Mobility increases the capacity of ad hoc wireless networks
IEEE/ACM Transactions on Networking (TON)
The random trip model: stability, stationary regime, and perfect simulation
IEEE/ACM Transactions on Networking (TON)
On the connectivity of dynamic random geometric graphs
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
On the latency for information dissemination in mobile wireless networks
Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing
Flooding time in edge-Markovian dynamic graphs
Proceedings of the twenty-seventh ACM symposium on Principles of distributed computing
Broadcasting in dynamic radio networks
Journal of Computer and System Sciences
MANETS: High Mobility Can Make Up for Low Transmission Power
ICALP '09 Proceedings of the 36th Internatilonal Collogquium on Automata, Languages and Programming: Part II
Parsimonious flooding in dynamic graphs
Proceedings of the 28th ACM symposium on Principles of distributed computing
Information spreading in stationary Markovian evolving graphs
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Proceedings of the 29th ACM SIGACT-SIGOPS symposium on Principles of distributed computing
| Hi-index | 0.00 |
We study the information spreading yielded by the (Parsimonious) k-Flooding Protocol in geometric Mobile Ad-Hoc Networks. We consider n agents on a square of side length L performing independent random walks with move radius ρ. At any time step, every active agent v informs every non-informed agent which is within distance R from v (R 0 is the transmission radius). An agent is only active for the next k time steps following the one in which has been informed and, after that, she is removed. At the initial time step, a source agent is informed and we look at the completion time of the protocol, i.e., the first time step (if any) in which all agents are informed. The presence of removed agents makes this process much more complex than the (standard) flooding and no analytical results are available over any explicit mobility model. We prove optimal bounds on the completion time depending on the parameters n, L, R, and ρ. The obtained bounds hold with high probability. Our method of analysis provides a clear picture of the dynamic shape of the information spreading (or infection wave) over the time.