A group mobility model for ad hoc wireless networks
MSWiM '99 Proceedings of the 2nd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
Smooth is better than sharp: a random mobility model for simulation of wireless networks
MSWIM '01 Proceedings of the 4th ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
The Spatial Node Distribution of the Random Waypoint Mobility Model
Mobile Ad-Hoc Netzwerke, 1. deutscher Workshop über Mobile Ad-Hoc Netzwerke WMAN 2002
CarTel: a distributed mobile sensor computing system
Proceedings of the 4th international conference on Embedded networked sensor systems
WICON '06 Proceedings of the 2nd annual international workshop on Wireless internet
IEEE Pervasive Computing
Combining web, mobile phones and public displays in large-scale: manhattan story mashup
PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
CenceMe: injecting sensing presence into social networking applications
EuroSSC'07 Proceedings of the 2nd European conference on Smart sensing and context
GreenGPS: a participatory sensing fuel-efficient maps application
Proceedings of the 8th international conference on Mobile systems, applications, and services
From opportunistic networks to opportunistic computing
IEEE Communications Magazine
Tight bounds on information dissemination in sparse mobile networks
Proceedings of the 30th annual ACM SIGACT-SIGOPS symposium on Principles of distributed computing
| Hi-index | 0.00 |
In this paper, we study the impact of node density on data dissemination time and achieved data quality in a distributed people-centric system. Our results are obtained through an extensive simulation campaign employing Random Way Point and Random Direction mobility and realistic node densities of real environments. Our simulation results show that, the impact of node density does not significantly affect the data dissemination time after a certain threshold of node density, without compromising the achieved data quality. This result is evident for both mobility models. Our study provides an insight to the parameters we need to consider while evaluating the success of any distributed people-centric system.