Update-Aware Scheduling Algorithms for Hierarchical Data Dissemination Systems

Mechanisms to efficiently and effectively transmit up-todate information to clients are of significant interest. Broadcast-based scheduling in hierarchical data dissemination systems are under reported in the literature. In these systems a primary server accepts updates that are broadcast to secondary servers and then to a population of clients upon requests. This paper focuses on data dissemination with update propagation at the primary server side. Our initial study shows that at high update rates, a straightforward broadcast scheduler that ignores clients´ access patterns can provide clients with outdated information more than 80% of the time. We propose three broadcast scheduling algorithms that primarily differ in how data dissemination with update propagation is guided at the primary and secondary servers. We present mechanisms based on real and predicted clients´ access patterns. We evaluate the new scheduling algorithms by running an extensive set of experiments. The performance study illustrates that the third algorithm, which depends on predictive scheduling at both the primary and the secondary servers, provides the best response time and the reception of up-to-date information.