Galileo: Scalable Storage of Time-Series Multidimensional Data



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[20]	Thilina Buddhika, Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara. Synopsis: A Distributed Sketch over Voluminous Spatiotemporal Observational Streams. (To appear) IEEE Transactions on Knowledge and Data Engineering. 2017.
[19]	Matthew Malensek, Sangmi Pallickara, and Shrideep Pallickara. Fast, Ad Hoc Query Evaluations over Multidimensional Geospatial Datasets. IEEE Transactions on Cloud Computing. Vol. 5(1) pp 28-42. 2017.
[18]	Walid Budgaga, Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara. A Framework for Scalable Real-Time Anomaly Detection over Voluminous, Geospatial Data Streams. Concurrency and Computation: Practice & Experience.* John-Wiley. Vol. 29(12) pp 1-16. John-Wiley. 2017.
[17]	Naman Shah, Harshil Shah, Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara. Network Analysis for Identifying and Characterizing Disease Outbreak Influence from Voluminous Epidemiology Data. Proceedings of the IEEE International Conference on Big Data (IEEE BigData). Washington D.C., USA. 2016.
[16]	Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara. Analytic Queries over Geospatial Time-Series Data using Distributed Hash Tables. IEEE Transactions on Knowledge and Data Engineering. Vol 28(6) pp 1408-1422. 2016.
[15]	Cameron Tolooee, Matthew Malensek, and Sangmi Pallickara. A Scalable Framework for Continuous Query Evaluations over Multidimensional, Scientific Datasets. Concurrency and Computation: Practice and Experience. Vol 28(8) pp. 2546-2563. 2016.
[14]	Matthew Malensek, Sangmi Pallickara, and Shrideep Pallickara. Autonomous Data Management and Federation to Support High-throughput Query Evaluations over Voluminous Datasets. Special Issue on Autonomic Clouds. IEEE Cloud Computing. Vol 3(3) pp 40-49. 2016.
[13]	Walid Budgaga, Matthew Malensek, Sangmi Pallickara, Neil Harvey, Jay Breidt, and Shrideep Pallickara. Predictive Analytics Using Statistical, Learning, and Ensemble Methods to Support Real-Time Exploration of Discrete Event Simulations. Future Generation Computer Systems. Elsevier. Volume 56, March, Pages 360–374. 2016.
[12]	Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara. Minerva: Proactive Disk Scheduling for QoS in Multi-Tier, Multi-Tenant Cloud Environments. IEEE Internet Computing. Vol 20 (3) pp 19-27. 2016.
[11]	Matthew Malensek, Sangmi Pallickara and Shrideep Pallickara. Alleviation of Disk I/O Contention in Virtualized Settings for Data-Intensive Computing. Proceedings of the IEEE/ACM International Symposium on Big Data Computing. Cyprus. 2015.
[10]	Jared Koontz, Matthew Malensek, and Sangmi Lee Pallickara. GeoLens: Enabling Interactive Visual Analytics over Large-scale, Multidimensional Geospatial Datasets. Proceedings of the IEEE/ACM Symposium on Big Data Computing. London, UK. 2014. **Best Paper Award
[9]	Matthew Malensek, Walid Budgaga, Sangmi Pallickara, Neil Harvey, Jay Bredit, and Shrideep Pallickara. Using Distributed Analytics to Enable Real-Time Exploration of Discrete Event Simulations. Proceedings of the IEEE/ACM Conference on Utility and Cloud Computing. London, UK. 2014.
[8]	Matthew Malensek, Sangmi Pallickara, and Shrideep Pallickara. Geometry and Proximity Constrained Query Evaluations over Large Geospatial Datasets Using Distributed Hash Tables. IEEE Computing in Science and Engineering (CiSE). Special Issue on Extreme Data. Vol. 16(4) pp 53-60. 2014.
[7]	Cameron Tolooee, Matthew Malensek, and Sangmi Pallickara. A Framework for Managing Continuous Query Evaluations over Voluminous, Multidimensional Datasets. Proceedings of the IEEE Cloud and Autonomic Computing Conference. London, UK. 2014.
[6]	Matthew Malensek, Sangmi Pallickara and Shrideep Pallickara. Polygon-Based Query Evaluation over Geospatial Data Using Distributed Hash Tables. Proceedings of the IEEE/ACM Conference on Utility and Cloud Computing. Dresden, Germany. 2013.
[5]	Matthew Malensek, Sangmi Pallickara and Shrideep Pallickara. Autonomously Improving Query Evaluations over Multidimensional Data in Distributed Hash Tables. Proceedings of the ACM Cloud and Autonomic Computing Conference. Miami, USA. 2013.
[4]	Matthew Malensek, Sangmi Pallickara, and Shrideep Pallickara. Exploiting Geospatial and Chronological Characteristics in Data Streams to Enable Efficient Storage and Retrievals. Future Generation Computer Systems. Vol 29(4): 1049-1061. Elsevier. 2013.
[3]	Matthew Malensek, Sangmi Pallickara, and Shrideep Pallickara. Expressive Query Support for Multidimensional Data in Distributed Hash Tables. Proceedings of the IEEE/ACM Conference on Utility and Cloud Computing. pp 31-38. Chicago, USA. 2012. **Best Paper Award
[2]	Sangmi Pallickara, Matthew Malensek and Shrideep Pallickara. Enabling Access to Time-Series, Geospatial Data for On Demand Visualization. Proceedings of the IEEE Symposium on Large-Scale Data Analysis and Visualization, Providence, Rhode Island. 2011.
[1]	Matthew Malensek, Sangmi Pallickara, and Shrideep Pallickara. Galileo: A Framework for Distributed Storage of High-Throughput Data Streams. Proceedings of the IEEE/ACM Conference on Utility and Cloud Computing. Melbourne, Australia. 2011.