This conference is the fifteenth in a series that spans 20 years of history, with 14 past editions as a conference and five editions as a workshop co-located with major conferences. The ACM International Conference on Distributed and Event - Based Systems (DEBS) has become the premier venue for cutting-edge research in event processing, distributed computing, and the integration of distributed and event-based systems in relevant domains such as Big Data, AI, ML, IoT and Blockchain. The objectives of the ACM International Conference on Distributed and Event - Based Systems (DEBS) are to provide a forum dedicated to the dissemination of original research, the discussion of practical insights, and the reporting of experiences relevant to distributed systems and event-based computing. The conference provides a forum for academia and industry to exchange ideas through its tutorials, research papers, and the grand challenge.
Proceeding Downloads
Workload-driven systems optimization: things are getting real!
In this talk, I will describe how workload-driven system optimization has quickly evolved from a researcher's dream into a production reality. In particular, I will provide a high-level overview of a large collection of efforts that build upon careful ...
Explainable anomaly detection on high-dimensional time series data
As enterprise information systems are collecting event streams from various sources, the ability of a system to automatically detect anomalous events and further provide human-readable explanations is of paramount importance. In this paper, we present ...
Thinking in events: from databases to distributed collaboration software
In this keynote I give a subjective but systematic overview of the landscape of distributed event-based systems, with an emphasis on two areas I have worked on over the last decade: large-scale stream processing with Apache Kafka and associated tools, ...
A distributed database system for event-based microservices
Microservice architectures are an emerging industrial approach to build large scale and event-based systems. In this architectural style, an application is functionally partitioned into several small and autonomous building blocks, so-called ...
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Distributed transactions on serverless stateful functions
Serverless computing is currently the fastest-growing cloud services segment. The most prominent serverless offering is Function-as-a-Service (FaaS), where users write functions and the cloud automates deployment, maintenance, and scalability. Although ...
Towards event-driven decentralized marketplaces on the blockchain
Blockchains have become a popular technology for lowering the trust-tax burden between transacting parties that cannot necessarily trust each other. They are used as substitutes for the centralized authorities typically incorporated in transactional ...
An experimental framework for improving the performance of BFT consensus for future permissioned blockchains
Permissioned Blockchains are increasingly considered in enterprise use-cases, many of which do not require geo-distribution, or even disallow it due to legislation. Examples include countrywide networks, such as Alastria, or those deployed using cloud-...
Fast recovery of correlated failures in distributed stream processing engines
In a large-scale cluster, correlated failures usually involve a number of nodes failing simultaneously. Although correlated failures occur infrequently, they have significant effect on systems' availability, especially for streaming applications that ...
An event driven framework for smart contract execution
Blockchain-based smart contract platforms have traditionally employed the transaction-driven execution model. This paper presents an alternate framework for blockchain-based smart contract execution called EDSC. Our platform design presents a novel ...
Box queries over multi-dimensional streams
Answering statistical queries about streams of online arriving data is becoming increasingly important. Often, such data includes multiple-attributes, so data elements can be viewed as points in a multi-dimensional universe. This paper extends existing ...
Real-time big data stream analytics and complex event detection: modular visual framework, data science platform, and industry applications
In many industry applications, larger and larger amounts of data become available, allowing to gain deeper insights, to generate more accurate forecats, to optimize and automate processes, and to thereby create significant value. Often the data is not ...
S2CE: a hybrid cloud and edge orchestrator for mining exascale distributed streams
The explosive increase in volume, velocity, variety, and veracity of data generated by distributed and heterogeneous nodes such as IoT and other devices, continuously challenge the state of art in big data processing platforms and mining techniques. ...
Descriptor based consensus for blockchain transactions
Blockchain networks use consensus mechanisms so participants can exchange transactions without the need to rely on a trusted third party. Consensus mechanisms using Proof of Work burn significant energy to select a block miner and the delay limits ...
The synergy of complex event processing and tiny machine learning in industrial IoT
Focusing on comprehensive networking, the Industrial Internet-of-Things (IIoT) facilitates efficiency and robustness in factory operations. Various intelligent sensors play a central role, as they generate a vast amount of real-time data that can ...
The DEBS 2021 grand challenge: analyzing environmental impact of worldwide lockdowns
The 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 ...
Solving the 2021 DEBS grand challenge using Apache Flink
The DEBS Grand Challenge is an annual event in which different event-based systems compete to solve a real-world problem. For the year 2021, the challenge is computing information given air quality sensor data. Due to the pandemic many factories are ...
DEBS grand challenge: real-time detection of air quality improvement with Apache Flink
The topic of the DEBS Grand Challenge 2021 is to develop a solution for detecting areas in which the air quality index (AQI) improved the most when compared to the previous year. The solution must run two given continuous queries in parallel on the ...
Scalable analytics of air quality batches with Apache Spark and Apache Sedona
According to the American National Institute of Environmental Health Sciences (NIEHS), air pollutants are harmful to the health of humans and other living beings, and cause damage to the climate and to the ecosystem by polluting lakes, streams, and ...
Machine learning over static and dynamic relational data
This tutorial overviews principles behind recent works on training and maintaining machine learning models over relational data, with an emphasis on the exploitation of the relational data structure to improve the runtime performance of the learning ...
Web stream processing with RSP4J
Social Media Analysis, Internet of Things, and Fake News detection have unveiled the relevance of real-time analytics on the Web. As a consequence, the Web infrastructure is evolving to enable continuous and reactive data access. Since data streams ...
Tutorial on graph stream analytics
In this short tutorial, we cover recent methods to analyze and model network data accessible as a stream of edges, such as interactions in a social network service, or any other graph database with real-time updates from a stream. First we introduce the ...
Towards autonomous semantic stream fusion for distributed video streams
Video streams are becoming ubiquitous in smart cities and traffic monitoring. Recent advances in computer vision with deep neural networks enable querying a rich set of visual features from these video streams. However, it is challenging to deploy these ...
HawkEDA: a tool for quantifying data integrity violations in event-driven microservices
A microservice architecture advocates for subdividing an application into small and independent components, each communicating via well-defined APIs or asynchronous events, to allow for higher scalability, availability, and fault isolation. However, the ...
Enforcing consistency in microservice architectures through event-based constraints
Microservice architectures are an emerging paradigm for developing event-driven applications. By prescribing that an application is decomposed into small and independent components, each encapsulating its own state and communicating via asynchronous ...
Building an end-to-end BAD application
Traditional big data infrastructures are passive in nature, passively answering user requests to process and return data. In many applications however, users not only need to analyze data, but also to subscribe to and actively receive data of interest, ...
Towards creating a generalized complex event processing operator using FlinkCEP: architecture & benchmark
FlinkCEP, the Complex Event Processing (CEP) API of the Flink Big Data platform, scales-out pattern detection to a number of machines in a computer cluster or cloud. The high expressive power of FlinkCEP's language comes at the cost of cumbersome ...
Real-time processing of geo-distributed financial data
- Antonios Kontaxakis,
- Antonios Deligiannakis,
- Holger Arndt,
- Stefan Burkard,
- Claus-Peter Kettner,
- Elke Pelikan,
- Kathleen Noack
Enabling real-time processing of financial data streams is extremely challenging, especially considering that typical operations that interest investors often require combining data across (a potentially quadratic number of) different pairs of stocks. ...
Accelerating the performance of data analytics using network-centric processing
Distributed execution of real-time data analytics such as event stream processing is the key to scalability, performance and reliable detection of situation changes. Although real-time analytics is highly I/O centric, existing methods supporting the ...
Index Terms
- Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems