Provenance-driven data dissemination in disruption tolerant networks

Disruption Tolerant Networks (DTNs) are characterized by low node density, unpredictable node mobility and lack of global network information. Most of the current research efforts in DTNs focus on data forwarding, but only limited work has examined the problem of providing effective access of fused information to mobile users. In this paper, we examine a QoI metric — provenance (“to come from”) — which enables a user to establish trust in an information product that is obtained by fusing raw data from one or more information sources (with varying degrees of trust). In particular, we examine a semi-ring model for provenance that allows us to quantify and compare “provenance levels” and propose a novel approach to support provenance queries in DTNs using a cooperative in-network caching approach. To address the challenges of opportunistic network connectivity in DTNs, our basic idea is to intentionally cache both data and its provenance at a set of Network Central Locations (NCLs), which can be easily accessed by other nodes in the network. We propose an effective scheme which ensures appropriate NCL selection based on a probabilistic selection metric, and furthermore coordinate multiple caching nodes to optimize the tradeoff between quality (provenance level), data accessibility and caching overhead. By extensive trace-driven simulations, we show that our proposed caching scheme significantly improves the performance of data access, in terms of the provenance level and data access delay, compared to existing schemes.