on certain observations and assumptions presented here—is subsequently simplified. Simulation results based on the proposed Markov chain model and a solar radiation dataset demonstrate the inefficiencies of Probabilistic Flooding and show that its enhanced version (i.e., Robust Probabilistic Flooding) is capable of fully covering the network on the expense of increased termination time in energy harvesting environments. Another advantage is that no extra overhead is introduced regarding the number of disseminated messages, thus not introducing any extra transmissions and therefore the consumed energy does not increase. View Full-Text
Keywords: wireless sensor networks; energy harvesting; Markov chain; Robust Probabilistic Flooding wireless sensor networks; energy harvesting; Markov chain; Robust Probabilistic Flooding

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Koufoudakis, G.; Oikonomou, K.; Tsoumanis, G. Adapting Probabilistic Flooding in Energy Harvesting Wireless Sensor Networks. J. Sens. Actuator Netw. 2018, 7, 39.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
J. Sens. Actuator Netw. EISSN 2224-2708 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top