Providing independent uniform samples from a system population poses considerable problems in highly dynamic settings, like P2P systems, where the number of participants and their unpredictable behavior (e.g., churn, crashes etc.) may introduce relevant bias. Current implementations of the Peer Sampling Service are designed to provide uniform samples only in static settings and do not consider that biased samples can directly affect the correctness of algorithms relying on a uniformity property or be exploited by a malicious adversary to increase the effectiveness of its attacks to the system. In this paper we provide a practical solution to the biasing problem by deploying a fully distributed Peer Sampling Correction Module on top of a given, possibly biased, peer sampling service. Samples provided by the peer sampling service will be locally processed by this module, using computationally efficient hashing functions, before getting to the application. The effectiveness of our approach is evaluated through an extensive simulation-based study.

This paper studies the problem of realizing a common software clock among a large set of nodes without an external time reference (i.e., internal clock synchronization), any centralized control, and where nodes can join and leave the distributed system at their will. The paper proposes an internal clock synchronization algorithm which combines the gossip-based paradigm with a nature-inspired approach, coming from the coupled oscillators phenomenon, to cope with scale and churn. The algorithm works on the top of an overlay network and uses a uniform peer sampling service to fulfill each node's local view. Therefore, differently from clock synchronization protocols for small scale and static distributed systems, here, each node synchronizes regularly with only the neighbors in its local view and not with the whole system. An evaluation of the convergence speed and the synchronization error of the coupled-based internal clock synchronization algorithm has been carried out, showing how convergence time and the synchronization error depends on the coupling factor and the local view size. Moreover, the variation of the synchronization error with respect to churn and the impact of a sudden variation of the number of nodes have been analyzed to show the stability of the algorithm. In all these contexts, the algorithm shows nice performance and very good self-organizing properties. Finally, we showed how the assumption on the existence of a uniform peer-sampling service is instrumental for the good behavior of the algorithm and how, in system models where network delays are unbounded, a mean-based convergence function reaches a lower synchronization error than median-based convergence functions exploiting the number of averaged clock values.

This paper proposes an internal clock synchronization algorithm for very large number of processes that is able to (i) self-synchronize their local clocks without any central control and (ii) resist to attacks of an adversary whose aim is to put out-of-synchronization as many correct processes as possible. To cope with scale the algorithm utilizes the gossip-based paradigm where each process has a limited view of the system, while to resist to attacks the algorithm employs a filtering mechanism based on the notion of ¿-trimmed mean to filter out out-of-range clock values. The algorithm shows nice convergence in presence of networks errors and in absence of the adversary. When the adversary takes control of some of the processes in the system, we define two goals for the adversary, actually two predicates, to measure the strength of the attack. The first one captures the percentage of time in which at least one correct is out of synchronization and the second one when all correct processes are out of synchronization. The paper presents an extensive simulation study showing under which conditions (in terms of number of corrupted processes and size of local views) these two goals can be achieved by the adversary. Interestingly, these results can be exploited by applications that can tolerate either a certain time in which some correct process is non-synchronized or a certain percentage of correct processes that is non-synchronized.

A fundamental problem for both structured and unstructured peer-to-peer networks is how to maintain connected the topology of a network in the presence of processes that, possibly concurrently, join and leave the network. In this paper we firstly define a model of the computation well-suited to analyze connectivity maintenance among processes carrying out a distributed computation considering unbounded concurrency and infinite participation. Secondly upon this model we provide a specification of the connectivity maintenance problem. We finally present a protocol that guarantees connectivity maintenance by arranging processes of the computation on a tree. The protocol handles both joins and leaves concurrently and actively (i.e., some piece of code is executed by a leaving/joining process interacting with its neighbors in the topology).