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
The Node Distribution of the Random Waypoint Mobility Model for Wireless Ad Hoc Networks
IEEE Transactions on Mobile Computing
Detecting MAC Layer Back-off Timer Violations in Mobile Ad Hoc Networks
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
Performance evaluation of backoff algorithms in 802.11 ad-hoc networks
Proceedings of the 3rd ACM international workshop on Performance evaluation of wireless ad hoc, sensor and ubiquitous networks
Stationary Distributions for the Random Waypoint Mobility Model
IEEE Transactions on Mobile Computing
Estimating sizes of social networks via biased sampling
Proceedings of the 20th international conference on World wide web
Friendship and mobility: user movement in location-based social networks
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Human mobility, social ties, and link prediction
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Human mobility and predictability enriched by social phenomena information
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
| Hi-index | 0.00 |
We propose to use social networking data to validate mobility models for pervasive mobile ad-hoc networks (MANETs) and delay tolerant networks (DTNs). The Random Waypoint (RWP) and Erdos-Renyi (ER) models have been a popular choice among researchers for generating mobility traces of nodes and relationships between them. Not only RWP and ER are useful in evaluating networking protocols in a simulation environment, but they are also used for theoretical analysis of such dynamic networks. However, it has been observed that neither relationships among people nor their movements are random. Instead, human movements frequently contain repeated patterns and friendship is bounded by distance. We used social networking site Go Walla to collect, create and validate models of human mobility and relationships for analysis and evaluations of applications in opportunistic networks such as sensor networks and transportation models in civil engineering. In doing so, we hope to provide more human-like movements and social relationship models to researchers to study problems in complex and mobile networks.