Characterizing Chord, Kelips and Tapestry algorithms in P2P streaming applications over wireless network

In the last few years, there is a tendency of shifting P2P applications toward multimedia services, especially P2P streaming applications. The reason behind this is the clear advantages of flexibility, efficiency and self-scalability of P2P networks, which greatly reduce the infrastructure cost of service providers. However, supporting P2P streaming over wireless environment is a very challenging task due to the intermittent nature of wireless link and the energy-saving mechanisms of mobile devices. As a result, the P2P streaming over wireless will be largely different from wired P2P application due to the high frequency of node joining & leaving the network namely churn rate. Since most of third generation of P2P applications implement Distributed Hash Table algorithm (DHT), it is crucial to deeply investigate and improve DHTs in order to adapt them in the harsh wireless environments. Our study use simulation approach to characterize and compare the performance of three popular DHT algorithms Chord, Kelips and Tapestry under high churn rate. The major contribution of this paper is the identification of the most important parameters of DHTs to their performance and the comparisons between these mechanisms under extreme conditions of wireless environment We observed several interesting behaviors of DHTs including: 1) Tapestry works better than Chord and Kelips in terms of successful lookup rate at very high churn rate less than 120s but Chord achieves the best performance among three DHTs when churn rate is more than 300s. 2) Tapestry performance is more sensitive to RTT than Kelips and Chord. 3) Both Chord and Tapestry shows high scalability under high churn (except for some extreme cases when Chord fails at very high churn rate). 4) Churn rate strongly affects to the successful lookup ratio, but shows very slight effect on medium lookup latency of all three protocols. 5) We also found Chord is inferior to the two other DHT in terms of performance optimization.