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IEEE BDS 2024 : BigDataService 2024: IEEE BigDataService 2024

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Link: https://ieeebigdataservice.com/
 
When Jul 15, 2024 - Jul 18, 2024
Where Shangai, China
Submission Deadline Apr 7, 2024
Notification Due May 15, 2024
Final Version Due May 22, 2024
 

Call For Papers

Call for Papers

The 10th IEEE International Conference on Big Data Computing Service and Machine Learning Applications (IEEE BigDataService 2024)
15-18 July 2024, Shanghai, China
https://ieeebigdataservice.com/

As computing systems become increasingly larger, more complex, distributed, and integrated, Big Data technologies and services are ever more vital. IEEE BigDataService 2024 provides an internationally leading forum for researchers and practitioners in academia and industry to exchange innovative ideas and share the latest results, experiences, and lessons learned in this crucial domain.
The conference will be held in person and will take place in Shanghai, China on the 15-18 July 2024. It will consist of a main track with several topics of interest; it seeks the submission of high-quality papers in the IEEE format: full papers (up to 8 pages), short/demo papers (up to 5 pages), and posters (2 pages). The conference also welcomes workshop proposals. All accepted papers will be included in the proceedings. Selected papers will be invited to submit extended versions in a special issue of a peer-reviewed (SCI-Indexed) journal.
BigDataService 2024 is part of the CISOSE 2024 congress, and it will be co-located with IEEE SOSE 2024, IEEE Mobile Cloud 2024, IEEE DAPPS 2024, IEEE AITest 2024, and IEEE JCC 2024.
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TOPICS OF INTEREST (INCLUDING BUT NOT LIMITED TO):
Big Data Analytics and Machine Learning
- Algorithms and systems for big data search and analytics
- Machine learning for big data and based on big data
- Predictive analytics and simulation
- Visualization systems for big data
- Knowledge extraction, discovery, analysis, and presentation

Integrated and Distributed Systems
- Sensor networks
- Internet of Things
- Networking and protocols
- Smart Systems (such as energy efficiency systems, smart homes, smart farms, etc.)

Big Data Platforms and Technologies
- Innovative, concurrent, and scalable big data platforms
- Data indexing, cleaning, transformation, and curation technologies
- Big data processing frameworks and technologies
- Big data services and application development methods and tools
- Big data quality evaluation and assurance technologies
- Big data system reliability, dependability, and availability
- Open-source development and technology for big data
- Big Data as a Service (BDaaS) platform and technologies

Big Data Foundations
- Foundational theoretical or computational models for big data
- Programming models, theories, and algorithms for big data
- Standards, protocols, and quality assurance for big data

Big Data Applications and Experiences
- Innovative big data applications and services in industries and domains e.g. healthcare, finance, insurance, transportation, agriculture, education, environment, multimedia, social networks, urban planning, disaster management, security
- Experiences and case studies of big data applications and services
- Real-world and large-scale practices of big data

Particular attention will be dedicated to the following special topics:
Special Topic 1: Real-time Big Data Services and Applications
- Models, algorithms, and technologies for real-time big data services and applications
- Experiences, practices and case studies of real-time big data services and applications

Special Topic 2: Big Data Security, Privacy, Trust, and Sustainability
- Models, algorithms and technologies for big data security and privacy
- Attacks and defenses for big data services
- Privacy-preserving processing of big data and Big Data for Security and Privacy Analysis
- Energy-aware big data storage, transfer, and usage
- AI-continuum (e.g., cloud, edge, sensors) for sustainable big data services

Special Topic 3: Big Data and Analytics for Healthcare
- Models, algorithms, and technologies of big data for healthcare
- Big data services and applications for healthcare
- Experiences, practices, and case studies of big data technologies for healthcare

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IMPORTANT DATES:
Workshop proposals: 3 March 2024
Abstract submission: 31 March 2024
Full, short, demo, and poster papers submission: 7 April 2024
Notification of acceptance: 15 May 2024
Final Paper and Registration: 22 May 2024
Conference: 15-18 July 2024

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PAPER SUBMISSION
Papers must be written in English. All papers must be prepared in the IEEE double-column proceedings format. Please see the following link for details: http://www.ieee.org/conferences_events/conferences/publishing/templates.html.
Full research papers are limited to 8 pages, short research papers and demo papers are limited to 5 pages, and posters are limited to 2 pages. All page limits include references. Authors must submit their papers at the Easychair link: https://easychair.org/conferences/?conf=bds2024.

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PAPER PUBLICATION
All accepted papers will be published by IEEE Computer Society Press (EI‚ÄźIndex) and included in IEEE Digital Library. For publication, at least one author is required to register at the full rate and present the paper at the conference for the paper to be included in the final technical program and the IEEE Digital Library. Selected papers will be invited for extension and published in journals (SCI-Index).

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ORGANIZING COMMITTEE:

General Chairs
Magdalini Eirinaki, San Jose State University, USA
Muhammad Younas, Oxford Brookes University, UK
Fei Wu, Zhejiang University, China

Program Chairs
Hiroyuki Fujioka, Fukuoka Institute of Technology, Japan
Katerina Potika, San Jose State University, USA
Junchi Yan, Shanghai Jiao Tong University, China

Workshop Chair
Elis Kulla, Fukuoka Institute of Technology, Japan

Publicity Chairs
Stefano Cirillo, University of Salerno, Italy
Jing Fu, Fukuoka Institute of Technology, Japan
Jorjeta Jetcheva, San Jose State University, USA

Proceedings Chair
Yassine Himeur, University of Dubai, UAE

Web Chair
Donald Elmazi, Metropolitan University of Tirana, Albania
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