Article

Performance analysis of structured peer-to-peer overlays for mobile networks

Details

Citation

Chowdhury F, Furness J & Kolberg M (2017) Performance analysis of structured peer-to-peer overlays for mobile networks. International Journal of Parallel, Emergent and Distributed Systems, 32 (5), pp. 522-548. https://doi.org/10.1080/17445760.2016.1203917

Abstract
Distributed Hash Table (DHT) based Peer-to-Peer (P2P) overlays have been widely researched and deployed in many applications such as file sharing, IP telephony, content distribution and media streaming applications. However, their deployment has largely been restricted to fixed, wired networks. This is due to the fact that supporting P2P overlays on wireless networks such as the public mobile data network is more challenging due to constraints in terms of data transmissions on cellular networks, limited battery power of the handsets and increased levels of node churn. However, the proliferation of smartphones makes the use of P2P applications on mobile handsets very desirable.  In this paper, we have analysed and evaluated the performance and efficiency of five popular DHT based structured P2P overlays (Chord, Pastry, Kademlia, Broose and EpiChord) under conditions as commonly experienced in public mobile data networks. Our results show that the conditions in mobile networks, including a high churn rate and the relatively low bandwidth availability is best matched by Kademlia and EpiChord. These overlays exhibit a high lookup success ratio and low hop count while consuming a moderate amount of bandwidth. These characteristics make these two overlays suitable candidates for use in mobile networks.

Keywords
Peer-to-peer overlay; distributed hash table; churn; mobile networks

Journal
International Journal of Parallel, Emergent and Distributed Systems: Volume 32, Issue 5

StatusPublished
Publication date31/12/2017
Publication date online20/07/2016
Date accepted by journal16/06/2016
URLhttp://hdl.handle.net/1893/23405
PublisherTaylor and Francis
ISSN1744-5760
eISSN1744-5779

People (1)

Dr Mario Kolberg

Dr Mario Kolberg

Senior Lecturer, Computing Science

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