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DEBS '21: Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems
ACM2021 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
DEBS '21: The 15th ACM International Conference on Distributed and Event-based Systems Virtual Event Italy 28 June 2021- 2 July 2021
ISBN:
978-1-4503-8555-8
Published:
28 June 2021
Sponsors:
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Abstract

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.

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SESSION: Keynotes
keynote
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 ...

keynote
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 ...

keynote
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, ...

SESSION: Research track
research-article
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 ...

research-article
Open Access
Best Paper
Best Paper
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 ...

research-article
Public Access
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 ...

research-article
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-...

research-article
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 ...

research-article
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 ...

research-article
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 ...

SESSION: Industry track
invited-talk
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 ...

research-article
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. ...

research-article
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 ...

research-article
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 ...

SESSION: DEBS 2021 grand challenge
short-paper
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 ...

short-paper
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 ...

short-paper
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 ...

short-paper
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 ...

TUTORIAL SESSION: Tutorials
tutorial
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 ...

tutorial
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
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 ...

DEMONSTRATION SESSION: Demonstrations and posters
short-paper
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 ...

short-paper
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 ...

short-paper
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 ...

short-paper
Open Access
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, ...

short-paper
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 ...

short-paper
Real-time processing of geo-distributed financial data

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. ...

SESSION: Doctoral symposium
short-paper
Open Access
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 ...

Contributors
  • Politecnico di Milano
  • Politecnico di Milano
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Acceptance Rates

DEBS '21 Paper Acceptance Rate 7 of 26 submissions, 27%;
Overall Acceptance Rate 145 of 583 submissions, 25%
YearSubmittedAcceptedRate
DEBS '24301550%
DEBS '22191053%
DEBS '2126727%
DEBS '20431126%
DEBS '19471328%
DEBS '18311239%
DEBS '17602237%
DEBS '14174169%
DEBS '13581628%
DEBS '11952324%
Overall58314525%