2012 5th International Conference on New Technologies, Mobility and Security (NTMS) 2012
DOI: 10.1109/ntms.2012.6208681
|View full text |Cite
|
Sign up to set email alerts
|

A Study of Mobility in Ad Hoc Networks and Its Effects on a Hop Count Based Distance Estimation

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
4
0

Year Published

2012
2012
2016
2016

Publication Types

Select...
3
3

Relationship

1
5

Authors

Journals

citations
Cited by 6 publications
(4 citation statements)
references
References 17 publications
0
4
0
Order By: Relevance
“…Nodes are also capable of avoiding obstacle collision by deviating their path upon obstacle detection. The stream mobility (StrM) model [16] has a similar mobility pattern, simulating nodes in moving water or wind. Each node chooses a random angle and speed.…”
Section: Group Mobility Modelsmentioning
confidence: 99%
“…Nodes are also capable of avoiding obstacle collision by deviating their path upon obstacle detection. The stream mobility (StrM) model [16] has a similar mobility pattern, simulating nodes in moving water or wind. Each node chooses a random angle and speed.…”
Section: Group Mobility Modelsmentioning
confidence: 99%
“…In this work, we are not proposing a completely new mobility model. Rather, we assume that the mobility of the nodes are given as semantics . For simulation, random way‐point model has been considered.…”
Section: Overview Of Policon Frameworkmentioning
confidence: 99%
“…Due to the fact that the neighbor closest to the referece device usually does not lie at the border of the communication range, but somewhere closer to the device itself, the distances are naturally overestimated throughout the network (cf. [5], [47]). Underestimation, due to the proposed distance estimation method, can only happen in a dynamic network.…”
Section: Distance Estimation With Firefly-inspired Hop Countingmentioning
confidence: 99%
“…As the distances are naturally overestimated, the mobility reduces the error for the distance estimates and, thus, the algorithms with higher proportion of underestimation have a lower MAPE. This effect is discussed in great detail for different kinds of mobility in [47]. The effect of mobility is higher, the further away a device moves from the reference device before updating its hop count.…”
Section: Distance Estimation With Firefly-inspired Hop Countingmentioning
confidence: 99%