Networked Systems

The problem of finding a consensus in a group of people occurs in many social contexts. In a similar way, distributed algorithms for consensus play an important role in networked computing and communication systems if centralized decision making is difficult or impossible. Each entity in such a system processes only local information obtained from its neighbors and ideally performs only simple computations. Despite this simplicity, the process of consensus building should be robust against different types of disturbance, such as faulty entities, noise, and communication errors.

A research team with members from Klagenfurt and Genoa has now analyzed the robustness of a special class of consensus algorithms, namely binary consensus, in which all entities must eventually agree on one out of two possible values. The motivation for their study is as follows: Some binary consensus algorithms that work well in noiseless and error-free networks?such as the well-known Gacs-Kurdyumov-Levin algorithm?show…

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