Tracking Topology Dynamicity for Link Prediction in Intermittently Connected Wireless Networks
| Autor: | Vincent Gauthier, Mohamed-Haykel Zayani, Ines Slama, Djamal Zeghlache |
|---|---|
| Přispěvatelé: | Zayani, Mohamed-Haykel, Département Réseaux et Services Multimédia Mobiles (RS2M), Institut Mines-Télécom [Paris] (IMT)-Télécom SudParis (TSP), Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux (SAMOVAR), Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: |
Networking and Internet Architecture (cs.NI)
FOS: Computer and information sciences Similarity (geometry) [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI] Wireless network Computer science business.industry Distributed computing 020206 networking & telecommunications Topology (electrical circuits) 02 engineering and technology Computer Science - Networking and Internet Architecture [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI] 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Communications protocol business Link (knot theory) Computer network |
| Zdroj: | IWCMC |
| Popis: | Through several studies, it has been highlighted that mobility patterns in mobile networks are driven by human behaviors. This effect has been particularly observed in intermittently connected networks like DTN (Delay Tolerant Networks). Given that common social intentions generate similar human behavior, it is relevant to exploit this knowledge in the network protocols design, e.g. to identify the closeness degree between two nodes. In this paper, we propose a temporal link prediction technique for DTN which quantifies the behavior similarity between each pair of nodes and makes use of it to predict future links. We attest that the tensor-based technique is effective for temporal link prediction applied to the intermittently connected networks. The validity of this method is proved when the prediction is made in a distributed way (i.e. with local information) and its performance is compared to well-known link prediction metrics proposed in the literature. Comment: Published in the proceedings of the 8th International Wireless Communications and Mobile Computing Conference (IWCMC), Limassol, Cyprus, 2012 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|