118 citations · 324 across the 21 of their papers we have counts for
5 papers · 1 filter
Efficient Hierarchical Storage Management Framework Empowered by Reinforcement Learning
Tianru Zhang, Salman Toor, Andreas Hellander
With the rapid development of big data and cloud computing, data management has become increasingly challenging. Over the years, a number of frameworks for data management and stor…
Smart Resource Management for Data Streaming using an Online Bin-packing Strategy
Oliver Stein, Ben Blamey, Johan Karlsson +4
Data stream processing frameworks provide reliable and efficient mechanisms for executing complex workflows over large datasets. A common challenge for the majority of currently av…
Resource- and Message Size-Aware Scheduling of Stream Processing at the Edge with application to Realtime Microscopy
Ben Blamey, Ida-Maria Sintorn, Andreas Hellander +1
Whilst computational resources at the cloud edge can be leveraged to improve latency and reduce the costs of cloud services for a wide variety mobile, web, and IoT applications; su…
Adapting The Secretary Hiring Problem for Optimal Hot-Cold Tier Placement under Top- Workloads
Ben Blamey, Fredrik Wrede, Johan Karlsson +2
Top-K queries are an established heuristic in information retrieval. This paper presents an approach for optimal tiered storage allocation under stream processing workloads using t…
Apache Spark Streaming, Kafka and HarmonicIO: A Performance Benchmark and Architecture Comparison for Enterprise and Scientific Computing
Ben Blamey, Andreas Hellander, Salman Toor
This paper presents a benchmark of stream processing throughput comparing Apache Spark Streaming (under file-, TCP socket- and Kafka-based stream integration), with a prototype P2P…