SIAM Journal on Applied Mathematics
A guided tour of Chernoff bounds
Information Processing Letters
Eigenvalues and expansion of regular graphs
Journal of the ACM (JACM)
Probabilistic Reliable Dissemination in Large-Scale Systems
IEEE Transactions on Parallel and Distributed Systems
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Araneola: A Scalable Reliable Multicast System for Dynamic Environments
NCA '04 Proceedings of the Network Computing and Applications, Third IEEE International Symposium
On the communication complexity of randomized broadcasting in random-like graphs
Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
The power of memory in randomized broadcasting
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Proceedings of the twenty-seventh ACM symposium on Principles of distributed computing
Quasirandom Rumor Spreading: Expanders, Push vs. Pull, and Robustness
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Broadcasting vs. mixing and information dissemination on Cayley graphs
STACS'07 Proceedings of the 24th annual conference on Theoretical aspects of computer science
Communication complexity of quasirandom rumor spreading
ESA'10 Proceedings of the 18th annual European conference on Algorithms: Part I
Efficient broadcasting in random power law networks
WG'10 Proceedings of the 36th international conference on Graph-theoretic concepts in computer science
Social networks spread rumors in sublogarithmic time
Proceedings of the forty-third annual ACM symposium on Theory of computing
Randomised broadcasting: memory vs. randomness
LATIN'10 Proceedings of the 9th Latin American conference on Theoretical Informatics
IEEE Transactions on Information Theory
| Hi-index | 5.23 |
In this paper we analyse broadcasting in d-regular networks with good expansion properties. For the underlying communication, we consider modifications of the so-called random phone call model. In the standard version of this model, each node is allowed in every step to open a channel to a randomly chosen neighbour, and the channels can be used for bi-directional communication. Then, broadcasting on the graphs mentioned above can be performed in time O(logn), where n is the size of the network. However, every broadcast algorithm with runtime O(logn) needs on average @W(logn/logd) message transmissions per node for random graphs with expected degree d[11]. In this paper we show that it is possible to save significantly on communications if the standard model is modified such that nodes can avoid opening channels to exactly the same neighbours in two consecutive steps. We consider the so-called Rr model where we assume that every node has a cyclic list of all of its neighbours, ordered in a random way. Then, in step i the node communicates with the i-th neighbour from that list. We provide an O(logn) time algorithm which produces in average O(logn) transmissions per node in networks with suitably defined expansion properties. Furthermore, we present a related lower bound of @W(logn/loglogn) for the average number of message transmissions. These results show that by using memory it is possible to reduce the number of transmissions per node by almost a quadratic factor.