Stochastic simulation of P2P VoIP network reconfiguration using graph transformation

Peer-to-Peer (P2P) networks provide an alternative approach to distributed systems, relaxing the requirements for dedicated servers from the client-server model. A P2P network operates as an overlay at application layer, on top of the physical network. In the early years of P2P, most applications lacked mechanisms for enforcing a particular overlay topology. This resulted in inefficient communication schemes, such as flooding or the maintenance of large numbers of connections with other peers. However, researchers and practitioners have realized the importance of constructing and maintaining appropriate overlay topologies for efficient and robust P2P systems. P2P-based Voice over IP (VoIP) networks, such as Skype, distinguish client peers from super peers. This results in a two-level hierarchy: Peers with powerful CPU, more free memory and greater bandwidth take on server-like responsibilities and provide services to a set of client peers. But building and maintaining a super peer-based overlay topology is not easy. In particular, the uncontrollable and unpredictable behaviour of peers results in volatile overlay topologies. This makes it challenging to design reconfigurable and stable networks that provide good Quality of Service (QoS). Various solutions have been proposed. However, peer dynamics, scale and complexity make it hard and expensive to validate them by testing. Simulation can help to validate network designs and protocols, but most existing approaches cannot cope with unbounded dynamic change of network topology. We propose a new approach to the modelling and simulation of P2P network reconfigurations using graph transformation, a visual rule based formalism. Based on existing alternatives we classify network design variations by means of a feature tree. Focussing on P2P VoIP applications, we develop a structural model and transformation rules to compare alternative solutions to the problems of selection and connection to super peers, peer promotion, and load balancing, evaluating their QoS properties. We validate the model using statistics from the real Skype network and experimental data in the literature.