IEEE JCC 2024 Call For Papers

The theme of the IEEE JCC 2024 conference revolves around "Joint-Cloud Computing Meets Large-Scale Foundation Models." This conference primarily serves as a platform for scholars and practitioners to exchange innovative ideas and disseminate the latest research findings in the realm of collaborative cloud computing basic technologies. Furthermore, the conference places a strong emphasis on the pivotal role that these technologies play in supporting the training and inference processes of large-scale foundation models, as well as the construction of robust computing power networks. This includes the effective integration of local computing resources, supercomputing infrastructure, and intelligent computing resources. The overarching objective of the forum is to foster comprehensive discussions surrounding practical experiences and insights derived from real-world applications in the field.


TOPICS

The scope of JCC2024 includes, but is not limited to, the following topics:

 

  • • Foundational theories and algorithms

  • • Cloud computing for large foundation models

  • • Inference and deployment for large foundation models

  • • Connection between HPC and intelligent computing

  • • The construction of computing networks

  • • Cloud supervision and cloud governance

  • • Cloud-based big data and AI applications

  • • Cloud-Edge computing

  • • Compute-continuum

  • • Inter-cloud computing

  • • Computing network convergence

  • • Information-centric networking

  • • Data center and network architectures

  • • Security, privacy, and trust technologies

  • • AI technologies for systems and systems for AI

  • • Resource and scheduling technologies

  • • Economics, Case studies, practices, and empirical evaluation

  • • Deployment, management, and maintenance technologies

  • • Performance, reliability and availability technologies

  • • Interoperation and integration technologies

  • • Migration and transformation of workloads


SUBMISSION

All contributions should be original, not published elsewhere, or intended to be published during the review period. 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.

Research papers are limited to 8 pages, and survey papers are limited to 10 pages, and experience/industry papers are limited to 6 pages, including references. JCC does NOT use double-anonymous reviews. Authors must submit their papers to the Easychair platform. Authors must submit their papers at: https://easychair.org/my/conference?conf=jcc2024

PUBLICATION

All accepted papers will be published by the IEEE Computer Society Press (EI Index) 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), such as IEEE Transactions on Emerging Topics in Computational Intelligence.

DATES

  • Abstract submission: April 7, 2024

  • Submission Deadline: April 28, 2024

  • Author’s notification: June 1, 2024

  • Final camera-ready paper submission: June 15, 2024

  • Conference registration: June 15, 2024

  • Conference dates: July 15 – 18, 2024

Accepted Papers

Full Papers:

  • Chenhui Ji, Dingji Li, Zeyu Mi, Yubin Xia, Prometheus Migrate: Efficient Live Migration of Confidential Virtual Machine with Software Abstraction
  • Jinghao Wang, Guangzu Wang, Tianyu Wo, Xu Wang, Renyu Yang, RESCAPE: Resource Estimation System for Microservices with Graph Neural Network and Profile Engine
  • Yaojie Li, Peichang Shi, Jianfei Liu, Rui Li, Fei Gao, Penghui Ma, Dong Xie, Guodong Yi, DCSA: The Deployment Mechanism of Chained Serverless Applications in JointCloud Environment
  • Junchen Li, Yang Zhang, Kele Xu, Tao Wang, Huaimin Wang, Understanding the Challenges of Data Management in the AI Application Development
  • Antonios Makris, Ioannis Kontopoulos, Stylianos Nektarios Xyalis, Evangelos Psomakelis, Theodoros Theodoropoulos, Andreas Varvarigos, Konstantinos Tserpes, A Study on the Performance of Distributed Storage Systems in Edge Computing Environments
  • Chang Deng, Zheyun Shen, Dingji Li, Zeyu Mi, Yubin Xia, The Design and Optimization of Memory Ballooning in SEV Confidential Virtual Machines
  • Rui Li, Huaimin Wang, Peichang Shi, Bi-Objective Scheduling Algorithm for Hybrid Workflow in JointCloud

  • Jie Wang, Huanxi Liu, Dawei Feng, Bo Ding, FP4-Quantization: Lossless 4bit Quantization for Large Language Models

Short papers:

  • Jiacheng Yang, Guodong Yi, Fei Gao, Peichang Shi, Huaimin Wang, Fairness-Aware AI-Workloads Allocation Considering Multidimensional User Demands in JointCloud
  • Chao Wang, Suzhen Pei, Jiawei Ding, Tianyu Zhong, Binbin Wu, IBCM: An IoT Solution for Building Collapse Monitoring in Smart Cities
  • Rasha Kadhem, Mazin S. Mohammed, Souheyl Mallat, Mounir Zrigui, A recommendation system based on the semantic content using Arabic texts
  • Vasiliki Liagkou, Evangelia Filiopoulou, George Fragiadakis, Mara Nikolaidou, Christos Michalakelis, The cost perspective of adopting Large Language Model-as-a-Service
  • Hoa Tran-Dang, Dong-Seong Kim, Parallel Computation in Dynamic Fog Computing Networks: A Multi-Armed Bandit Learning-based Decentralized Matching Approach
  • Weiyu Peng, Jinghao Wang, Tianyu Wo, Renyu Yang, Precision Probe: Non-intrusive Performance Analysis Tool for Deep Learning Recommendation Training Jobs