Power law and exponential decay of inter contact times between mobile devices
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
The age of gossip: spatial mean field regime
Proceedings of the eleventh international joint conference on Measurement and modeling of computer systems
Characterizing podcast services: publishing, usage, and dissemination
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Distributed stochastic optimization in opportunistic networks: the case of optimal relay selection
Proceedings of the 5th ACM workshop on Challenged networks
On the stability and optimality of universal swarms
Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
On the stability and optimality of universal swarms
ACM SIGMETRICS Performance Evaluation Review - Performance evaluation review
Scoop: decentralized and opportunistic multicasting of information streams
MobiCom '11 Proceedings of the 17th annual international conference on Mobile computing and networking
MobiTrade: trading content in disruption tolerant networks
CHANTS '11 Proceedings of the 6th ACM workshop on Challenged networks
When multi-touch meets streaming
Proceedings of the 10th International Conference on Mobile and Ubiquitous Multimedia
An on-demand routing protocol for improving channel use efficiency in multichannel ad hoc networks
Journal of Network and Computer Applications
CEDO: content-centric dissemination algorithm for delay-tolerant networks
Proceedings of the 16th ACM international conference on Modeling, analysis & simulation of wireless and mobile systems
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Collaborative ad-hoc dissemination has been proposed as an efficient means to disseminate information among devices in wireless ad-hoc networks. It is based on each device forwarding channels that the user of this device is subscribed to and helping forward some other channels. We consider the case where devices have limited resources and thus have to decide which channels to help. The goal is to identify a channel selection strategy that optimizes a global system welfare that is a function of the dissemination times across all distinct channels. We consider a random mixing mobility model under which the channel dissemination time is a function of the number of nodes that forward this channel. We show that maximizing system welfare is equivalent to an assignment problem whose solution can be obtained by a centralized greedy algorithm. We provide empirical evidence that the difference between the system welfare of an optimum assignment and some heuristics proposed in the past can be significant. Furthermore, we show that the optimum social welfare can be approximated by a decentralized algorithm based on Metropolis-Hastings sampling and give a variant that also accounts for the battery energy. Our work provides guidelines how to design decentralized channel selection algorithms that optimize an a priori defined global objective.