Tracking Topology Dynamicity for Link Prediction in Intermittently Connected Wireless Networks - Archive ouverte HAL Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2012

Tracking Topology Dynamicity for Link Prediction in Intermittently Connected Wireless Networks

Résumé

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.

Dates et versions

hal-00716597 , version 1 (10-07-2012)

Identifiants

Citer

Mohamed-Haykel Zayani, Vincent Gauthier, Ines Slama, Djamal Zeghlache. Tracking Topology Dynamicity for Link Prediction in Intermittently Connected Wireless Networks. 2012. ⟨hal-00716597⟩
129 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More