| Execution time estimation for workflow scheduling AM Chirkin, ASZ Belloum, SV Kovalchuk, MX Makkes, MA Melnik, ... Future generation computer systems 75, 376-387, 2017 | 122 | 2017 |
| Distributed data-driven platform for urgent decision making in cardiological ambulance control SV Kovalchuk, E Krotov, PA Smirnov, DA Nasonov, AN Yakovlev Future Generation Computer Systems 79, 144-154, 2018 | 49 | 2018 |
| Blockchain-based transaction integrity in distributed big data marketplace D Nasonov, AA Visheratin, A Boukhanovsky Computational Science–ICCS 2018: 18th International Conference, Wuxi, China …, 2018 | 48 | 2018 |
| Workflow scheduling algorithms for hard-deadline constrained cloud environments AA Visheratin, M Melnik, D Nasonov Procedia Computer Science 80, 2098-2106, 2016 | 41 | 2016 |
| Performance-aware scheduling of streaming applications using genetic algorithm P Smirnov, M Melnik, D Nasonov Procedia Computer Science 108, 2240-2249, 2017 | 38 | 2017 |
| Workflow scheduling using neural networks and reinforcement learning M Melnik, D Nasonov Procedia computer science 156, 29-36, 2019 | 36 | 2019 |
| Hybrid evolutionary workflow scheduling algorithm for dynamic heterogeneous distributed computational environment D Nasonov, N Butakov, M Balakhontseva, K Knyazkov, AV Boukhanovsky International Joint Conference SOCO’14-CISIS’14-ICEUTE’14: Bilbao, Spain …, 2014 | 28 | 2014 |
| Evaluation of modern tools and techniques for storing time-series data A Struckov, S Yufa, AA Visheratin, D Nasonov Procedia Computer Science 156, 19-28, 2019 | 27 | 2019 |
| Adaptive performance model for dynamic scaling Apache Spark Streaming M Petrov, N Butakov, D Nasonov, M Melnik Procedia Computer Science 136, 109-117, 2018 | 26 | 2018 |
| CLAVIRE: îáëà÷íàÿ ïëàòôîðìà äëÿ îáðàáîòêè äàííûõ áîëüøèõ îáúåìîâ ÂÍ Âàñèëüåâ, Ê Êíÿçüêîâ, ÒÍ ×óðîâ, ÄÀ Íàñîíîâ, Ñ Ìàðüèí, ... Èíôîðìàöèîííî-èçìåðèòåëüíûå è óïðàâëÿþùèå ñèñòåìû 10 (11), 7-16, 2012 | 24 | 2012 |
| Hybrid scheduling algorithm in early warning systems D Nasonov, N Butakov Procedia Computer Science 29, 1677-1687, 2014 | 22 | 2014 |
| Hybrid scheduling algorithm in early warning systems AA Visheratin, M Melnik, D Nasonov, N Butakov, AV Boukhanovsky Future Generation Computer Systems 79, 630-642, 2018 | 21 | 2018 |
| Interactive workflow-based infrastructure for urgent computing KV Knyazkov, DA Nasonov, TN Tchurov, AV Boukhanovsky Procedia Computer Science 18, 2223-2232, 2013 | 21 | 2013 |
| A clustering-based approach to static scheduling of multiple workflows with soft deadlines in heterogeneous distributed systems K Bochenina, N Butakov, A Dukhanov, D Nasonov Procedia Computer Science 51, 2827-2831, 2015 | 18 | 2015 |
| Data preloading and data placement for MapReduce performance improving A Spivak, D Nasonov Procedia Computer Science 101, 379-387, 2016 | 17 | 2016 |
| Multiscale event detection using convolutional quadtrees and adaptive geogrids AA Visheratin, KD Mukhina, AK Visheratina, D Nasonov, ... Proceedings of the 2nd ACM SIGSPATIAL Workshop on Analytics for Local Events …, 2018 | 16 | 2018 |
| Unified domain-specific language for collecting and processing data of social media N Butakov, M Petrov, K Mukhina, D Nasonov, S Kovalchuk Journal of Intelligent Information Systems 51, 389-414, 2018 | 16 | 2018 |
| Hard-deadline constrained workflows scheduling using metaheuristic algorithms A Visheratin, M Melnik, N Butakov, D Nasonov Procedia Computer Science 66, 506-514, 2015 | 15 | 2015 |
| Peregreen–modular database for efficient storage of historical time series in cloud environments A Visheratin, A Struckov, S Yufa, A Muratov, D Nasonov, N Butakov, ... 2020 USENIX Annual Technical Conference (USENIX ATC 20), 589-601, 2020 | 14 | 2020 |
| Orienteering problem with functional profits for multi-source dynamic path construction KD Mukhina, AA Visheratin, D Nasonov PloS one 14 (4), e0213777, 2019 | 14 | 2019 |
Alexander VisheratinBeehive AIVerified email at beehive.ai
