An adaptive peer selection scheme with dynamic network condition awareness
Wang, CJ, Wang, N, Howarth, MP and Pavlou, G (2009) An adaptive peer selection scheme with dynamic network condition awareness In: IEEE International Conference on Communications (ICC 2009), 2009-06-14 - 2009-06-18, Dresden, Germany.
icc final accepted.pdf
Available under License : See the attached licence file.
Locality-based peer selection paradigms have been proposed recently based on cooperation between peer-to-peer (P2P) service providers, Internet Service Providers (ISPs) and end users in order to achieve efficient resource utilization by P2P traffic. Based on this cooperation between different stakeholders, we introduce a more advanced paradigm with adaptive peer selection that takes into account traffic dynamics in the operational network. Specifically, peers associated with low path utilization as measured by the ISP are selected in order to reduce the probability of network congestion. This approach not only improves real-time P2P service assurance but also optimizes the overall use of network resources. Our simulations based on the GEANT network topology and real traffic traces show that the proposed adaptive peer selection scheme achieves significant improvement in utilizing bandwidth resources as compared to static locality-based approaches.
|Item Type:||Conference or Workshop Item (Paper)|
|Divisions :||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research|
|Additional Information :||
© 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
|Depositing User :||Symplectic Elements|
|Date Deposited :||29 Feb 2012 13:54|
|Last Modified :||23 Sep 2013 18:57|
Actions (login required)
Downloads per month over past year