Preliminary results of an evolutionary approach towards Contact Plan design for satellite DTNs

Delay and disruption tolerant networks (DTNs) are becoming an appealing solution for extending Internet boundaries so as to embrace disruptive communications. In particular, if node trajectory and orientation can be predicted as in satellite networks, routing schemes can take advantage of the a-priori knowledge of a contact plan comprising the forthcoming communications opportunities. However, the design of such a plan need to consider both available spacecraft resources and the expected traffic which is largely foreseeable in space applications. In this context, the existing Traffic-Aware Contact Plan (TACP) procedure exploits this properties, but the computation complexity of its theoretical formulation results prohibitive for real satellite applications. As a result, we propose CPD-EA: a genetic algorithm to provide sub-optimal yet efficient and implementable contact plans in reasonable time. In particular, we describe the algorithm strategies and evaluate its preliminary performance in a realistic Low Earth Orbit (LEO) scenario demonstrating it usefulness for planning future DTN-based satellite networks.