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Parallel continuous skyline query over high-dimensional data stream windows
Real-time multi-criteria decision-making applications in fields like high-speed algorithmic trading, emergency response, and disaster management have...
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PECC: parallel expansion based on clustering coefficient for efficient graph partitioning
In the pursuit of graph processing performance, graph partitioning, as a crucial preprocessing step, has been widely concerned. Based on an in-depth...
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A blockchain datastore for scalable IoT workloads using data decaying
The Internet of Things (IoT) revolution has introduced sensor-rich devices to an ever growing landscape of smart environments. A key component in the...
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Flexible fingerprint cuckoo filter for information retrieval optimization in distributed network
In a large-scale distributed network, a naming service is used to achieve location transparency and provide effective content discovery. However,...
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Range constrained group query on attribute social graph
The geo-social group query is to find a group of users for the query point based on location and social information. In this paper, we propose the...
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Federated computation: a survey of concepts and challenges
Federated Computation is an emerging area that seeks to provide stronger privacy for user data, by performing large scale, distributed computations...
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Balanced parallel triangle enumeration with an adaptive algorithm
Triangle enumeration is a foundation brick for solving harder graph problems related to social networks, the Internet and transportation, to name a...
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SimCost: cost-effective resource provision prediction and recommendation for spark workloads
Spark is one of the most popular big data analytical platforms. To save time, achieve high resource utilization, and remain cost-effective for Spark...
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Scalable top-k query on information networks with hierarchical inheritance relations
Graph query, pattern mining and knowledge discovery become challenging on large-scale heterogeneous information networks (HINs). State-of-the-art...
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Multi-model query languages: taming the variety of big data
A critical issue in Big Data management is to address the variety of data–data are produced by disparate sources, presented in various formats, and...
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Performance models of data parallel DAG workflows for large scale data analytics
Directed Acyclic Graph (DAG) workflows are widely used for large-scale data analytics in cluster-based distributed computing systems. The performance...
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On combining system and machine learning performance tuning for distributed data stream applications
The growing need to identify patterns in data and automate decisions based on them in near-real time, has stimulated the development of new machine...
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Adaptive update handling for graph HTAP
Hybrid transactional/analytical processing (HTAP) workloads on graph data can significantly benefit from GPU accelerators. However, to exploit the...
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DOE: database offloading engine for accelerating SQL processing
The CPU-Accelerator heterogeneous systems have demonstrated performance and efficiency benefits on DBMSs. However, the CPU-Cache-DRAM architecture...
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GTraclus: a novel algorithm for local trajectory clustering on GPUs
Due to the high availability of location-based sensors like GPS, it has been possible to collect large amounts of spatio-temporal data in the form of...
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Adaptive query compilation in graph databases
Compiling database queries into compact and efficient machine code has proven to be a great technique to improve query performance and exploit...
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Out-of-the-box library support for DBMS operations on GPUs
GPU accelerated query execution is still ongoing research in the database community, as GPUs continue to be heterogeneous in their architectures...
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BOUNCE: memory-efficient SIMD approach for lightweight integer compression
Integer compression plays an important role in columnar database systems to reduce the main memory footprint as well as to speedup query processing....
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Novel insights on atomic synchronization for sort-based group-by on GPUs
Using heterogeneous processing devices, like GPUs, to accelerate relational database operations is a well-known strategy. In this context, the
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