Probabilistic routing in intermittently connected networks
ACM SIGMOBILE Mobile Computing and Communications Review
Spray and wait: an efficient routing scheme for intermittently connected mobile networks
Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking
A hybrid routing approach for opportunistic networks
Proceedings of the 2006 SIGCOMM workshop on Challenged networks
Opportunistic wireless access networks
AcessNets '06 Proceedings of the 1st international conference on Access networks
Prioritized epidemic routing for opportunistic networks
Proceedings of the 1st international MobiSys workshop on Mobile opportunistic networking
Visualizing communities and centralities from encounter traces
Proceedings of the third ACM workshop on Challenged networks
The ONE simulator for DTN protocol evaluation
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
Detecting dynamic communities in opportunistic networks
ICUFN'09 Proceedings of the first international conference on Ubiquitous and future networks
Time-varying graphs and dynamic networks
ADHOC-NOW'11 Proceedings of the 10th international conference on Ad-hoc, mobile, and wireless networks
BUBBLE Rap: Social-Based Forwarding in Delay-Tolerant Networks
IEEE Transactions on Mobile Computing
A Comparison of Opportunistic Connection Datasets
EIDWT '12 Proceedings of the 2012 Third International Conference on Emerging Intelligent Data and Web Technologies
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Opportunistic networking differs from conventional architectures in the lack of existing network infrastructure, which can cause intermittent connectivity or increased communication delay between nodes. From a message routing perspective, solving these problems require a different set of techniques than those used in more traditional network schemes. Forwarding algorithms in these scenarios aim to improve performance metrics such as message delivery ratio and message delay time, while trying to keep the number of message copies small. A common approach used for testing the performance of opportunistic protocols relies on existing opportunistic contact traces. These datasets are widely available on the Internet, and provide a convenient way of simulating realistic usage scenarios. As such, studying the contact patterns between nodes can lead to useful observations to take into account in future experiments. This paper presents the results of a study on four different datasets. First, the authors describe the main characteristics of each trace. Then, they propose a graphical representation of the contact behavior for each pair of nodes. Further analysis of the results in terms of connectivity distribution among nodes reveals that contacts follow a roughly lognormal distribution and that there is a small group of nodes in each set which is seemingly much more popular than the rest. Finally, the authors introduce a temporal analysis that was made over the duration of each collection experiment. It was noticeable that individual nodes have repetitive contact patterns over time, apart from some observed cyclic variation over time namely on weekends. By modeling the data traces as time-varying graphs, a performance decrease was observed with the absence of the most popular nodes.