Okeanos: wasteless journaling for fast and reliable multistream storage
USENIXATC'11 Proceedings of the 2011 USENIX conference on USENIX annual technical conference
Mining large distributed log data in near real time
SLAML '11 Managing Large-scale Systems via the Analysis of System Logs and the Application of Machine Learning Techniques
Improving Bandwidth Efficiency for Consistent Multistream Storage
ACM Transactions on Storage (TOS)
Rollback-recovery without checkpoints in distributed event processing systems
Proceedings of the 7th ACM international conference on Distributed event-based systems
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Event stream processing (ESP) applications target the real-time processing of huge amounts of data. Events traverse a graph of stream processing operators where the information of interest is extracted. As these applications gain popularity, the requirements for scalability, availability, and dependability increase. In terms of dependability and availability, many applications require a precise recovery, i.e., a guarantee that the outputs during and after a recovery would be the same as if the failure that triggered recovery had never occurred. Existing solutions for precise recovery induce prohibitive latency costs, either by requiring continuous checkpoint or logging (in a passive replication approach) or perfect synchronization between replicas executing the same operations (in an active replication approach). We introduce a novel technique to guarantee precise recovery for ESP applications while minimizing the latency costs as compared to traditional approaches. The technique minimizes latencies via speculative execution in a distributed system. In terms of scalability, the key component of our approach is a modified software transactional memory that provides not only the speculation capabilities but also optimistic parallelization for costly operations.