A first approach was the study of Probabilistic Flooding. For the analysis, random graphs were considered and it was shown that Probabilistic Flooding creates a network of certain characteristics that allowed for using results from random graph theory concerning the performance of Probabilistic Flooding. A robust version was also studied taking into account data from the NASA Langley Research Center (LaRC) POWER Project.
Application for a sensor network for the case of historical buildings was also considered.
|||George Koufoudakis, Konstantinos Oikonomou, Georgios Tsoumanis, “Adapting Probabilistic Flooding in Energy Harvesting Wireless Sensor Networks”, In Journal of Sensor and Actuator Networks, vol. 7, no. 3, pp. 39, 2018.
|||Eleni Kavvadia, George Koufoudakis, Konstantinos Oikonomou, “Robust Probabilistic Information Dissemination in Energy Harvesting Wireless Sensor Networks”, In 2014 13th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET), pp. 63-70, 2014.
|||Konstantinos Skiadopoulos, Konstantinos Oikonomou, “Probabilistic Information Dissemination Aspects in Wireless Sensor Networks Located in Historical Buildings”, In 2014 S.M.ART.BUIL.T International Conference, 2014. ([pdf])
|||Konstantinos Oikonomou, Dimitrios Kogias, Ioannis Stavrakakis, “Probabilistic Flooding for Efficient Information Dissemination in Random Graph Topologies”, In Computer Networks, Elsevier, vol. 54, no. 10, pp. 1615-1629, 2010.
|||Konstantinos Oikonomou, Dimitrios Kogias, Leonidas Tzevelekas, Ioannis Stavrakakis, “Investigation of Information Dissemination Design Criteria in Large-Scale Network Environments”, In 2009 13th Panhellenic Conference on Informatics, pp. 163-167, 2009.
|||Konstantinos Oikonomou, Ioannis Stavrakakis, “Performance Analysis of Probabilistic Flooding Using Random Graphs”, In 2007 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, pp. 1-6, 2007.