Tracking Message Spread in Mobile Delay Tolerant Networks

International audienceWe consider a Delay Tolerant Network under two message forwarding schemes – a non-replicative direct deliveryscheme and a replicative epidemic routing scheme. Our objective is to track the degree of spread of a message in the network.Such estimation can be used for on-line control of message dissemination. With a homogeneous mobility model with pairwise i.i.d. exponential inter-meeting times, we rigorously derive the system dynamic and measurement equations for optimal tracking by a Kalman filter. Moreover, we provide a framework for tracking a large class of processes that can be modeled as densitydependent Markov chains. We also apply the same filter with a heterogeneous mobility, where the aggregate inter-meeting times exhibit a power law with exponential tail as in real-world mobility traces, and show that the performance of the filter is comparable to that with homogeneous mobility. Through customized simulations, we demonstrate the trade-offs and provide severalinsightful observations on how the number of observers impacts the filter performance

Optimal Estimation of Multicast Membership

This paper addresses optimal on-line estimation of the size of a multicast group. Three distinct approaches are used. The first one builds on Kalman filter theory to derive the MSEoptimal estimator in heavy-traffic regime. Under more general assumptions, the second approach uses Wiener filter theory to compute the MSE-optimal linear filter. The third approach develops the best first-order linear filter from which an estimator that holds for any on-time distribution is derived. Our estimators are tested on real video traces and exhibit good performance. The paper also provides guidelines on how to tune the parameters involved in the schemes in order to achieve high quality estimation while simultaneously avoiding feedback implosion