Epidemic algorithms for replicated database maintenance
PODC '87 Proceedings of the sixth annual ACM Symposium on Principles of distributed computing
A guided tour of Chernoff bounds
Information Processing Letters
Embedding meshes on the star graph
Journal of Parallel and Distributed Computing
Discrete Applied Mathematics
Edge-Disjoint Spanning Trees on the Star Network with Applications to Fault Tolerance
IEEE Transactions on Computers
A Comparative Study of Topological Properties of Hypercubes and Star Graphs
IEEE Transactions on Parallel and Distributed Systems
Nearly Optimal One-to-Many Parallel Routing in Star Networks
IEEE Transactions on Parallel and Distributed Systems
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Threshold of Broadcast in Random Graphs
Threshold of Broadcast in Random Graphs
Characterization of node disjoint (parallel) path in star graphs
IPPS '91 Proceedings of the Fifth International Parallel Processing Symposium
Three disjoint path paradigms in star networks
SPDP '91 Proceedings of the 1991 Third IEEE Symposium on Parallel and Distributed Processing
On the runtime and robustness of randomized broadcasting
Theoretical Computer Science
Broadcasting vs. mixing and information dissemination on Cayley graphs
STACS'07 Proceedings of the 24th annual conference on Theoretical aspects of computer science
On the runtime and robustness of randomized broadcasting
ISAAC'06 Proceedings of the 17th international conference on Algorithms and Computation
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One of the most frequently studied problems in the context of information dissemination in communication networks is the broadcasting problem. In this paper, we study the following robust, simple, and scalable randomized broadcasting protocol: At some time t an information is placed at one of the nodes of a graph G, and in the succeeding steps, each informed node choses one of its neighbors in G uniformly at random, and sends the information to this neighbor. We show that this algorithm spreads an information to all nodes in a Star graph Sn of dimension n within O(log (n)) steps, with high probability, where n denotes the number of nodes in Sn. In our proofs, we apply some methods which may be of independent interest, and extend the results of [10] concerning randomized broadcasting in hypercubic graphs.