Disruption-Tolerant Networks (DTN) allow communication between devices that lack end-to-end connectivity. Even though the mobility of devices in a DTN is frequently dynamic, most proposed DTN protocols are not adaptive. This work presents an ongoing research project that aims to find out to which extent context-based adaptation may be useful to improve DTN performance. We are convinced that, in highly predictive networks, metadata exchange is a crucial factor in supporting routing decisions and recognize context changes. This paper summarizes the efforts we have made so far and presents the next steps we plan to take towards the design and implementation of an adaptive framework.

Future applications will run in a highly heterogeneous and dynamic execution environment that forces them to adapt their behavior and offered functionality depending on the user's or the system's current situation. Since application components in such heterogeneous multi-device systems will be distributed over multiple interconnected devices and cooperate to achieve a common goal, a coordinated adaptation is required to ensure a consistent system behavior. In this paper we present a decentralized adaptation middleware to adapt a distributed software system. Our approach supports the reliable execution of multiple adaptation operations that depend on each other and are performed transactionally even in unsteady environments coined by message loss or node failures. We implemented our approach in a search-and-rescue robot scenario to show its feasibility and conduct first performance evaluations.