Minimizing Latency in Fault-Tolerant Distributed Stream Processing Systems

Research output: Contribution to conferencesPaperContributedpeer-review

Contributors

Abstract

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

Details

Original languageEnglish
Pages173-182
Number of pages10
Publication statusPublished - 2009
Peer-reviewedYes

Conference

Title2009 29th IEEE International Conference on Distributed Computing Systems
Abbreviated titleICDCS 2009
Conference number29
Duration22 - 26 June 2009
Degree of recognitionInternational event
CityMontreal
CountryCanada

External IDs

Scopus 70350222222

Keywords

Research priority areas of TU Dresden

DFG Classification of Subject Areas according to Review Boards