Name
Abstract | ||
|---|---|---|
Human mobility has been shown to have significant impact on the performance of Opportunistic Networks. For reliable performance evaluation, it is important to make sure the models used are in steady state. The mobility model Small World In Motion (SWIM) incorporates statistical properties of human movements in its results and is, at the same time, easy to configure. However, SWIM is not in steady state. In this paper, we show how a steady state for SWIM can be achieved.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3345768.3355935 | Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems |
Keywords | Field | DocType |
mobility model, opportunistic networks, steady state | Computer science,Mobility model,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-4503-6904-6 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nils Aschenbruck | 1 | 555 | 56.28 |
| Hanna Döring | 2 | 0 | 0.34 |
| Christian Heiden | 3 | 0 | 0.34 |
| Matthias Schwamborn | 4 | 199 | 9.31 |