Bandwidth Prediction in the Face of Asymmetry

Abstract : An increasing number of networked applications, like video conference and video-on-demand, benefit from knowledge about Internet path measures like available bandwidth. Server selection and placement of infrastructure nodes based on accurate information about network conditions help to improve the quality-of-service of these systems. Acquiring this knowledge usually requires fully-meshed ad-hoc measurements. These, however, introduce a large overhead and a possible delay in communication establishment. Thus, prediction-based approaches like Sequoia have been proposed, which treat path properties as a semimetric and embed them onto trees, leveraging labelling schemes to predict distances between hosts not measured before. In this paper, we identify asymmetry as a cause of serious distortion in these systems causing inaccurate prediction. We study the impact of asymmetric network conditions on the accuracy of existing tree-embedding approaches, and present direction-aware embedding, a novel scheme that separates upstream from downstream properties of hosts and significantly improves the prediction accuracy for highly asymmetric datasets. This is achieved by embedding nodes for each direction separately and constraining the distance calculation to inversely labelled nodes. We evaluate the effectiveness and trade-offs of our approach using synthetic as well as real-world datasets.
Type de document :
Communication dans un congrès
Jim Dowling; François Taïani. 13th International Conference on Distributed Applications and Interoperable Systems (DAIS), Jun 2013, Florence, Italy. Springer, Lecture Notes in Computer Science, LNCS-7891, pp.99-112, 2013, Distributed Applications and Interoperable Systems. 〈10.1007/978-3-642-38541-4_8〉
Liste complète des métadonnées

Littérature citée [26 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01489468
Contributeur : Hal Ifip <>
Soumis le : mardi 14 mars 2017 - 14:19:51
Dernière modification le : mardi 14 mars 2017 - 16:07:25
Document(s) archivé(s) le : jeudi 15 juin 2017 - 14:25:38

Fichier

978-3-642-38541-4_8_Chapter.pd...
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Sven Schober, Stefan Brenner, Rüdiger Kapitza, Franz Hauck. Bandwidth Prediction in the Face of Asymmetry. Jim Dowling; François Taïani. 13th International Conference on Distributed Applications and Interoperable Systems (DAIS), Jun 2013, Florence, Italy. Springer, Lecture Notes in Computer Science, LNCS-7891, pp.99-112, 2013, Distributed Applications and Interoperable Systems. 〈10.1007/978-3-642-38541-4_8〉. 〈hal-01489468〉

Partager

Métriques

Consultations de la notice

54

Téléchargements de fichiers

26