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DEBS '20: Proceedings of the 14th ACM International Conference on Distributed and Event-based Systems
ACM2020 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
DEBS '20: The 14th ACM International Conference on Distributed and Event-based Systems Montreal Quebec Canada July 13 - 17, 2020
ISBN:
978-1-4503-8028-7
Published:
15 July 2020
Sponsors:
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Abstract

This conference is the fourteenth in a series that spans 18 years of history with twelve 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 cuttingedge research in the field of event processing and 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 aims at providing a forum for academia and industry to exchange ideas through its tutorials, research papers, and the Grand Challenge.

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invited-talk
Streaming graph processing and analytics

Graphs are now ubiquitous as many applications emerge where the relationships among entities are paramount and require being modeled as first-class objects. Graph database systems empower such applications by enabling querying and processing both the ...

invited-talk
Building reproducible, reusable, and robust machine learning software

We have seen significant achievements with machine learning in recent years. Yet reproducing results for state-of-the-art deep learning methods is seldom straightforward. High variance of some methods can make learning particularly difficult. ...

SESSION: Research track
research-article
Triggerflow: trigger-based orchestration of serverless workflows

As more applications are being moved to the Cloud thanks to serverless computing, it is increasingly necessary to support native life cycle execution of those applications in the data center.

But existing systems either focus on short-running workflows (...

research-article
Leaving stragglers at the window: low-latency stream sampling with accuracy guarantees

Stream Processing Engines (SPEs) are used to process large volumes of application data to emit high velocity output. Under high load, SPEs aim to minimize output latency by leveraging sample processing for many applications that can tolerate approximate ...

research-article
A survey of adaptive sampling and filtering algorithms for the internet of things

The Internet of Things (IoT) represents one of the fastest emerging trends in the area of information and communication technology. The main challenge in the IoT is the timely gathering of data streams from potentially millions of sensors. In particular,...

research-article
EdgeScaler: effective elastic scaling for graph stream processing systems

Existing solutions for elastic scaling perform poorly with graph stream processing for two key reasons. First, when the system is scaled, the graph must be dynamically re-partitioned among workers. This requires a partitioning algorithm that is fast and ...

research-article
On the tracking of sensitive data and confidential executions

The production of large amounts of sensitive data raises growing concerns on confidentiality guarantees. Considering this, it is natural that data owners have an interest in how their data are being used. In this work, we propose Data aNd Application ...

research-article
Public Access
Mechanisms for outsourcing computation via a decentralized market

As the number of personal computing and IoT devices grows rapidly, so does the amount of computational power that is available at the edge. Many of these devices are often idle and constitute an untapped resource which could be used for outsourcing ...

research-article
FaaSdom: a benchmark suite for serverless computing

Serverless computing has become a major trend among cloud providers. With serverless computing, developers fully delegate the task of managing the servers, dynamically allocating the required resources, as well as handling availability and fault-...

research-article
The Kaiju project: enabling event-driven observability

Microservices architectures are getting momentum. Even small and medium-size companies are migrating towards cloud-based distributed solutions supported by lightweight virtualization techniques, containers, and orchestration systems. In this context, ...

research-article
DeepMatch: deep matching for in-vehicle presence detection in transportation

A key feature of modern public transportation systems is the accurate detection of the mobile context of transport vehicles and their passengers. A prominent example is automatic in-vehicle presence detection which allows, e.g., intelligent auto-...

research-article
Best Paper
Best Paper
hSPICE: state-aware event shedding in complex event processing

In complex event processing (CEP), load shedding is performed to maintain a given latency bound during overload situations when there is a limitation on resources. However, shedding load implies degradation in the quality of results (QoR). Therefore, it ...

research-article
RocketBufs: a framework for building efficient, in-memory, message-oriented middleware

As companies increasingly deploy message-oriented middleware (MOM) systems in mission-critical components of their infrastructures and services, the demand for improved performance and functionality has accelerated the rate at which new systems are ...

short-paper
Hermes: enabling energy-efficient IoT networks with generalized deduplication

The Internet of Things (IoT) is connecting a massive number of devices that generate a growing amount of data to be transmitted over the network. This traffic growth is expected to continue. Generalized deduplication (GD) is a novel technique to ...

short-paper
ByzGame: byzantine generals game

Byzantine Fault Tolerance (BFT) has gained renewed interest due to its usage as the core primitive in building consensus in blockchains. One of the primary challenges with BFT is understanding the theory behind it. Numerous BFT protocols have been ...

SESSION: Industry track
research-article
TinTiN: Travelling in time (if necessary) to deal with out-of-order data in streaming aggregation

Cyber-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 ...

research-article
Classification of vessel activity in streaming data

In this paper we motivate the need for real-time vessel behaviour classification and describe in detail our event-based classification approach, as implemented in our real-world industry strong maritime event detection service at MarineTraffic.com. A ...

research-article
Managing geo-distributed stream processing pipelines for the IIoT with StreamPipes edge extensions

The industrial IoT and its promise to realize data-driven decision-making by analyzing industrial event streams is an important innovation driver in the industrial sector. Due to an enormous increase of generated data and the development of specialized ...

short-paper
On the performance of commodity hardware for low latency and low jitter packet processing

With the introduction of Virtual Network Functions (VNF), network processing is no longer done solely on special purpose hardware. Instead, deploying network functions on commodity servers increases flexibility and has been proven effective for many ...

SESSION: DEBS grand challenge
short-paper
The DEBS 2020 grand challenge

The 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 ...

short-paper
Best Grand Challenge Performance
Best Grand Challenge Performance
Incremental stream query analytics

Applications in the Internet of Things (IoT) create many data processing challenges because they have to deal with massive amounts of data and low latency constraints. The DEBS Grand Challenge 2020 specifies an IoT problem whose objective is to identify ...

short-paper
Real-time detection of smart meter events with odysseus

The 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-paper
Anomaly detection for NILM task with Apache Flink

The topic of the 2020 DEBS Grand Challenge is to develop a solution for Non Intrusive Load Monitoring (NILM). Sensors continuously send voltage and current data into a stream processing application that would detect the pattern of power data based on ...

short-paper
Using streaming data and Apache Flink to infer energy consumption

This paper entails the technical details of an approach to the challenge presented by the DEBS 2020 committee [5], regarding Non-Intrusive Load Monitoring (NILM) and its relevance in the area of data streaming. Our project highlights how the open source ...

short-paper
Optimized parallel implementation of sequential clustering-based event detection

The ACM 2020 DEBS Grand Challenge focused on Non-Intrusive Load Monitoring (NILM). NILM is a method that analyzes changes in the voltage and current going into a building to deduce appliance use and energy consumption. The 2020 Grand Challenge requires ...

TUTORIAL SESSION: Tutorials
short-paper
The role of event-time order in data streaming analysis

The 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-paper
Open Access
Blockchain consensus unraveled: virtues and limitations

Since the introduction of Bitcoin---the first wide-spread application driven by blockchains---the interest of the public and private sector in blockchains has skyrocketed. At the core of this interest are the ways in which blockchains can be used to ...

SESSION: Doctoral symposium
short-paper
Trade-off analysis of thermal-constrained scheduling strategies in multi-core systems

The increasing usage of multi-cores in safety-critical applications, such as autonomous control, demands high levels of reliability, which crucially depends on the temperature. The scheduling of tasks is one of the key factors which determine the ...

short-paper
Pre-processing and data validation in IoT data streams

In the last few years, distributed stream processing engines have been on the rise due to their crucial impacts on real-time data processing with guaranteed low latency in several application domains such as financial markets, surveillance systems, ...

short-paper
Dynamic scaling of distributed data-flows under uncertainty

Existing approaches to dynamic scaling of streaming applications often fail to incorporate uncertainty arising from performance variability of shared computing infrastructures, and rapid changes in offered load. We explore the definition and ...

Contributors
  • School of Higher Technology
  • School of Higher Technology
  • University of Waterloo
  • McGill University
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Recommendations

Acceptance Rates

DEBS '20 Paper Acceptance Rate 11 of 43 submissions, 26%;
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%