Abstract
Much of the well-established theory of distributed algorithms focuses on static networks, where nodes do not crash and edges maintain operational status forever. On the other hand, large real-world networks are inherently dynamic: the participants in peer-to-peer networks and social networks change over time, mobile nodes in wireless networks move in and out of each other’s transmission range, and, in distributed data center networks, faulty machines need to be replaced by new machines without interrupting the operation of the remaining network. Dynamic network models, where the communication topology varies over time but where the set of nodes is fixed, have been studied extensively in literature.
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