Final Report Summary - MOVE-R (Improving the Realism of Mobility and Cooperation Models in Opportunistic Networks)
Summary of the final publishable summary report:
Opportunistic networking is a novel paradigm based on data storing, carrying, and forwarding by mobile nodes which exploit wireless ad-hoc communication opportunities when coming in range of one another. These networks are disruption tolerant and make use of node mobility to transfer data. In areas without connectivity or at the edge of the Internet, opportunistic networks are potential networking alternatives to traditional, infrastructure-based networks. Thus, opportunistic networks are applicable in situations such as search and rescue missions when infrastructure networks have been destroyed or in remote areas without sufficient connectivity, when infrastructures are overloaded and can benefit from offloading, and in disconnected regions in developing countries that should be connected.
As opportunistic networks depend on human mobility and device cooperation, they rely on a good understanding of human mobility behavior, device characteristics, and finally on the application scenario determining the data traffic and quality of service requirements. The Marie Curie EU FP7 project MOVE-R, Improving the Realism of Mobility and Cooperation Models in Opportunistic Networks, conducted at the Communication Systems Group, ETH Zurich, focused on three lines of investigations: (i) characterizing human mobility based on real-world mobility traces originating from GPS data or cellular mobility data, (ii) deriving realistic device models by characterizing major properties such as energy consumption, and (iii) application-driven traffic characterization - in the use cases search and rescue mission and connecting so far disconnected populations.
The results of MOVE-R are documented in 17 publications. The outcomes of MOVE-R are facilitated and extended in SWARMIX, an ongoing project at the Communication Systems Group, ETH Zurich, targeting aerial network provisioning in search and rescue missions to shorten the mission completion time, and ongoing research on connecting disconnected populations – a topic with high societal impact. Finally, we believe that in particular our results for road congestion detection based on cellular data can be leveraged by city planning and road management.
Further information about MOVE-R can be found at: http://people.ee.ethz.ch/˜khummel/mover.html.
A more extended version of the final publishable summary report is attached () as well as a figure ().
Opportunistic networking is a novel paradigm based on data storing, carrying, and forwarding by mobile nodes which exploit wireless ad-hoc communication opportunities when coming in range of one another. These networks are disruption tolerant and make use of node mobility to transfer data. In areas without connectivity or at the edge of the Internet, opportunistic networks are potential networking alternatives to traditional, infrastructure-based networks. Thus, opportunistic networks are applicable in situations such as search and rescue missions when infrastructure networks have been destroyed or in remote areas without sufficient connectivity, when infrastructures are overloaded and can benefit from offloading, and in disconnected regions in developing countries that should be connected.
As opportunistic networks depend on human mobility and device cooperation, they rely on a good understanding of human mobility behavior, device characteristics, and finally on the application scenario determining the data traffic and quality of service requirements. The Marie Curie EU FP7 project MOVE-R, Improving the Realism of Mobility and Cooperation Models in Opportunistic Networks, conducted at the Communication Systems Group, ETH Zurich, focused on three lines of investigations: (i) characterizing human mobility based on real-world mobility traces originating from GPS data or cellular mobility data, (ii) deriving realistic device models by characterizing major properties such as energy consumption, and (iii) application-driven traffic characterization - in the use cases search and rescue mission and connecting so far disconnected populations.
The results of MOVE-R are documented in 17 publications. The outcomes of MOVE-R are facilitated and extended in SWARMIX, an ongoing project at the Communication Systems Group, ETH Zurich, targeting aerial network provisioning in search and rescue missions to shorten the mission completion time, and ongoing research on connecting disconnected populations – a topic with high societal impact. Finally, we believe that in particular our results for road congestion detection based on cellular data can be leveraged by city planning and road management.
Further information about MOVE-R can be found at: http://people.ee.ethz.ch/˜khummel/mover.html.
A more extended version of the final publishable summary report is attached () as well as a figure ().
