Resilient Asymptotic Consensus in Robust Networks

Multidimensional Asymptotic Consensus in Dynamic Networks

We study the problem of asymptotic consensus as it occurs in a wide range of applications in both man-made and natural systems. In particular, we study systems with directed communication graphs that may change over time. We recently proposed a new family of convex combination algorithms in dimension one whose weights depend on the received values and not only on the communication topology. Her...

Error Resilient and Robust Overlay Networks

Brief Announcement: Lower Bounds for Asymptotic Consensus in Dynamic Networks

In the asymptotic consensus problem a set of agents, each starting from an initial value in R, update their values such that all agents’ values converge to a common value within the convex hull of initial values. The problem is closely related to the approximate consensus problem, in which agents have to irrevocably decide on values that lie within a predefined distance ε > 0 of each other. The...

Lower Bounds for Asymptotic Consensus in Dynamic Networks

In this work we study the performance of asymptotic and approximate consensus algorithms in dynamic networks. The asymptotic consensus problem requires a set of agents to repeatedly set their outputs such that the outputs converge to a common value within the convex hull of initial values. This problem, and the related approximate consensus problem, are fundamental building blocks in distribute...

Issues for Robust Consensus Building in P2P Networks

The need for semantic interoperability between ontologies in a peer-to-peer (P2P) environment is imperative. This is because, by definition participants in P2P environment are equal, autonomous and distributed. For example, the synthesis of concepts developed independently by different academic researchers, different research labs, various emergency service departments and, hospitals and pharma...