On Characteristics and Modeling of P2P Resources with Correlated Static and Dynamic Attributes

Modeling and simulation of Peer-to-Peer (P2P) resources with correlated static and dynamic attributes is essential in application design, validation, and performance analysis. A novel mechanism is presented to generate realistic synthetic traces of multivariate static and dynamic attributes of P2P resources. The methodology is demonstrated using characteristics of PlanetLab node traces. First, a multi-attribute resource model is defined using a selected set of static and dynamic attributes. Second, characteristics of resources are presented. We observe that attribute values are correlated, follow a mixture of probability distributions, and time series of some of the dynamic attributes are nonstationary. Third, random vectors of static attributes are generated using empirical copulas that capture the entire dependence structure of multivariate distribution of attributes. Finally, time series of dynamic attributes are randomly drawn from a library of multivariate-time-series segments extracted from PlanetLab traces. These segments are identified by detecting the structural changes in time series corresponding to a selected attribute. Time series corresponding to rest of the attributes are split at the same breakpoints and randomly drawn together to preserve their contemporaneous correlation. Furthermore, a tool is developed to automate the synthetic data generation process and its output is validated using statistical tests.