Window-based data parallelization in complex event processing
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[1] M. Tamer Özsu,et al. Adaptive input admission and management for parallel stream processing , 2013, DEBS.
[2] Rajkumar Buyya,et al. Cost of Virtual Machine Live Migration in Clouds: A Performance Evaluation , 2009, CloudCom.
[3] Ramakrishna Varadarajan,et al. The Vertica Analytic Database: C-Store 7 Years Later , 2012, Proc. VLDB Endow..
[4] Scott Shenker,et al. Discretized Streams: An Efficient and Fault-Tolerant Model for Stream Processing on Large Clusters , 2012, HotCloud.
[5] Gabriele Mencagli. A Game-Theoretic Approach for Elastic Distributed Data Stream Processing , 2016, TAAS.
[6] Kurt Rothermel,et al. Supporting Strong Reliability for Distributed Complex Event Processing Systems , 2011, 2011 IEEE International Conference on High Performance Computing and Communications.
[7] Holger Ziekow,et al. The DEBS 2014 grand challenge , 2014, DEBS '14.
[8] Armin Zimmermann,et al. Flexible On-Board Stream Processing for Automotive Sensor Data , 2010, IEEE Transactions on Industrial Informatics.
[9] Kurt Rothermel,et al. Moving range queries in distributed complex event processing , 2012, DEBS.
[10] Matthias Weidlich,et al. Discovery and Validation of Queueing Networks in Scheduled Processes , 2015, CAiSE.
[11] Björn Schilling,et al. Efficient and secure event correlation in heterogeneous environments , 2015 .
[12] Assaf Schuster,et al. Lazy evaluation methods for detecting complex events , 2015, DEBS.
[13] Nathan Kallus,et al. Predicting crowd behavior with big public data , 2014, WWW.
[14] Kurt Rothermel,et al. Minimizing Communication Overhead in Window-Based Parallel Complex Event Processing , 2017, DEBS.
[15] Matthias Weidlich,et al. Queue mining for delay prediction in multi-class service processes , 2015, Inf. Syst..
[16] Dominic Battré,et al. Nephele/PACTs: a programming model and execution framework for web-scale analytical processing , 2010, SoCC '10.
[17] Ruben Mayer,et al. Demo Abstract: Fog Computing for Improving User Application Interaction and Context Awareness , 2017, 2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation (IoTDI).
[18] Imrich Chlamtac,et al. Internet of things: Vision, applications and research challenges , 2012, Ad Hoc Networks.
[19] Kun-Lung Wu,et al. Elastic scaling of data parallel operators in stream processing , 2009, 2009 IEEE International Symposium on Parallel & Distributed Processing.
[20] Odej Kao,et al. Elastic Stream Processing with Latency Guarantees , 2015, 2015 IEEE 35th International Conference on Distributed Computing Systems.
[21] Hari Balakrishnan,et al. Choreo: network-aware task placement for cloud applications , 2013, Internet Measurement Conference.
[22] Alessandro Margara,et al. Complex event processing with T-REX , 2012, J. Syst. Softw..
[23] Rajeev Motwani,et al. Operator scheduling in data stream systems , 2004, VLDB 2004.
[24] Beate Ottenwälder,et al. Mobility-awareness in complex event processing systems , 2016 .
[25] Andrey Brito,et al. Scalable and elastic realtime click stream analysis using StreamMine3G , 2014, DEBS '14.
[26] Martin Hirzel,et al. Partition and compose: parallel complex event processing , 2012, DEBS.
[27] Michael Stonebraker,et al. Operator Scheduling in a Data Stream Manager , 2003, VLDB.
[28] Kurt Rothermel,et al. Predictable Low-Latency Event Detection With Parallel Complex Event Processing , 2015, IEEE Internet of Things Journal.
[29] Shlomo Zilberstein,et al. Using Anytime Algorithms in Intelligent Systems , 1996, AI Mag..
[30] Tiziano De Matteis,et al. Keep calm and react with foresight: strategies for low-latency and energy-efficient elastic data stream processing , 2016, PPoPP.
[31] Peter R. Pietzuch,et al. Distributed complex event processing with query rewriting , 2009, DEBS '09.
[32] Sam Toueg,et al. Unreliable failure detectors for reliable distributed systems , 1996, JACM.
[33] Vincenzo Grassi,et al. Optimal Operator Replication and Placement for Distributed Stream Processing Systems , 2017, PERV.
[34] J. Le Boudec,et al. Adaptive load sharing for network processors , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.
[35] Ruben Mayer,et al. EmuFog: Extensible and scalable emulation of large-scale fog computing infrastructures , 2017, 2017 IEEE Fog World Congress (FWC).
[36] Rajkumar Buyya,et al. Article in Press Future Generation Computer Systems ( ) – Future Generation Computer Systems Cloud Computing and Emerging It Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility , 2022 .
[37] Alexander Artikis,et al. Event Forecasting with Pattern Markov Chains , 2017, DEBS.
[38] Rudolf Hornig,et al. An overview of the OMNeT++ simulation environment , 2008, Simutools 2008.
[39] Frank Dürr,et al. Solving the Multi-Operator Placement Problem in Large-Scale Operator Networks , 2010, 2010 Proceedings of 19th International Conference on Computer Communications and Networks.
[40] Owen Rambow,et al. Sentiment Analysis of Twitter Data , 2011 .
[41] Michael Philippsen,et al. Adaptive Speculative Processing of Out-of-Order Event Streams , 2014, TOIT.
[42] Alexander L. Wolf,et al. SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures , 2016, SIGMOD Conference.
[43] Ruben Mayer,et al. The Fog Makes Sense: Enabling Social Sensing Services with Limited Internet Connectivity , 2017, SocialSens@CPSWeek.
[44] Randy H. Katz,et al. A view of cloud computing , 2010, CACM.
[45] Alessandro Margara,et al. Processing flows of information: From data stream to complex event processing , 2012, CSUR.
[46] Navendu Jain,et al. Design, implementation, and evaluation of the linear road bnchmark on the stream processing core , 2006, SIGMOD Conference.
[47] Fred B. Schneider,et al. Implementing fault-tolerant services using the state machine approach: a tutorial , 1990, CSUR.
[48] Thomas S. Heinze,et al. Elastic Complex Event Processing under Varying Query Load , 2013, BD3@VLDB.
[49] Jignesh M. Patel,et al. Twitter Heron: Stream Processing at Scale , 2015, SIGMOD Conference.
[50] Kurt Rothermel,et al. Meeting predictable buffer limits in the parallel execution of event processing operators , 2014, 2014 IEEE International Conference on Big Data (Big Data).
[51] Antonio Iera,et al. The Internet of Things: A survey , 2010, Comput. Networks.
[52] Jeong-Hyon Hwang,et al. Fast and Highly-Available Stream Processing over Wide Area Networks , 2008, 2008 IEEE 24th International Conference on Data Engineering.
[54] M. Stephens. EDF Statistics for Goodness of Fit and Some Comparisons , 1974 .
[55] Kurt Rothermel,et al. Access Policy Consolidation for Event Processing Systems , 2013, 2013 Conference on Networked Systems.
[56] Sharma Chakravarthy,et al. Seamless Event and Data Stream Processing: Reconciling Windows and Consumption Modes , 2011, DASFAA.
[57] Jeong-Hyon Hwang,et al. Borealis-R: a replication-transparent stream processing system for wide-area monitoring applications , 2008, SIGMOD Conference.
[58] Pramod Bhatotia,et al. Slider: incremental sliding window analytics , 2014, Middleware.
[59] Jennifer Widom,et al. The CQL continuous query language: semantic foundations and query execution , 2006, The VLDB Journal.
[60] Kurt Rothermel,et al. MCEP: A Mobility-Aware Complex Event Processing System , 2014, ACM Trans. Internet Techn..
[61] Hua Chen,et al. Pingmesh: A Large-Scale System for Data Center Network Latency Measurement and Analysis , 2015, SIGCOMM.
[62] Andrey Brito,et al. User-Constraint and Self-Adaptive Fault Tolerance for Event Stream Processing Systems , 2015, 2015 45th Annual IEEE/IFIP International Conference on Dependable Systems and Networks.
[63] David Luckham,et al. The power of events - an introduction to complex event processing in distributed enterprise systems , 2002, RuleML.
[64] Fred B. Schneider,et al. The primary-backup approach , 1993 .
[65] Kostas Magoutis,et al. CEC: Continuous eventual checkpointing for data stream processing operators , 2011, 2011 IEEE/IFIP 41st International Conference on Dependable Systems & Networks (DSN).
[66] Massimo Franceschetti,et al. A Leader Election Protocol for Fault Recovery in Asynchronous Fully-Connected Networks , 1998 .
[67] Joseph M. Hellerstein,et al. MapReduce Online , 2010, NSDI.
[68] Guoqiang Mao,et al. Road traffic density estimation in vehicular networks , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).
[69] Andrey Brito,et al. Scalable and Low-Latency Data Processing with Stream MapReduce , 2011, 2011 IEEE Third International Conference on Cloud Computing Technology and Science.
[70] Kun-Lung Wu,et al. Auto-parallelizing stateful distributed streaming applications , 2012, 2012 21st International Conference on Parallel Architectures and Compilation Techniques (PACT).
[71] Andrey Brito,et al. Minimizing Latency in Fault-Tolerant Distributed Stream Processing Systems , 2009, 2009 29th IEEE International Conference on Distributed Computing Systems.
[72] Kurt Rothermel,et al. RECEP: selection-based reuse for distributed complex event processing , 2014, DEBS '14.
[73] Stanley B. Zdonik,et al. Staying FIT: Efficient Load Shedding Techniques for Distributed Stream Processing , 2007, VLDB.
[74] Tiziano De Matteis,et al. Parallel Patterns for Window-Based Stateful Operators on Data Streams: An Algorithmic Skeleton Approach , 2017, International Journal of Parallel Programming.
[75] Albert G. Greenberg,et al. Fault-tolerant stream processing using a distributed, replicated file system , 2008, Proc. VLDB Endow..
[76] Johannes Gehrke,et al. Fast Iterative Graph Computation with Block Updates , 2013, Proc. VLDB Endow..
[77] Andrey Brito,et al. Speculative out-of-order event processing with software transaction memory , 2008, DEBS.
[78] Kurt Rothermel,et al. Efficient and Distributed Rule Placement in Heavy Constraint-Driven Event Systems , 2011, 2011 IEEE International Conference on High Performance Computing and Communications.
[79] Srinath Perera,et al. Siddhi: a second look at complex event processing architectures , 2011, GCE '11.
[80] Michael Stonebraker,et al. A Comparison of Stream-Oriented High-Availability Algorithms , 2003 .
[81] Henk Tijms. New and old results for the M/D/c queue , 2006 .
[82] Robert Grimm,et al. A catalog of stream processing optimizations , 2014, ACM Comput. Surv..
[83] Samuel Kounev,et al. Self‐adaptive workload classification and forecasting for proactive resource provisioning , 2014, Concurr. Comput. Pract. Exp..
[84] Liang Tong,et al. A hierarchical edge cloud architecture for mobile computing , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.
[85] Christina A. Christie,et al. The Chi-Square Test , 2012 .
[86] Kurt Rothermel,et al. Knowledge Is at the Edge! How to Search in Distributed Machine Learning Models , 2017, OTM Conferences.
[87] David Maier,et al. Frames: data-driven windows , 2016, DEBS.
[88] Stanley B. Zdonik,et al. Window-aware load shedding for aggregation queries over data streams , 2006, VLDB.
[89] Kurt Rothermel,et al. GraphCEP: real-time data analytics using parallel complex event and graph processing , 2016, DEBS.
[90] Kun-Lung Wu,et al. Elastic Scaling for Data Stream Processing , 2014, IEEE Transactions on Parallel and Distributed Systems.
[91] Dror G. Feitelson,et al. Workload Modeling for Computer Systems Performance Evaluation , 2015 .
[92] Thomas S. Heinze,et al. Latency-aware elastic scaling for distributed data stream processing systems , 2014, DEBS '14.
[93] Claudio Soriente,et al. StreamCloud: An Elastic and Scalable Data Streaming System , 2012, IEEE Transactions on Parallel and Distributed Systems.
[94] Hitesh Ballani,et al. Towards predictable datacenter networks , 2011, SIGCOMM 2011.
[95] Thomas S. Heinze,et al. Auto-scaling techniques for elastic data stream processing , 2014, 2014 IEEE 30th International Conference on Data Engineering Workshops.
[96] Ruben Mayer,et al. StreamLearner: Distributed Incremental Machine Learning on Event Streams: Grand Challenge , 2017, DEBS.
[97] Alessandro Margara,et al. TESLA: a formally defined event specification language , 2010, DEBS '10.
[98] Bugra Gedik. Partitioning functions for stateful data parallelism in stream processing , 2013, The VLDB Journal.
[99] Tiziano De Matteis,et al. Elastic Scaling for Distributed Latency-Sensitive Data Stream Operators , 2017, 2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP).
[100] David Maier,et al. No pane, no gain: efficient evaluation of sliding-window aggregates over data streams , 2005, SGMD.
[101] Badrish Chandramouli,et al. Accurate latency estimation in a distributed event processing system , 2011, 2011 IEEE 27th International Conference on Data Engineering.
[102] Kun-Lung Wu,et al. Language level checkpointing support for stream processing applications , 2009, 2009 IEEE/IFIP International Conference on Dependable Systems & Networks.
[103] Raja Lavanya,et al. Fog Computing and Its Role in the Internet of Things , 2019, Advances in Computer and Electrical Engineering.
[104] Margo I. Seltzer,et al. Network-Aware Operator Placement for Stream-Processing Systems , 2006, 22nd International Conference on Data Engineering (ICDE'06).
[105] Kurt Rothermel,et al. Cordies: expressive event correlation in distributed systems , 2010, DEBS '10.
[106] Samuel Kounev,et al. Performance Modeling and Evaluation of Distributed Component-Based Systems Using Queueing Petri Nets , 2006, IEEE Transactions on Software Engineering.
[107] Raul Castro Fernandez,et al. Integrating scale out and fault tolerance in stream processing using operator state management , 2013, SIGMOD '13.
[108] Vincenzo Grassi,et al. Optimal operator placement for distributed stream processing applications , 2016, DEBS.
[109] Sharma Chakravarthy,et al. Snoop: An Expressive Event Specification Language for Active Databases , 1994, Data Knowl. Eng..
[110] Opher Etzion,et al. Amit - the situation manager , 2003, The VLDB Journal.
[111] Daniel Mills,et al. MillWheel: Fault-Tolerant Stream Processing at Internet Scale , 2013, Proc. VLDB Endow..
[112] Yanlei Diao,et al. High-performance complex event processing over streams , 2006, SIGMOD Conference.
[113] Ying Xing,et al. Scalable Distributed Stream Processing , 2003, CIDR.
[114] Themistoklis Charalambous,et al. Overload Management in Data Stream Processing Systems with Latency Guarantees , 2012, ICAC 2012.
[115] Leonardo Querzoni,et al. Load-aware shedding in stream processing systems , 2016, DEBS.
[116] Vincenzo Gulisano,et al. The DEBS 2017 Grand Challenge , 2017, DEBS.
[117] Michael Stonebraker,et al. Fault-tolerance in the borealis distributed stream processing system , 2008, ACM Trans. Database Syst..
[118] Tore Risch,et al. Massive scale-out of expensive continuous queries , 2011, Proc. VLDB Endow..
[119] Thomas S. Heinze,et al. Online parameter optimization for elastic data stream processing , 2015, SoCC.
[120] Sharma Chakravarthy,et al. LOAD SHEDDING IN DATA STREAM MANAGEMENT SYSTEMS , 2009 .
[121] Kurt Rothermel,et al. MigCEP: operator migration for mobility driven distributed complex event processing , 2013, DEBS.
[122] Ruben Mayer,et al. FogStore: Toward a distributed data store for Fog computing , 2017, 2017 IEEE Fog World Congress (FWC).
[123] Martin Hirzel,et al. Low-Latency Sliding-Window Aggregation in Worst-Case Constant Time , 2017, DEBS.
[124] Michael Stonebraker,et al. Load Shedding in a Data Stream Manager , 2003, VLDB.
[125] Alessandro Margara,et al. Low latency complex event processing on parallel hardware , 2012, J. Parallel Distributed Comput..
[126] Magdalena Balazinska,et al. Moirae: History-Enhanced Monitoring , 2007, CIDR.
[127] Kurt Rothermel,et al. Rollback-recovery without checkpoints in distributed event processing systems , 2013, DEBS '13.
[128] Yuan Yu,et al. Dryad: distributed data-parallel programs from sequential building blocks , 2007, EuroSys '07.
[129] Vincenzo Guerriero,et al. Power Law Distribution: Method of Multi-scale Inferential Statistics , 2012 .
[130] Andrey Brito,et al. Active Replication at (Almost) No Cost , 2011, 2011 IEEE 30th International Symposium on Reliable Distributed Systems.
[131] Nesime Tatbul,et al. Scalable Data Partitioning Techniques for Parallel Sliding Window Processing over Data Streams , 2011 .
[132] Rainer Unland,et al. On the semantics of complex events in active database management systems , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).
[133] Nesime Tatbul,et al. RIP: run-based intra-query parallelism for scalable complex event processing , 2013, DEBS.
[134] A. Taleb-Bendiab,et al. A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing , 2010, 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops.
[135] Seif Haridi,et al. Apache Flink™: Stream and Batch Processing in a Single Engine , 2015, IEEE Data Eng. Bull..