Results 1 to 10 of about 257 (146)
SPARQL2Flink: Evaluation of SPARQL Queries on Apache Flink [PDF]
Applied Sciences (Switzerland), 2021 Existing SPARQL query engines and triple stores are continuously improved to handle more massive datasets. Several approaches have been developed in this context proposing the storage and querying of RDF data in a distributed fashion, mainly using the ...
Oscar Ceballos +2 more
exaly +4 more sources
FlinkCheck: Property-Based Testing for Apache Flink [PDF]
IEEE Access, 2019 Apache Flink is an open-source, soft real-time stream processing framework underlying many modern systems dealing with cloud and real-time computing, data analytics, and the Internet of Things, among others. As the complexity of stream-processing systems
Enrique Martin-Martin +2 more
exaly +5 more sources
A stream processing abstraction framework [PDF]
Frontiers in Big Data, 2023 Real-time analysis of large multimedia streams is nowadays made efficient by the existence of several Big Data streaming platforms, like Apache Flink and Samza.
Ilaria Bartolini, Marco Patella
doaj +2 more sources
Apache Flink and clustering-based framework for fast anonymization of IoT stream data
Intelligent Systems With Applications, 2023 In this paper, we present a novel framework that considers the expiration period time of the Internet of Things (IoT) data stream to anonymize it. IoT stands among one of most fast-growing technology in the world. Also, anonymity is one of the safeguards
Mohsen Rahmani +2 more
exaly +3 more sources
Performance Evaluation Analysis of Spark Streaming Backpressure for Data-Intensive Pipelines [PDF]
Sensors, 2022 A significant rise in the adoption of streaming applications has changed the decision-making processes in the last decade. This movement has led to the emergence of several Big Data technologies for in-memory processing, such as the systems Apache Storm,
Kassiano J. Matteussi +3 more
doaj +2 more sources
FogGuru: a Fog Computing platform based on Apache Flink [PDF]
2020 23rd Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN), 2020 Fog computing infrastructure aims to offload computing resources from cloud providers by placing edge devices closer to end-users and/or data sources. Systems and methods for developing and deploying an application in Fog nodes are still in their infancy.
Battulga, Davaadorj +2 more
exaly +3 more sources
RTEDAP framework for real-time event-driven data aggregation and processing in tsunami early warning systems [PDF]
Scientific ReportsTsunami early warning systems are critical for minimizing the impact of seismic events on coastal communities. However, existing systems face challenges in terms of latency, scalability, and real-time data processing.
M. Umadevi +3 more
doaj +2 more sources
BigBench Workload Executed by using Apache Flink
Procedia Manufacturing, 2017 Abstract Many of the challenges that have to be faced in Industry 4.0 involve the management and analysis of huge amount of data (e.g. sensor data management and machine-fault prediction in industrial manufacturing, web-logs analysis in e-commerce). To handle the so-called Big Data management and analysis, a plethora of frameworks has been proposed ...
Luca Gagliardelli +2 more
exaly +4 more sources
Industry 4.0 towards Forestry 4.0: Fire Detection Use Case [PDF]
Sensors, 2021 Forestry 4.0 is inspired by the Industry 4.0 concept, which plays a vital role in the next industrial generation revolution. It is ushering in a new era for efficient and sustainable forest management.
Radhya Sahal +3 more
doaj +2 more sources
The construction of an integrated cloud network digital intelligence platform for rail transit based on artificial intelligence [PDF]
Scientific ReportsThis study presents the design and validation of a closed-loop control platform for rail transit construction. The platform integrates multi-source data, enables real-time prediction, and supports AI-driven scheduling, with strategy execution and ...
Keke Wang, Xin Zhou, Jianbo Guan
doaj +2 more sources