Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Geldenhuys, Morgan K."'
Distributed Stream Processing (DSP) systems are capable of processing large streams of unbounded data, offering high throughput and low latencies. To maintain a stable Quality of Service (QoS), these systems require a sufficient allocation of resourc
Externí odkaz:
http://arxiv.org/abs/2403.02093
Publikováno v:
IEEE IC2E (2023) 202-211
Stream processing has become a critical component in the architecture of modern applications. With the exponential growth of data generation from sources such as the Internet of Things, business intelligence, and telecommunications, real-time process
Externí odkaz:
http://arxiv.org/abs/2307.14287
Distributed Stream Processing systems have become an essential part of big data processing platforms. They are characterized by the high-throughput processing of near to real-time event streams with the goal of delivering low-latency results and thus
Externí odkaz:
http://arxiv.org/abs/2206.09679
Autor:
Geldenhuys, Morgan K., Pfister, Benjamin J. J., Scheinert, Dominik, Thamsen, Lauritz, Kao, Odej
Distributed Stream Processing systems are becoming an increasingly essential part of Big Data processing platforms as users grow ever more reliant on their ability to provide fast access to new results. As such, making timely decisions based on these
Externí odkaz:
http://arxiv.org/abs/2109.02340
Autor:
Scheinert, Dominik, Zhu, Houkun, Thamsen, Lauritz, Geldenhuys, Morgan K., Will, Jonathan, Acker, Alexander, Kao, Odej
Publikováno v:
IEEE IPCCC (2021) 1-8
Distributed dataflow systems like Spark and Flink enable the use of clusters for scalable data analytics. While runtime prediction models can be used to initially select appropriate cluster resources given target runtimes, the actual runtime performa
Externí odkaz:
http://arxiv.org/abs/2108.12211
Autor:
Geldenhuys, Morgan K., Will, Jonathan, Pfister, Benjamin J. J., Haug, Martin, Scharmann, Alexander, Thamsen, Lauritz
The Internet of Things describes a network of physical devices interacting and producing vast streams of sensor data. At present there are a number of general challenges which exist while developing solutions for use cases involving the monitoring an
Externí odkaz:
http://arxiv.org/abs/2108.10721
Publikováno v:
IEEE/ACM CloudIntelligence (2021) 7-12
Operation and maintenance of large distributed cloud applications can quickly become unmanageably complex, putting human operators under immense stress when problems occur. Utilizing machine learning for identification and localization of anomalies i
Externí odkaz:
http://arxiv.org/abs/2103.05245
Autor:
Geldenhuys, Morgan K., Pfister, Benjamin J. J., Scheinert, Dominik, Thamsen, Lauritz, Kao, Odej
Publikováno v:
Annals of Computer Science and Information Systems.
Distributed Stream Processing systems are becoming an increasingly essential part of Big Data processing platforms as users grow ever more reliant on their ability to provide fast access to new results. As such, making timely decisions based on these
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5717a1befa90d2965477f72d61c8d46
https://doi.org/10.15439/2022f225
https://doi.org/10.15439/2022f225
