Many Cloud providers have data centers located in different geographical regions. Supporting global-scale applications with low-latency needs (such as world-scale games) relying on a publish/subscribe paradigm brings many challenges.
MultiPub aims at proposing a fine-grained model for minimizing latencies in the context of wide-area topic-based pub/sub applications. MultiPub takes advantage of multiple “Clouds” in different geographical regions in order to respect a predefined delivery time bound while minimizing Cloud-based costs. MultiPub includes a prediction model for latencies between arbitrary pairs of clients and publication servers. Latency optimization is done on a per-topic basis where topics are seamlessly migrated or replicated between Clouds, whenever needed.
A simulator tool was built in order to perform large-scale experiments, which we plan to open-source in the near-future. Furthermore, a Cloud-based implementation taking advantage of multiple Amazon EC2 regions was also built in order to assess the validity of our results in a real multi-Cloud setting. Our results showed that MultiPub was able to significantly reduce bandwidth-related costs while respecting predefined delivery time constraints, and that it performed better than other approaches.
Julien Gascon-Samson 