Name
Abstract | ||
|---|---|---|
In this paper, we consider Underwater Sensor Networks (UWSNs) where nodes can move freely with underwater currents. In such networks, it is of interest to estimate the likelihood that a network has a connected component of (at least) a given size during some interval of time of interest after deployment. We formalize the problem using a probabilistic graph model, and develop a dynamic programming algorithm to solve the problem exactly when the graph has an interval representation. The interval representation model is motivated by scenarios where nodes move along a path in a relatively long but thin geographical area. We present numerical results on the performance of the algorithm under varying conditions of the required component size, and the size and structure of the set of intervals representing the probabilistic graph. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LCN.2018.8638137 | LCN |
Keywords | Field | DocType |
Probabilistic logic,Analytical models,Numerical models,Computational modeling,Approximation algorithms,Conferences,Computer networks | Dynamic programming,Approximation algorithm,Graph,Underwater sensor networks,Software deployment,Computer science,Algorithm,Connected component,Probabilistic logic,Distributed computing,Underwater | Conference |
ISBN | Citations | PageRank |
978-1-5386-4413-3 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Salwa Abougamila | 1 | 0 | 0.34 |
| Mohammed Elmorsy | 2 | 3 | 2.78 |
| Ehab S. Elmallah | 3 | 105 | 19.29 |