Efficient Data Advertisement in Information Centric Disruption Tolerant Networks

Abstract

Large-scale Information Centric Disruption Tolerant Networks (ICDTNs) are now being evaluated as a powerful system paradigm for data sharing when existing communication infrastructures are compromised. The effectiveness of an ICDTN is largely dependent upon efficient and scalable data advertising mechanisms, yet this problem has until recently not been extensively studied. This paper proposes a solution to the data advertising problem that is based upon random linear network coding. We show how to encode, decode, and use Named Data Networking advertising structures in an ICDTN environment. We have compared our approach to the standard flooding techniques under a variety of network sizes, communication conditions, node densities and mobility patterns. Our results show that our approach is both highly scalable and can significantly decrease the time for advertisement message delivery.