Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
We consider the fault-tolerant consensus problem in radio networks with crash-prone nodes. Specifically, we develop lower bounds and matching upper bounds for this problem in single-hop radios networks, where all nodes are located within broadcast range of ...
We study oblivious deterministic gossip algorithms for multi-channel radio networks with a malicious adversary. In a multi-channel network, each of the n processes in the system must choose, in each round, one of the c channels of the system on which to pa ...
How efficiently can a malicious device disrupt communication in a wireless network? Imagine a basic game involving two honest players, Alice and Bob, who want to exchange information, and an adversary, Collin, who can disrupt communication using a limited ...
Many recommend planning for the worst and hoping for the best. In this paper we devise efficient indulgent consensus algorithms that can tolerate crash failures and arbitrarily long periods of asynchrony, and yet perform (asymptotically) optimally in well- ...
How efficiently can a malicious device disrupt a single-hop wireless network? Imagine two honest players attempting to exchange information in the presence of a malicious adversary that can disrupt communication by jamming or overwriting messages. Assume t ...
We study the problem of secure communication in a multi-channel, single-hop radio network with a malicious adversary that can cause collisions and spoof messages. We assume no pre-shared secrets or trusted-third-party infrastructure. The main contribution ...