Spatial Node Distribution of the Random Waypoint Mobility Model with Applications
IEEE Transactions on Mobile Computing
Efficient routing in intermittently connected mobile networks: the multiple-copy case
IEEE/ACM Transactions on Networking (TON)
Proceedings of the 1st ACM SIGMOBILE workshop on Mobility models
The ONE simulator for DTN protocol evaluation
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
Optimal routing and scheduling for deterministic delay tolerant networks
WONS'09 Proceedings of the Sixth international conference on Wireless On-Demand Network Systems and Services
Information propagation speed in mobile and delay tolerant networks
IEEE Transactions on Information Theory
Wardrop Equilibrium Formulation of Resource-Constrained DTN Routing in Public Safety Networks
MASS '11 Proceedings of the 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems
DTN: an architectural retrospective
IEEE Journal on Selected Areas in Communications
Taming the mobile data deluge with drop zones
IEEE/ACM Transactions on Networking (TON)
Fragmentation algorithms for DTN links
Computer Communications
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Estimating end-to-end capacity is challenging in disruption-tolerant networks (DTNs) because reliable and timely feedback is usually unavailable. This paper proposes a resource-aware framework for estimating capacity between pairs of nodes. The proposed framework builds on information gathered autonomously by nodes so that results emerge from actual network properties. Achievable capacity is formulated as a linear programming problem. The objective function attempts to maximize delivered size when input data are quantized into messages at source and then injected in a single burst. Problem constraints emerge from conditioning intermediary nodes to avoid resource exhaustion. While the optimal solution remains challenging for most practical settings, the paper discusses alternatives that are less complex and more suitable for real implementation. We cover two scenarios: i) when network mobility is periodic or known in advance, and ii) when mobility is random but its spatial distribution remains stable in time. We claim that the proposed framework can be used to avoid resource exhaustion and network congestion in heterogeneous environments where no information about the system is known in advance. The results have been validated by simulations under various settings (number of flows, store-carry-forward protocols, homogeneous and heterogeneous resource distribution).