The heterogeneous nature of Peer-to-Peer (P2P) networks can be exploited to optimize a wide range of applications. But this requires an accurate characterization of peer heterogeneity, which is difficult due to huge population and disparate properties of individuals. To overcome this barrier, we conduct a thorough inspection of peer heterogeneity in terms of individual churn and resource capacity. We make a first attempt to (i) experimentally reduce heterogeneous churn and resource dynamics to simple distributions with individual-specific parameters, and to (ii) provide an empirical support for the heterogeneous Markov model of churn. We further demonstrate how our characterization can be leveraged to optimize practical systems, through two case studies: fast backup in online storage and fault-tolerance in cycle-sharing systems. Both applications gain remarkable performance improvement by incorporating our model of peer heterogeneity.
['Zhi Yang', 'Yuanjian Xing', 'Feng Xiao', 'Zhi Qu', 'Xiaoming Li', 'Yafei Dai']
Exploring peer heterogeneity: Towards understanding and application