JumpNet: Improving Connectivity and Robustness in Unstructured P2P Networks by Randomness

We propose a self-organizing algorithm that maintains a high degree of connectivity and robustness in unstructured P2P networks. The algorithm is based on the "jump" primitive that periodically replaces overlay links at each node. The algorithm produces and maintains P2P networks that closely approximate sparse random graphs. Although the sparse random graphs have low degree, they are well connected and possess low diameter. This makes them good candidates for common P2P networks. Through a series of simulation experiments, we confirm that the jump algorithm leads to a network topology with these desirable properties if we start with an ad-hoc network. P2P networks conditioned through jumps also accomplish search and broadcast operations very effectively as compared to both simulated and real-life systems such as the Gnutella ultrapeer network.