Epidemic algorithms for replicated database maintenance
ACM SIGOPS Operating Systems Review
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Gossip-Based Computation of Aggregate Information
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Quasirandom Rumor Spreading: Expanders, Push vs. Pull, and Robustness
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
On the runtime and robustness of randomized broadcasting
ISAAC'06 Proceedings of the 17th international conference on Algorithms and Computation
Reliable broadcasting in random networks and the effect of density
INFOCOM'10 Proceedings of the 29th conference on Information communications
How efficient can gossip be? (on the cost of resilient information exchange)
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming: Part II
On the randomness requirements of rumor spreading
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
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Randomized rumor spreading is a classic protocol to disseminate information in a network. At SODA 2008, a quasirandom version of this protocol was proposed and competitive bounds for its run-time were proven. This prompts the question: to what extent does the quasirandom protocol inherit the second principal advantage of randomized rumor spreading, namely robustness against transmission failures?A tentative solution was proposed at ICALP 2009 where it was demonstrated that if each transmission reaches its destination with a probability of p 驴 (0,1], the run-time increases by a factor of approximately 4/p. In this paper, we follow up on this research and provide a result precise up to (1 卤o(1)) factors. We limit ourselves to the network in which every two vertices are connected by a direct link. Run-times accurate to their leading constants are unknown for all other non-trivial networks.For networks on n nodes, we show that after $(1+\varepsilon)(\log_{1+p}n+\frac{1}{p}\ln n)$ rounds, the quasirandom protocol with probability 1 驴 n 驴 c(驴, p) has informed all nodes in the network. Note that this is faster than the intuitively natural 1/p factor increase over the run-time of approximately log2 n + ln n for the non-corrupted case.We also provide a corresponding lower bound for the classical model. This demonstrates that the quasirandom model is at least as robust as the fully random model despite the greatly reduced degree of independent randomness.