TurboStream: Towards Low-Latency Data Stream Processing
暂无分享,去创建一个
Hai Jin | Fei Chen | Shadi Ibrahim | Song Wu | Lin Gu | Zhiyi Liu | Mi Liu | M. Liu | Hai Jin | Song Wu | S. Ibrahim | Lin Gu | Fei Chen | Zhiyi Liu
[1] Margo I. Seltzer,et al. Network-Aware Operator Placement for Stream-Processing Systems , 2006, 22nd International Conference on Data Engineering (ICDE'06).
[2] Dhabaleswar K. Panda,et al. High performance RDMA-based design of HDFS over InfiniBand , 2012, 2012 International Conference for High Performance Computing, Networking, Storage and Analysis.
[3] Seif Haridi,et al. Apache Flink™: Stream and Batch Processing in a Single Engine , 2015, IEEE Data Eng. Bull..
[4] Jignesh M. Patel,et al. Storm@twitter , 2014, SIGMOD Conference.
[5] Richard T. B. Ma,et al. Smooth Task Migration in Apache Storm , 2015, SIGMOD Conference.
[6] Shrideep Pallickara,et al. Online Scheduling and Interference Alleviation for Low-Latency, High-Throughput Processing of Data Streams , 2017, IEEE Transactions on Parallel and Distributed Systems.
[7] Guillaume Mercier,et al. Cache-Efficient, Intranode, Large-Message MPI Communication with MPICH2-Nemesis , 2009, 2009 International Conference on Parallel Processing.
[8] Bingsheng He,et al. AdaStorm: Resource Efficient Storm with Adaptive Configuration , 2017, 2017 IEEE 33rd International Conference on Data Engineering (ICDE).
[9] Cong Xu,et al. JVM-Bypass for Efficient Hadoop Shuffling , 2013, 2013 IEEE 27th International Symposium on Parallel and Distributed Processing.
[10] Mohammad Hosseini,et al. R-Storm: Resource-Aware Scheduling in Storm , 2015, Middleware.
[11] Jian Tang,et al. T-Storm: Traffic-Aware Online Scheduling in Storm , 2014, 2014 IEEE 34th International Conference on Distributed Computing Systems.
[12] Kun-Lung Wu,et al. SODA: An Optimizing Scheduler for Large-Scale Stream-Based Distributed Computer Systems , 2008, Middleware.
[13] Jignesh M. Patel,et al. Twitter Heron: Stream Processing at Scale , 2015, SIGMOD Conference.
[14] Thomas S. Heinze,et al. Latency-aware elastic scaling for distributed data stream processing systems , 2014, DEBS '14.
[15] Sayantan Sur,et al. LiMIC: support for high-performance MPI intra-node communication on Linux cluster , 2005, 2005 International Conference on Parallel Processing (ICPP'05).
[16] Anthony Skjellum,et al. A High-Performance, Portable Implementation of the MPI Message Passing Interface Standard , 1996, Parallel Comput..
[17] George Bosilca,et al. Locality and Topology Aware Intra-node Communication among Multicore CPUs , 2010, EuroMPI.
[18] John D. Valois. Lock-free linked lists using compare-and-swap , 1995, PODC '95.
[19] Raul Castro Fernandez,et al. Making State Explicit for Imperative Big Data Processing , 2014, USENIX Annual Technical Conference.
[20] Guillaume Mercier,et al. Design and evaluation of Nemesis, a scalable, low-latency, message-passing communication subsystem , 2006, Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID'06).
[21] Raul Castro Fernandez,et al. Integrating scale out and fault tolerance in stream processing using operator state management , 2013, SIGMOD '13.
[22] Roberto Baldoni,et al. Adaptive online scheduling in storm , 2013, DEBS.
[23] Kun-Lung Wu,et al. Elastic scaling of data parallel operators in stream processing , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.
[24] Hai Jin,et al. Runtime‐aware adaptive scheduling in stream processing , 2016, Concurr. Comput. Pract. Exp..