Big Data in Emergent Distributed Environments (BiDEDE 2023)

Workshop @ ACM SIGMOD 2023

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International Workshop on
Big Data in Emergent Distributed Environments (BiDEDE 2023)
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The International Workshop on Big Data in Emergent Distributed Environments (BiDEDE 2023)

In conjunction with ACM SIGMOD 2023

In-person event:
SIGMOD 2023 and its workshops including BiDEDE are going to be an in-person (not a hybrid) event. In rare cases, remote presentations may be allowed if the presenter has a legitimate reason for not being able to travel such as travel restrictions from their government, or visa application not granted for even one of the authors. Note that this is reserved for exceptional cases.

Aims of the Workshop

Today, new forms of distributed environments beyond Cloud Computing occur that offer new kinds of applications, but pose new challenges for data management. The recent efforts for serverless computing aim at simplifying the process of deploying code in the Cloud into production by hiding scaling, capacity planning and maintenance operations from the developer or operator. Other initiatives work on avoiding the communication to the Cloud by deploying and running environments for data processing near data sources in Internet-of-Things scenarios (e.g., fog and edge computing) for large-scale smart homes, companies and cities, and near the applications (e.g., Cloudlets for mobile applications and Offline First technologies for web applications).

Research on distributed data management evolves addressing new challenges specific to these new environments. Properties of emergent distributed environments regarding capabilities of nodes, bandwidth for communication, battery lifetime of nodes, reliability of nodes and communication, and heterogeneity of configurations impact data management mechanisms and approaches, such as those for fault tolerance, replication, resource provisioning, buffer management, query processing and optimization, and transaction management. In addition, federated approaches and polystores spanning over several emergent distributed environments also remain research challenges based on the need for combining these different distributed environments into one distributed runtime environment for easy handling of Big Data in different models, and for globally optimizing data management tasks across these different environments.

The goal of this workshop is to bring together academic researchers and industry practitioners to discuss the challenges and solutions, including new approaches, techniques and applications, that significantly would advance the state of the art of Big Data in emergent distributed environments.

Categories of Papers

The workshop solicits papers of the following categories:

  • Research Papers propose new approaches, theories or techniques related to Big Data in emergent distributed environments including new data structures, protocols and algorithms. They should make substantial theoretical and empirical contributions to the research field.

  • System Papers describe new data management tools, stream processing engines, databases and other systems, which are able to handle Big Data in emergent distributed environments.

  • Experiments and Analysis Papers focus on the experimental evaluation of existing approaches including data structures and algorithms for Big Data in emergent distributed environments and bring new insights through the analysis of these experiments. Results of Experiments and Analysis Papers can be, for example, showing benefits of well-known approaches in new settings and environments, opening new research problems by demonstrating unexpected behavior or phenomena, or comparing a set of traditional approaches in an experimental survey.

  • Application Papers report practical experiences on applications of Big Data in emergent distributed environments. Application Papers might describe how to apply technologies to specific application domains with big data demands in emergent distributed environments like social networks, web search, e-business, collaborative environments, e-learning, medical informatics, bioinformatics and geographic information systems.

  • Vision Papers identify emerging new or future research issues and directions, and describe new research visions having demands for Big Data in emergent distributed environments. The new visions will potentially have great impacts on society.

  • Demo Papers deal with innovative systems and applications for Big Data in emergent distributed environments. These papers describe a showcase of the proposed system/application, but may also explain the novelty of the system's architecture. We are especially interested in demonstrations having a WOW-effect.

The length of papers must be within 4 pages to 6 pages. Accepted papers will be published in the ACM Digital Library and presented as oral presentations.

Topics of Interest

We are interested in all issues concerning the management of data to be processed in emergent environments such as the following:

  • Cloud Computing

  • Serverless Computing

    • Cloud Functions
    • App Engines
    • Cloud Runs

  • Post-Cloud Computing

    • Cloudlet
    • Fog Computing
    • Edge Computing
    • Cloud-Edge Continuum
    • Dew Computing
    • Offline First
    • Smart Home/Companies/Cities

  • Quantum Computing

The Data Management issues to be solved in the emergent environments include, but are not limited to, the following:

  • Query Processing and Optimization
  • Transaction Management
  • Fault Tolerance Mechanisms
  • Cloud Data Warehouses
  • Distributed Databases
  • Federation/Polystore Architectures
  • Data Lakes
  • Artificial Intelligence in Big Data Environments
  • Interactive Data Analytics and Big Data Science
  • 5G/6G Impact on Data Management

Important Dates

Time Schedule
Submission (extended): March 26, 2023
Notification: April 24, 2023
Workshop: June 18 (Sunday), 2023

Diversity Considerations of the Program Committee

We have currently recruited 24 PC members and chairs listed below who are experts in the topics of interest of our workshop. The current PC members and chairs are selected from 15 nations all over the world as shown also by the map below. While most PC members are from academia, we have 5 experts also from industry (21%). 7 of the PC members and chairs are women (29%).

Legend

Program committee members and chairs: 1  10

Program Committee Chairs

Proceedings Chairs

Steering Committee

Program Committee

  • Ahmed S. Abdelhamid, Purdue University, USA
  • Mithun Balakrishna, Amazon.com Inc.
  • Srinjoy Ganguly, Woxsen University, India
  • Jinghua Groppe, University of Lübeck, Germany
  • Ekaterini Ioannou, Tilburg University
  • Ioannis Kontopoulos, Harokopio University of Athens, Greece
  • Xiang Lian, Kent State University, USA
  • Qing Liu, Data61, CSIRO, Australia
  • Renato Marroquín, Oracle
  • Grażyna Paliwoda-Pękosz, Cracow University of Economics, Poland
  • Alfredo Pulvirenti, University of Catania, Italy
  • Praveen Rao, The University of Missouri, USA
  • Omair Shafiq, Carleton University, Canada
  • Katja Gilly de La Sierra-Llamazares, Miguel Hernandez University, Spain
  • Marta Tatu, Raytheon Technologies
  • Konstantinos Tserpes, Harokopio University of Athens, Greece
  • Sanjay Vishwakarma, IBM Quantum, IBM Research - Almaden, USA
  • Xikui Wang, Google, USA
  • Robert Wrembel, Poznan University of Technology, Poland
  • Steffen Zeuch, Technische Universität Berlin, Germany
  • Zhuoyue Zhao, University at Buffalo, USA

Evaluation of Papers

To verify the originality of submissions, we will use Plagiarism Detection Tools to check the content of the submitted manuscripts against previous publications.

Papers will be evaluated according to the following aspects:

  • Relevance to the Workshop
  • Novelty and practical impact
  • Technical soundness
  • Appropriateness and adequacy of:
    • Literature review
    • Background discussion
    • Analysis of issues
  • Presentation, including:
    • Overall organization and structure
    • Correctness of English language
    • Readability

Accepted Papers

The proceedings are available here.
  • Martin Schallnahs, Thomas Günther, Thomas Kudraß:
    Challenges in Prototyping a Cloud-Native Billing Application for 5G with Stream Processing
    DOI: 10.1145/3579142.3594292
  • Patrick Hansert, Sebastian Michel:
    Schema-based Column Reordering for Dremel-encoded Data
    DOI: 10.1145/3579142.3594286
  • Tarek Stolz, István Koren, Liam Tirpitz, Sandra Geisler:
    GALOIS: A Hybrid and Platform-Agnostic Stream Processing Architecture
    DOI: 10.1145/3579142.3594287
  • Ricky Sun, Jamie Chen:
    Design of Highly Scalable Graph Database Systems without Exponential Performance Degradation
    DOI: 10.1145/3579142.3594293
  • Tobias Winker, Umut Çalıkyılmaz, Le Gruenwald, Sven Groppe:
    Quantum Machine Learning for Join Order Optimization using Variational Quantum Circuits
    DOI: 10.1145/3579142.3594299
  • Shailesh Deshpande, Shruti Kunde, Ravi Singh, Chaman Banolia, Rekha Singhal, Balamurlidhar P.:
    DAFTA: Distributed Architecture for Fusion-Transformer training Acceleration
    DOI: 10.1145/3579142.3594294
  • Nitin Nayak, Jan Rehfeld, Tobias Winker, Benjamin Warnke, Umut Çalıkyılmaz, Sven Groppe:
    Constructing Optimal Bushy Join Trees by Solving QUBO Problems on Quantum Hardware and Simulators
    DOI: 10.1145/3579142.3594298

Program

Keynote (Common Keynote with the Data Economy Workshop in Room Evergreen F)

Time Type Description
8:30am: keynote Jian Pei (Duke University):
Data and AI Model Markets: Grand Opportunities for Facilitating Sharing, Discovery, and Integration in Data and AI Economies
(Common Keynote with the Data Economy Workshop in Room Evergreen F)
10:30am: break Coffee Break

Paper Session 1 (Room Evergreen A)

Time Type Description
11am: paper Patrick Hansert, Sebastian Michel:
Schema-based Column Reordering for Dremel-encoded Data
DOI: 10.1145/3579142.3594286
11:20am: paper Tarek Stolz, István Koren, Liam Tirpitz, Sandra Geisler:
GALOIS: A Hybrid and Platform-Agnostic Stream Processing Architecture
DOI: 10.1145/3579142.3594287
11:40am: paper Ricky Sun, Jamie Chen:
Design of Highly Scalable Graph Database Systems without Exponential Performance Degradation
DOI: 10.1145/3579142.3594293
12am: paper Martin Schallnahs, Thomas Günther, Thomas Kudraß:
Challenges in Prototyping a Cloud-Native Billing Application for 5G with Stream Processing
DOI: 10.1145/3579142.3594292
12:20am: lunch Lunch Break

Paper Session 2 (Room Evergreen A)

Time Type Description
1:30pm: paper Tobias Winker, Umut Çalıkyılmaz, Le Gruenwald, Sven Groppe:
Quantum Machine Learning for Join Order Optimization using Variational Quantum Circuits
DOI: 10.1145/3579142.3594299
1:50pm: paper Shailesh Deshpande, Shruti Kunde, Ravi Singh, Chaman Banolia, Rekha Singhal, Balamurlidhar P.:
DAFTA: Distributed Architecture for Fusion-Transformer training Acceleration
DOI: 10.1145/3579142.3594294
2:10pm: paper Nitin Nayak, Jan Rehfeld, Tobias Winker, Benjamin Warnke, Umut Çalıkyılmaz, Sven Groppe:
Constructing Optimal Bushy Join Trees by Solving QUBO Problems on Quantum Hardware and Simulators
DOI: 10.1145/3579142.3594298
2:30pm: keynote Valter Uotila (University of Helsinki):
Invited Talk: SQL Query Classification with A Quantum Natural Language Processing Approach
Bio: Valter Uotila is currently pursuing a PhD in computer science at the University of Helsinki. His research focuses on exploring the potential of quantum computing in data management and database optimization. He is also interested in applying category theory to establish a link between quantum computing and databases. To date, he has published several papers, including studies on the application of category theory to multi-model databases. In one of his recent papers, he identifies several database issues that can be resolved using quantum computing techniques.
Abstract: This work proposes a quantum natural language processing-inspired approach for classifying SQL queries based on their execution times and cardinalities. Using parameterized quantum circuits and an iterative method for their optimization, we estimate query metrics by executing optimized circuits on a quantum computer or simulating them. Our results achieve comparable accuracy to previous research in quantum natural language processing, suggesting the potential of this approach in applications beyond quantum natural language processing. We also analyze the model's expressibility and entangling capability histograms for further insights.
2:50pm: break End of Workshop

Manuscript Preparation

Authors are invited to submit original, unpublished research papers that are not being considered for publication in any other forum.

Manuscripts should be submitted electronically as PDF files using this webpage and be formatted using the camera-ready templates in the ACM proceedings double-column format according to the "sigconf" proceedings template. Papers cannot exceed 6 pages in length.

Accepted papers will be published online in the ACM digital library. The papers must include the standard ACM copyright notice on the first page.

The pdf version of your paper should consider the following items:

  • The pdf be optimized for fast web viewing.

  • The pdf should apply the ACM Computing Classification categories and terms (CCS concepts). The ACM templates provide space for this indexing and please consider the Computing Classification Scheme.

  • The pdf should contain the keywords.

  • The pdf should have the rights management statement and bibliographic strip on the bottom of the first page left column.

  • Please start numbering your paper with page number 1.

  • The pdf should have Type 1 fonts (scalable), not Type 3 (bit-mapped). All fonts MUST be embedded within the PDF file (to be corrected in the source files before the PDF is generated according to ACM documentation).

Submission to International Workshop on Big Data in Emergent Distributed Environments (BiDEDE 2023)

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Editions

Please use the following links for further information on the edition of the given year of the International Workshop on Big Data in Emergent Distributed Environments (BiDEDE):