  Large scale decentralized systems, such as P2P, sensor or IoT device networks
are becoming increasingly common, and require robust protocols to address the
challenges posed by the distribution of data and the large number of peers
belonging to the network. In this paper, we deal with the problem of mining
frequent items in unstructured P2P networks. This problem, of practical
importance, has many useful applications. We design P2PSS, a fully
decentralized, gossip--based protocol for frequent items discovery, leveraging
the Space-Saving algorithm. We formally prove the correctness and theoretical
error bound. Extensive experimental results clearly show that P2PSS provides
very good accuracy and scalability, also in the presence of highly dynamic P2P
networks with churning. To the best of our knowledge, this is the first
gossip--based distributed algorithm providing strong theoretical guarantees for
both the Approximate Frequent Items Problem in Unstructured P2P Networks and
for the frequency estimation of discovered frequent items.
