SPARQL2Flink: Evaluation of SPARQL Queries on Apache Flink [PDF]
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]
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 Martín-Martín +2 more
exaly +4 more sources
A stream processing abstraction framework [PDF]
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
Performance Evaluation Analysis of Spark Streaming Backpressure for Data-Intensive Pipelines [PDF]
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
Apache Flink and clustering-based framework for fast anonymization of IoT stream data
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
Alireza Sadeghi-Nasab +2 more
exaly +3 more sources
Industry 4.0 towards Forestry 4.0: Fire Detection Use Case [PDF]
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
Usages of Spark Framework with Different Machine Learning Algorithms. [PDF]
Sensors, satellites, mobile devices, social media, e‐commerce, and the Internet, among others, saturate us with data. The Internet of Things, in particular, enables massive amounts of data to be generated more quickly. The Internet of Things is a term that describes the process of connecting computers, smart devices, and other data‐generating equipment
Ali Mohamed M, El-Henawy IM, Salah A.
europepmc +2 more sources
BigBench Workload Executed by using Apache Flink
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 ...
Sonia Bergamaschi +2 more
exaly +4 more sources
Predictive topology refinements in distributed stream processing system. [PDF]
Cloud computing has evolved the big data technologies to a consolidated paradigm with SPaaS (Streaming processing-as-a-service). With a number of enterprises offering cloud-based solutions to end-users and other small enterprises, there has been a boom ...
Muhammad Hanif, Choonhwa Lee, Sumi Helal
doaj +2 more sources
The construction of an integrated cloud network digital intelligence platform for rail transit based on artificial intelligence [PDF]
This 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

