Dirk Kutscher

I presented GreenICN work on Scalable Content Exchange in Challenged ICNs at CCNxCon-2015 this week.

Download: ccnxcon2015-kutscher.pdf

Abstract:
The principles of Information­Centric Networking (ICN), accessing data objects by name (not by location address), securing data objects (not connections), in­network caching (for sharing, repair, rate adaptation) make ICN attractive for a wide range of application scenarios beyond traditional data center or telco access network scenarios. In fact, one of the first instantiation of ICN had been developed based on Delay­Tolerant Networking (DTN) technologies.

Currently, ICN/DTN is considered a promising approach for enabling/enhancing communication in disaster scenarios. In such scenarios, so­called ICN data mules (that carry and disseminate data times) may move randomly, and each time data mules encounter one another exchange data items. We envision that in such a scenario where there is no connectivity, data mules (e.g. vehicles or drones) can move around randomly. So these mobile routers interact with end users, working base stations and other data mules to fetch and deliver the data and queries. Thus, we do not consider adhoc networks where you can build a path to the destination reactively or proactively, rather a DTN like scenario.

Consider a large scale disaster scenario like the earthquake in Japan in 2011 , where people in different parts of the city are stranded without the internet connectivity. But there are some zones, where base stations are still working and providing connectivity. Essentially, the scenario is such that ICN data mule move randomly across a geographic area, and when meeting end­users receive interests from them and also forward corresponding data items to end­users (if present in the content store / cache of the data mule). At the same time, when data mules encounter each other, they forward to each other certain end­user interest and/or data items (according to a predefined rule set and algorithm), such that interests and data items can be forwarded in a hop­by­hop DTN fashion. One research problem in such a scenario is how to optimize such data exchanges among data mules for optimal data dissemination (e.g. optimizing how many desired messages reach their recipients within a given timeframe with a given forwarding strategy, assuming that data mules only have limited time at each encounter to exchange
messages).