- Original Paper Submission Deadline: 20 August 2024, extended to: 20 September 2024
- Acceptance Notification: 7 October 2024
- Camera Ready Papers Due: 20 October 2024
Conference Date: 16-19 December 2024
Note: IEEE/ACM UCC 2024 & BDCAT Conferences will be held in conjunction. Date submissions are the same for both events. See below for futher details.
IEEE/ACM UCC 2024
We are pleased to inform you that the “17th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2024)” will be held in Sharjah, United Arab Emirates between 16 and 19 December, 2024.
The IEEE/ACM International Conference on Utility and Cloud Computing (UCC) is a premier annual conference series aiming to provide a platform for researchers from both academia and industry to present new discoveries and high-quality contributions in the broad area of Cloud, Edge and Computing Continuum utility computing and applications. The conference features keynotes, posters, workshops and a student symposium. UCC 2024 will be held in conjunction with the 11th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT 2024).
The PDF version of the UCC 2024 Call for Papers may be downloaded HERE.
Authors are invited to submit original, unpublished research manuscripts in all areas of Cloud-Edge Continuum for utility computing and related computing paradigms such as Serverless, Distributed Computing and Function as a Service. The theme of this year is Self-adaptive and Autonomic Cloud, Edge, and Utility Computing in the Era of Large Language Models (LLM). The theme will explore new synergies between self-* and autonomous management of cloud, edge and their computing utilities and LLM approaches and solutions. We invite novel contributions with excellent balance between sound and rigorous foundational research and experimental results that relate to this year’s theme and to the general UCC topics, as below.
UCC 2024 topics of interest include but not limited to:
1. Resource Management for Cloud-Edge Continuum:
• Principles and Theoretical Foundations of Utility Computing
• Architectural Models and Patterns to achieve Utility; Virtualization, Containerization, Composition and Orchestration
• Formal and Qualitative Aspects
• Middleware and Stacks
• Networking and Network Management
• Saas, Paas, Iaas and XaaS
2. Resource Management and Scalability:
• Brokering, Scheduling, Capacity planning and Elasticity
• Security, Trust, Privacy, Policies and Blockchains
3. Autonomic, Adaptive, Self-*, SLAs, Management and Monitoring; Designs and Deployment Models:
• Private, Public, Hybrid, Federated, Aggregated, Inter-Cloud; High Performance Computing (HPC)
• Performance Analysis and Modelling
• Foundational self-* solutions, possibly leveraging LLM techniques (see this year theme)
4. Artificial Intelligence for Cloud-Edge Continuum and Utility Computing:
• Machine Learning Operations (MLOps)
• Artificial Intelligence Solutions for Scheduling
• Provisioning and Deployment
• Lightweight machine learning for edge learning
• Artificial Intelligence Solutions for Orchestration
• GPU as a Service (GPUaaS), Artificial Intelligence as a Service (AIaaS); Support for Extract/Transform/Load (ETL) or ETL Pipelines
• Machine Learning Cloud Frameworks; Artificial Intelligence Infrastructure
• Distributed, Federated, Collaborative Learning, and Large Language Models (LLM)
5. Applications, Systems and new Computing Paradigms for Cloud-Edge Continuum:
• Native Application Design, Programming Models and Engineering
• Serverless and Function-Based Applications (FaaS)
• Microservices Architectures, Quantum Computing
• Interfacing to Internet of Things, (IoT) Applications
• Utility-Driven Models and Mechanisms in All Domains (e.g., Smart Cities, Mobility, Healthcare, Industry 4.0)
• Micro Data Centers
• Interfacing to Mobile Devices: Management, Hierarchy Models and Business Models
• Energy-Efficiency and Sustainability; Development; Operations (DevOps)
• Economic and Business Models
• Business and Legal Implications Beyond Technology
• Digital Twins solutions
PAPER SUBMISSION
Submitted manuscripts must represent original unpublished research that is not currently under review for any other conference or journal. Manuscripts are submitted in PDF format and may not exceed ten (10) IEEE-formatted *double-column* pages, including figures, tables, and references. All manuscripts undergo a double-blind peer-review process and will be reviewed and judged on correctness, originality, technical strength, rigor in analysis, quality of results, quality of presentation, and interest and relevance to the conference attendees. Your submission is subject to a determination that you are not under any sanctions by IEEE.
At least one author of each paper must be registered for the conference in order for the paper to be published in the proceedings. The conference proceedings will be published by the ACM and made available online via the IEEE Xplore Digital Library and ACM Digital Library.
AWARDS AND SPECIAL ISSUES
A selection committee chaired by the UCC 2024 conference co-chairs will select and acknowledge the best paper to receive an award during the conference.
Authors of highly rated papers from UCC 2024 will be invited to submit an extended version to special issues in ACM Transactions on Autonomous and Adaptive Systems (TAAS).
Submit your paper and learn more about the conference here.
IEEE/ACM Int’l Conf. on Big Data Computing, Applications, and Technologies (BDCAT)
We are pleased to inform you that the “11th IEEE/ACM International Conference on Big Data Computing, Applications, and Technologies (BDCAT 2024)” will be held in Sharjah, United Arab Emirates between 16 and and 19 December, 2024.
Recent years witnessed significant interest in the use of Machine Learning and AI-based techniques to support large data analysis, with research and implementation of systems specifically focused on supporting different phases of the data processing lifecycle. These have ranged from in-memory systems and distributed environments (e.g., MapReduce/Hadoop, Spark) to specialist environments for stream processing of data and events (e.g., Flink, Kinesis) and Serverless (e.g., OpenWhisk, AWS Lambda). On the other hand, we also realise the importance of computational systems required to process small data volumes, but which involve interdependencies and relationships that are hard to capture and derive.
The IEEE/ACM International Conference on Big Data Computing, Applications, and Technologies (BDCAT) is a premier annual conference series aiming to provide a platform for researchers from both academia and industry to present new discoveries in the broad area of big data computing and applications. Previous events were held in London, UK (BDCAT 2014), Limassol, Cyprus (BDCAT 2015), Shanghai, China (BDCAT 2016), Austin, USA (BDCAT 2017), Zurich, Switzerland (BDCAT 2018), Auckland, New Zealand (BDCAT 2019), Leicester, UK (BDCAT 2020), Leicester, UK (BDCAT 2021), Vancouver, USA (BDCAT 2022), and Taormina, Italy (BDCAT 2023). The BDCAT 2024 will be held in conjunction with the 17th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2024) in Sharjah, UAE.
The PDF version of the BDCAT 2024 Call for Papers may be downloaded HERE.
Authors are invited to submit original, unpublished research manuscripts in all areas of Big Data computing, applications and technologies, as well as on related scaling data analysis.
Topics of interest include (but not limited to):
1. Machine Learning and Data Mining
• Data Science Models and Approaches
• Data Acquisition, Integration, Cleaning and Best Practices
• Supervised, Unsupervised and Reinforcement Learning
• Neural Networks, Convolution Neural Networks and Recurrent Neural Networks
• Transformer and Natural Language Processing
• Swarm Intelligence and Evolutionary Strategy
• Efficient Model Training, Inference and Serving
• Distributed, Federated and Parallel Learning Algorithms
• Testing, Debugging and Monitoring
• Fairness, Interpretability and Explainability
• Specialized Hardware for Scaling
2. Data Infrastructures and Platforms
• Scalable Computing Models, Theories and Algorithms
• Mapreduce: Hadoop and Spark
• Privacy and Security over the Data Life Cycle
• Data Search and Information Retrieval Techniques
• Extract/Transform/Load (ETL) or ETL Pipelines
• In-Memory Systems and Platforms
• Performance Evaluation Reports
• Storage Systems (including file systems, NoSQL, and RDBMS)
• Resource Management Approaches
• Data Analytics on Edge Devices
• Fault Tolerance and Reliability
• Energy-Efficiency and Sustainability
• Data Archival and Preservation
3. Scaling Data Applications
• Data Applications for Internet of Things, Mobile Applications and Cyber-Physical Systems
• Data Applications for Healthcare and Life Science (e.g., Genome Processing)
• Data Applications for Physical Science and Engineering
• Data Applications for Business and Enterprise Applications
• Data Applications for Social Networks
• Data Applications for Scientific Case Studies
• Data Applications over the Cloud-Edge Continuum
• Data Streaming and Batch Applications
• Data Trends and Challenges
4. Scaling Data Visualization
• Visual Analytics Algorithms and Foundations
• Graph and Context Models for Visualization
• Analytics Reasoning and Sense-making
• Visual Representation and Interaction
• Data Transformation and Presentation
PAPER SUBMISSION
Submitted manuscripts must represent original unpublished research that is not currently under review for any other conference or journal. Manuscripts are submitted in PDF format and may not exceed ten (10) IEEE-formatted *double-column* pages, including figures, tables, and references. All manuscripts undergo a double-blind peer-review process and will be reviewed and judged on correctness, originality, technical strength, rigor in analysis, quality of results, quality of presentation, and interest and relevance to the conference attendees. Your submission is subject to a determination that you are not under any sanctions by IEEE.
At least one author of each paper must be registered for the conference in order for the paper to be published in the proceedings. The conference proceedings will be published by IEEE and made available online via the IEEE Xplore Digital Library and ACM Digital Library.
AWARDS AND SPECIAL ISSUES
A selection committee chaired by the BDCAT 2024 conference co-chairs will select and acknowledge the best paper to receive an award during the conference.
Authors of highly rated papers from BDCAT 2024 will be invited to submit an extended version to special issues of prestigious journals.
Click here for details for CALL FOR PAPERS IEEE/ACM Int’l Conf. on Big Data Computing, Applications, and Technologies BDCAT
