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Work-efficient Batch-incremental Minimum Spanning Trees with Applications to the Sliding Window Model [article]

Daniel Anderson, Guy E. Blelloch, Kanat Tangwongsan
2020 arXiv   pre-print
Using our batch-incremental MST algorithm, we demonstrate a range of applications that become efficiently solvable in parallel in the sliding-window model, such as graph connectivity, approximate MSTs,  ...  In this paper, we present the first work-efficient parallel batch-dynamic algorithm for incremental MST, which can insert ℓ edges in O(ℓlog(1+n/ℓ)) work in expectation and O(polylog(n)) span w.h.p.  ...  Acknowledgements This work was supported in part by NSF grants CCF-1408940 and CCF-1629444. The authors would like to thank Ticha Sethapakdi for helping with the figures.  ... 
arXiv:2002.05710v1 fatcat:fqp6urbg5fcaxaajdsapoysr4q

Slider

Pramod Bhatotia, Umut A. Acar, Flavio P. Junqueira, Rodrigo Rodrigues
2014 Proceedings of the 15th International Middleware Conference on - Middleware '14  
When pairs of consecutive windows overlap, there is a potential to update the output incrementally, more efficiently than recomputing from scratch.  ...  However, in most systems, realizing this potential requires programmers to explicitly manage the intermediate state for overlapping windows, and devise an application-specific algorithm to incrementally  ...  Acknowledgements We are thankful to Paarijaat Aditya, Marcel Dischinger, and Farshad Kooti for helping us with the evaluation of the case studies.  ... 
doi:10.1145/2663165.2663334 dblp:conf/middleware/BhatotiaAJR14 fatcat:td5fiak5yjhrhcl4gu6awsz7v4

A Review: Frequent Pattern Mining Techniques in Static and Stream Data Environment

, Simarpreet, Varun Singla
2016 Indian Journal of Science and Technology  
The problems like concept drifting, nature of data, its processing model, inadequacy, size, its retention in warehouses etc. are also required to be taken into account while working with real time data  ...  A confidence defines if a person purchases any item M, how many times he purchases item N with it 1 . Minimum confidence value is set to validate associations.  ...  The algorithm uses sliding window model to mine the most recent data. The model works by putting transactions into batches. A sliding window is composed of a number of basic windows.  ... 
doi:10.17485/ijst/2016/v9i45/106350 fatcat:v2qym4qpcndfbgyzb3rmx35axq

Regular Path Query Evaluation on Streaming Graphs [article]

Anil Pacaci, Angela Bonifati, M. Tamer Özsu
2020 arXiv   pre-print
We adopt the Regular Path Query (RPQ) model that specifies navigational patterns with labeled constraints.  ...  Experimental analysis on real and synthetic streaming graphs shows that the proposed algorithms can process up to tens of thousands of edges per second and efficiently answer RPQs that are commonly used  ...  The proposed algorithms incrementally maintain query answers as the window slides thus eliminating the computational overhead of the naive strategy of batch computation after each window movement.  ... 
arXiv:2004.02012v1 fatcat:733z3i5w6bcb5dx6rbhi2nd6eu

GASSER: An Auto-Tunable System for General Sliding-Window Streaming Operators on GPUs

Tiziano De Matteis, Gabriele Mencagli, Daniele De Sensi, Massimo Torquati, Marco Danelutto
2019 IEEE Access  
INDEX TERMS Data stream processing, sliding-window queries, GPU processing, autotuning, selfconfiguring systems.  ...  Furthermore, Gasser provides an auto-tuning approach able to automatically find the optimal value of the configuration parameters (i.e., batch length and the degree of parallelism) needed to optimize throughput  ...  However, the system does not support sliding window since windows span across several batches.  ... 
doi:10.1109/access.2019.2910312 fatcat:l377xhz3ybg4ray3qbwt47teii

Efficient anomaly monitoring over moving object trajectory streams

Yingyi Bu, Lei Chen, Ada Wai-Chee Fu, Dawei Liu
2009 Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '09  
Then, we utilize the local continuity characteristics of trajectories to build local clusters upon trajectory streams and monitor anomalies via efficient pruning strategies.  ...  Our extensive experiments demonstrate the effectiveness and efficiency of our methods.  ...  by v VP-trees, from VP-tree 1 to Vp-tree v, except some boundary ones near the start or end of the sliding window.  ... 
doi:10.1145/1557019.1557043 dblp:conf/kdd/BuCFL09 fatcat:zp4jfgxpujdwfof5psysqyfjd4

Memory-adaptive high utility sequential pattern mining over data streams

Morteza Zihayat, Yan Chen, Aijun An
2017 Machine Learning  
Furthermore, in order to show the effectiveness and efficiency of MAHUSP in real-life applications, we apply our proposed algorithm to a web clickstream dataset obtained from a Canadian news portal to  ...  Our experimental study shows that our algorithm can not only discover HUSPs over data streams efficiently, but also adapt to memory allocation with limited sacrifices in the quality of discovered HUSPs  ...  The sliding window model captures a fixed number of most recent records (e.g., instances/batches of instances) in a window, and it focuses on discovering the patterns within the window.  ... 
doi:10.1007/s10994-016-5617-1 fatcat:vymcebqsq5bv7fyaa6lfwsxsae

Incremental Bayesian network structure learning in high dimensional domains

Amanullah Yasin, Philippe Leray
2013 2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)  
There are few works addressing this issue and they differs with respect to the way of dealing with incrementality. Some works consider sliding windows, i.e.  ...  For this reason, incremental learning algorithms are needed in order to efficiently integrate the novel data with the existing knowledge.  ... 
doi:10.1109/icmsao.2013.6552635 fatcat:5bvt6lavgjdlnpfetaybqty44q

Incremental mining of sequential patterns: Progress and challenges

Bhawna Mallick, Deepak Garg, P.S. Grover
2013 Intelligent Data Analysis  
Sequential pattern mining is a vital problem with broad applications.  ...  The three more relevant algorithms, based on this approach, are also studied in depth along with the other work done in this area. This would give scope for future research direction.  ...  ICspan algorithm, hence proposed the use of sliding window model that sample the data from the input stream into units.  ... 
doi:10.3233/ida-130591 fatcat:ituubtk5ujca3bxmrxyl44zgdm

Underwater Sonar Signals Recognition by Incremental Data Stream Mining with Conflict Analysis

Simon Fong, Suash Deb, Raymond Wong, Guangmin Sun
2014 International Journal of Distributed Sensor Networks  
Classification algorithms in traditional data mining approach offer fair accuracy by training a classification model with the full dataset, in batches.  ...  Since sonar signal data streams can amount to infinity, the data preprocessing time must be kept to a minimum to fulfill the need for high speed.  ...  Acknowledgments The authors are thankful for the financial support from the Research Grant "Adaptive OVFDT with Incremental Pruning and ROC Corrective Learning for Data Stream Mining, " Grant no.  ... 
doi:10.1155/2014/635834 fatcat:f5yrdjo2wfhi5hsmqenwomr2wi

Efficient Incremental Computation of Aggregations over Sliding Windows

Chao Zhang, Reza Akbarinia, Farouk Toumani
2021 Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining  
compute sliding window aggregations efficiently.  ...  PBA runs in 𝑂 (1) time, performing at most 3 merging operations per slide while consuming 𝑂 (𝑛) space for windows with 𝑛 partial aggregations.  ...  ACKNOWLEDGMENTS This research was financed by the French government IDEX-ISITE initiative 16-IDEX-0001 (CAP 20-25).  ... 
doi:10.1145/3447548.3467360 fatcat:szdsgp2wvrgerctgbiytdhq4du

Real-Time Detection of In-flight Aircraft Damage

Brenton Blair, Herbert K. H. Lee, Misty Davies
2017 Journal of Classification  
Random Forests provide a computationally efficient approach with sufficient accuracy to be able to detect and classify the different scenarios in real-time.  ...  We demonstrate our approach by classifying realizations of a 45 degree bank angle generated from the Generic Transport Model flight simulator in collaboration with NASA.  ...  Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement by the United States Government  ... 
doi:10.1007/s00357-017-9237-7 fatcat:fvcmeyz5x5dmzctkilfqe2agqq

SABER

Alexandros Koliousis, Matthias Weidlich, Raul Castro Fernandez, Alexander L. Wolf, Paolo Costa, Peter Pietzuch
2016 Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16  
It must do this while respecting the semantics of streaming SQL queries, in particular with regard to window handling.  ...  Such heterogeneous architectures have the potential to improve the performance of data-intensive stream processing applications, but they are not supported by current relational stream processing engines  ...  For sliding windows, tasks perform incremental computation on the windows in a batch to avoid redundant computation.  ... 
doi:10.1145/2882903.2882906 dblp:conf/sigmod/KoliousisWFWCP16 fatcat:x5oopplx3zepto4zttbwspbl6a

Continuous Prediction of Closed Frequent Itemsets from High speed Distributed Data Streams using Parallel Mining on Manifold Windows with Varying Size

V. SiddaReddy, T.V. Rao, A.Govardhan A.Govardhan
2014 International Journal of Computer Applications  
Continuous prediction of closed frequent itemsets from high speed distributed data streams is an active research work, which is because of the conflict to the process time taken to perform mining consistent  ...  The said model is referred as Parallel Closed Frequent Itemsets Mining (PCFIM) over High Speed Distributed Data streams by Manifold Varying Size Windows (MVSW).  ...  ACKNOWLEDGMENTS The authors would like to thank the anonymous reviewers for their valuable comments. We also thank the authors of all references for helping us setup the paper.  ... 
doi:10.5120/17662-8479 fatcat:ykuilwrrpfbqbipdnivignntx4

Dynamic diversification of continuous data

Marina Drosou, Evaggelia Pitoura
2012 Proceedings of the 15th International Conference on Extending Database Technology - EDBT '12  
The diversification problem is in general NP-complete; we provide theoretical bounds that characterize the quality of our solution based on cover trees with respect to the optimal solution.  ...  Finally, we report experimental results concerning the efficiency and effectiveness of our approach on a variety of real and synthetic datasets.  ...  We would like to thank the authors of [23] for providing us with their version of the "Faces" dataset.  ... 
doi:10.1145/2247596.2247623 dblp:conf/edbt/DrosouP12 fatcat:ddcexve755c4ndowhyrdtyeod4
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