Smart scheme: an efficient query execution scheme for event-driven stream processing
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DOI: 10.1007/s10115-018-1195-9
Abstract: With the increase in stream data, a demand for stream processing has become diverse and complicated. To meet this demand, several stream processing engines (SPEs) have been developed which execute continuous queries (CQs) to process… read more here.
Keywords: stream; stream processing; query; event driven ... See more keywords
Reliable stream data processing for elastic distributed stream processing systems
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DOI: 10.1007/s10586-019-02939-9
Abstract: Distributed stream processing system (DSPS) has proven to be an effective way to process and analyze large-scale data streams in real-time fashions. The reliability problem of DSPS is becoming a popular topic in recent years.… read more here.
Keywords: distributed stream; system; processing; stream processing ... See more keywords
Real-Time Big Data Stream Processing Using GPU with Spark Over Hadoop Ecosystem
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DOI: 10.1007/s10766-017-0513-2
Abstract: In this technological era, every person, authorities, entrepreneurs, businesses, and many things around us are connected to the internet, forming Internet of thing (IoT). This generates a massive amount of diverse data with very high-speed,… read more here.
Keywords: big data; real time; stream processing; time ... See more keywords
Towards Automatic Parallelization of Stream Processing Applications
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DOI: 10.1109/access.2018.2855064
Abstract: Parallelizing and optimizing codes for recent multi-/many-core processors have been recognized to be a complex task. For this reason, strategies to automatically transform sequential codes into parallel and discover optimization opportunities are crucial to relieve… read more here.
Keywords: processing applications; framework; stream processing; towards automatic ... See more keywords
Distributed Join Processing Between Streaming and Stored Big Data Under the Micro-Batch Model
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DOI: 10.1109/access.2019.2904730
Abstract: In order to interpret, enrich, and analyze the streaming data, stream applications often access the data stored in an external database. Although there has been a lot of studies on stream processing, little attention has… read more here.
Keywords: batch model; micro batch; join; stream processing ... See more keywords
A Survey of Distributed Data Stream Processing Frameworks
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DOI: 10.1109/access.2019.2946884
Abstract: Big data processing systems are evolving to be more stream oriented where each data record is processed as it arrives by distributed and low-latency computational frameworks on a continuous basis. As the stream processing technology… read more here.
Keywords: processing frameworks; data stream; stream processing; distributed data ... See more keywords
Resource-Aware Edge-Based Stream Analytics
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DOI: 10.1109/mic.2022.3152478
Abstract: Understanding how machine learning (ML) algorithms can be used for stream processing on edge devices remains an important challenge. Such ML algorithms can be represented as operators and dynamically adapted based on the resources on… read more here.
Keywords: stream processing; stream; resource aware; edge based ... See more keywords
Stream Processing of Shortest Path Query in Dynamic Road Networks
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DOI: 10.1109/tkde.2020.3010005
Abstract: Shortest path query in road network is pervasive in various location-based services nowadays. As the business expands, the scalability issue becomes severer and more servers are deployed to cope with it. Moreover, as the traffic… read more here.
Keywords: path query; stream processing; query; shortest path ... See more keywords
A Sketch Framework for Approximate Data Stream Processing in Sliding Windows
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DOI: 10.1109/tkde.2022.3151140
Abstract: Data stream processing has become a hot issue in recent years. There are three fundamental stream processing tasks: membership query, frequency query, and Top-K query. While most existing solutions address these queries in fixed windows,… read more here.
Keywords: data stream; sliding windows; framework; stream processing ... See more keywords
Efficient Time-Evolving Stream Processing at Scale
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DOI: 10.1109/tpds.2019.2911495
Abstract: Time-evolving stream datasets exist ubiquitously in many real-world applications where their inherent hot keys often evolve over times. Nevertheless, few existing solutions can provide efficient load balancing on these time-evolving datasets while preserving low memory… read more here.
Keywords: time; time evolving; efficient time; stream processing ... See more keywords
Hone: Mitigating Stragglers in Distributed Stream Processing With Tuple Scheduling
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DOI: 10.1109/tpds.2021.3051059
Abstract: Low latency stream processing on large clusters consisting of hundreds to thousands of servers is an increasingly important challenge. A crucial barrier to tackling this challenge is stragglers, i.e., tasks that are significantly straggling behind… read more here.
Keywords: hone; stream processing; tuple scheduling; tuple ... See more keywords