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- research-articleNovember 2023
Throughput Optimization with a NUMA-Aware Runtime System for Efficient Scientific Data Streaming
SC-W '23: Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and AnalysisNovember 2023, Pages 795–805https://doi.org/10.1145/3624062.3624593With the surge in data generation rates from advanced scientific instruments, there is an urgent need for effective network management and resource utilization strategies for data streaming. Present strategies often lag behind hardware advancements, ...
- research-articleSeptember 2023
Digital Twins and Blockchain for IoT Management
BSCI '23: Proceedings of the 5th ACM International Symposium on Blockchain and Secure Critical InfrastructureJuly 2023, Pages 64–74https://doi.org/10.1145/3594556.3594611Security and privacy are primary concerns in IoT management. Security breaches in IoT resources, such as smart sensors, can leak sensitive data and compromise the privacy of individuals. Effective IoT management requires a comprehensive approach to ...
- research-articleMay 2023
Real-time Spread Burst Detection in Data Streaming
Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), Volume 7, Issue 2Article No.: 35, Pages 1–31https://doi.org/10.1145/3589979Data streaming has many applications in network monitoring, web services, e-commerce, stock trading, social networks, and distributed sensing. This paper introduces a new problem of real-time burst detection in flow spread, which differs from the ...
- ArticleSeptember 2022
Accurate Performance Predictions with Component-Based Models of Data Streaming Applications
AbstractData streaming applications are an important class of data-intensive systems and performance is an essential quality of such systems. Current component-based performance prediction approaches are not sufficient for modeling and predicting the ...
- short-paperJuly 2022
Detecting trading trends in financial tick data: the DEBS 2022 grand challenge
DEBS '22: Proceedings of the 16th ACM International Conference on Distributed and Event-Based SystemsJune 2022, Pages 132–138https://doi.org/10.1145/3524860.3539645The DEBS Grand Challenge (GC) is an annual programming competition open to practitioners from both academia and industry. The GC 2022 edition focuses on real-time complex event processing of high-volume tick data provided by Infront Financial Technology ...
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- research-articleOctober 2021
Automated Discovery of Network Cameras in Heterogeneous Web Pages
- Ryan Dailey,
- Aniesh Chawla,
- Andrew Liu,
- Sripath Mishra,
- Ling Zhang,
- Josh Majors,
- Yung-Hsiang Lu,
- George K. Thiruvathukal
ACM Transactions on Internet Technology (TOIT), Volume 22, Issue 1Article No.: 15, Pages 1–25https://doi.org/10.1145/3450629Reduction in the cost of Network Cameras along with a rise in connectivity enables entities all around the world to deploy vast arrays of camera networks. Network cameras offer real-time visual data that can be used for studying traffic patterns, ...
- short-paperJune 2021
The DEBS 2021 grand challenge: analyzing environmental impact of worldwide lockdowns
DEBS '21: Proceedings of the 15th ACM International Conference on Distributed and Event-based SystemsJune 2021, Pages 136–141https://doi.org/10.1145/3465480.3467836The ACM DEBS 2021 Grand Challenge (GC) is the eleventh episode of a series of programming challenge competitions that began in 2011. Every year, participants of the GC are provided with new datasets and practical problems, and the challenge receives ...
- research-articleNovember 2021
Unlimited vector extension with data streaming support
ISCA '21: Proceedings of the 48th Annual International Symposium on Computer ArchitectureJune 2021, Pages 209–222https://doi.org/10.1109/ISCA52012.2021.00025Unlimited vector extension (UVE) is a novel instruction set architecture extension that takes streaming and SIMD processing together into the modern computing scenario. It aims to overcome the shortcomings of state-of-the-art scalable vector extensions ...
- keynoteApril 2021
Motivations and Challenges for Stream Processing in Edge Computing
ICPE '21: Companion of the ACM/SPEC International Conference on Performance EngineeringApril 2021, Pages 17–18https://doi.org/10.1145/3447545.3451899The 2030 Agenda for Sustainable Development of the United Nations General Assembly defines 17 development goals to be met for a sustainable future. Goals such as Industry, Innovation and Infrastructure and Sustainable Cities and Communities depend on ...
- short-paperJuly 2020
The role of event-time order in data streaming analysis
DEBS '20: Proceedings of the 14th ACM International Conference on Distributed and Event-based SystemsJuly 2020, Pages 214–217https://doi.org/10.1145/3401025.3404088The data streaming paradigm was introduced around the year 2000 to overcome the limitations of traditional store-then-process paradigms found in relational databases (DBs). Opposite to DBs' "first-the-data-then-the-query" approach, data streaming ...
- short-paperJuly 2020
The DEBS 2020 grand challenge
DEBS '20: Proceedings of the 14th ACM International Conference on Distributed and Event-based SystemsJuly 2020, Pages 183–186https://doi.org/10.1145/3401025.3402684The ACM DEBS 2020 Grand Challenge is the tenth in a series of challenges which seek to provide a common ground and evaluation criteria for a competition aimed at both research and industrial event-based systems. The focus of the ACM DEBS 2020 Grand ...
- research-articleJuly 2020
TinTiN: Travelling in time (if necessary) to deal with out-of-order data in streaming aggregation
DEBS '20: Proceedings of the 14th ACM International Conference on Distributed and Event-based SystemsJuly 2020, Pages 141–152https://doi.org/10.1145/3401025.3401769Cyber-Physical Systems (CPS) rely on data stream processing for high-throughput, low-latency analysis with correctness and accuracy guarantees (building on deterministic execution) for monitoring, safety or security applications. The trade-offs in ...
- short-paperJuly 2020
Real-time detection of smart meter events with odysseus
DEBS '20: Proceedings of the 14th ACM International Conference on Distributed and Event-based SystemsJuly 2020, Pages 193–198https://doi.org/10.1145/3401025.3401757The energy grid is changing rapidly to include volatile, renewable energy sources to help achieve climate goals. The transition to a smart grid, including smart meters for the metering and communication of the energy consumption, helps with that ...
- short-paperJune 2021
An Osmotic Ecosystem for Data Streaming Applications in Smart Cities
- Emanuele Carlini,
- Lorenzo Carnevale,
- Massimo Coppola,
- Patrizio Dazzi,
- Gabriele Mencagli,
- Domenico Talia,
- Massimo Villari
FRAME '21: Proceedings of the 1st Workshop on Flexible Resource and Application Management on the EdgeJune 2021, Pages 27–31https://doi.org/10.1145/3452369.3463822Modern multi-tier Cloud-Edge-IoT computational platforms seamlessly map with the distributed and hierarchical nature of smart cities infrastructure. However, classical tools and methodologies to organise data as well as computational and network ...
- research-articleMarch 2019
Behind Enemy Lines: Exploring Trusted Data Stream Processing on Untrusted Systems
CODASPY '19: Proceedings of the Ninth ACM Conference on Data and Application Security and PrivacyMarch 2019, Pages 243–254https://doi.org/10.1145/3292006.3300021Data Stream Processing Systems (DSPSs) execute long-running, continuous queries over transient streaming data, often making use of outsourced, third-party computational platforms. However, third-party outsourcing can lead to unwanted violations of data ...
- articleMarch 2019
An algorithm for arbitrary–order cumulant tensor calculation in a sliding window of data streams
International Journal of Applied Mathematics and Computer Science (IJAMCS), Volume 29, Issue 1Mar 2019, Pages 195–206https://doi.org/10.2478/amcs-2019-0015AbstractHigh-order cumulant tensors carry information about statistics of non-normally distributed multivariate data. In this work we present a new efficient algorithm for calculation of cumulants of arbitrary orders in a sliding window for data streams. ...
- research-articleAugust 2018
A Scalable Streaming Big Data Architecture for Real-Time Sentiment Analysis
ICCBDC '18: Proceedings of the 2018 2nd International Conference on Cloud and Big Data ComputingAugust 2018, Pages 47–51https://doi.org/10.1145/3264560.3266428The systems with a short window of opportunity for actions and decisions require developing solutions providing real-time streaming analytics. Real-time big data streaming analytics is a challenging task. In this paper, we propose a streaming big data ...
- research-articleJune 2018
Online Active Learning with Expert Advice
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 12, Issue 5Article No.: 58, Pages 1–22https://doi.org/10.1145/3201604In literature, learning with expert advice methods usually assume that a learner always obtain the true label of every incoming training instance at the end of each trial. However, in many real-world applications, acquiring the true labels of all ...
- research-articleJuly 2017
dispel4py
International Journal of High Performance Computing Applications (SAGE-HPCA), Volume 31, Issue 47 2017, Pages 316–334https://doi.org/10.1177/1094342016649766This paper presents dispel4py, a new Python framework for describing abstract stream-based workflows for distributed data-intensive applications. These combine the familiarity of Python programming with the scalability of workflows. Data streaming is ...
- posterMarch 2017
MORPH: supporting the integration of learning analytics at institutional level
LAK '17: Proceedings of the Seventh International Learning Analytics & Knowledge ConferenceMarch 2017, Pages 596–597https://doi.org/10.1145/3027385.3029478While there is high potential in using learning analytics to provide educational institutions as well as teachers and learners with actionable information and improve learning experiences, currently only very few learning analytics tools are actually ...