Title :
Predicting journeys for DTN routing in a public transportation system
Author :
Segundo, Fabio Rafael ; Silveira e Silva, Eraldo ; Farines, Jean-Marie
Author_Institution :
Univ. Fed. de Santa Catarina (UFSC), Florianopolis, Brazil
Abstract :
Communication in Delay/Disruption Tolerant Networks (DTNs) is a challenge because it presumes the absence of a connected end-to-end path (journey) at the time of sending a message to a destination. An efficient selection of a contact node to forward a message is a key in the routing process. Prediction techniques can be used to assist in routing decisions. In this paper we present a journey predictor for DTN based on a context of public transportation system. The journey predictor is centred on an algorithm that builds a graph of predicted journeys and then selects the best journey to a specific destination. This graph is built from a next contact predictor based on Artificial Neural Networks. Experiments were carried out with real contacts of a quasi-opportunist scenario. The proposal outperformed the MaxProp strategy in the most cases considering the number of messages delivered and the execution time.
Keywords :
computer networks; delay tolerant networks; graph theory; mobility management (mobile radio); neural nets; public transport; telecommunication network routing; traffic engineering computing; DTN routing; artificial neural networks; communication networks; contact node selection; delay tolerant networks; disruption tolerant networks; end-to-end path; intermittent connectivity; journey prediction; node mobility; public transportation system; quasi-opportunist scenario; routing decisions; store-carry-and-forward procedure; Artificial neural networks; Computational modeling; Delays; Routing;
Conference_Titel :
Wireless and Mobile Computing, Networking and Communications (WiMob), 2014 IEEE 10th International Conference on
Conference_Location :
Larnaca
DOI :
10.1109/WiMOB.2014.6962216
