Heuristics for Flash-Dissemination in Heterogenous Networks

Flash Dissemination is a particularly useful form of data broadcast that arises in many mission-critical applications. The goal is rapid distribution of medium amounts of data in as short a time period as possible. While optimal algorithms are available for a highly constrained case (all nodes having the same bandwidth and latency), there is relatively little work in the context of heterogenous networks. Most systems and protocols today either use trees or randomized mesh-based techniques to deal with heterogeneity and mostly work with local knowledge. We argue that a protocol with global knowledge can perform much better. In this paper, we propose two centralized heuristics – DIM-Rank and DIM-Time that use global knowledge to schedule data transfer between nodes. The heuristics are based upon insights from broadcast theory. We perform detailed experimental evaluation of these two heuristics with two decentralized randomized approaches, CREW and NOD. Currently, CREW is the one of the fastest decentralized flash-dissemination protocols. Our experiments show that DIM-Rank is better among the two centralized heuristics and achieves faster dissemination than CREW and NOD across a range of heterogeneity