Call for Papers

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The 22nd IEEE/ACM international Symposium on Cluster, Cloud and Internet Computing (CCGrid 2022) is a leading forum to disseminate an discuss research activities and results on a broad range of topics in distributed systems, ranging from computing Clusters to widely distributed Clouds and emerging Internet computing paradigms such as Fog/Edge Computing for Internet of Things (IoT)/Big Data applications. The conference features keynotes, technical presentations, posters, workshops, tutorials, as well as the SCALE challenge featuring live demonstrations and the ICFEC 2022 conference.

We solicit original contributions on all aspects of distributed systems and applications in the context of Cluster, Cloud, and Internet computing environments. Specific topics of interest include but are not limited to the following:

  • Track 1: Future Internet computing systems
    • Internet Computing Frontiers: Edge, Fog, Serverless, Lambda, Streaming, Highly decentralized approaches to cloud computing. Edge/Fog computing, sensor data streaming and computation on the edges of the network. Function as a Service (Faas), Backend as a Service (BaaS), serverless computing, lambda computing.
    • Future Internet: 5G and Use cases of 5G system. Software defined networking and 5G. 5G cyber security challenges and concerns Machine learning algorithms for 5G systems.
    • Osmotic Computing: Cloud Continuum with Osmosis behaviors, Micro Services and MicroData, Software Defined Membranes.
    • Cloud-Economics.

VCs: – Hai Jin, Huangzong University of Science and Technology, China (hjin@hust.edu.cn)
– Lydia Y. Chen, TU Delft, Netherlands (LydiaYChen@ieee.org)

  • Track 2: Programming models and runtime systems
    • Programming Models and Runtime Systems: Programming models, languages, systems and tools/environments. Virtualization, containers, and middleware technologies. Actors, agents, programming decentralized computing systems.

VCs: – Taisuke Boku, University of Tsukuba, Japan(taisuke@cs.tsukuba.ac.jp)
– Martin Schulz, Technical University of Munich, Germany (schulzm@in.tum.de)

  • Track 3: Distributed middleware and network architectures
    • Architecture, Networking, Data Centers: Service oriented architectures. Utility computing models. IaaS, PaaS, SaaS, *aaS paradigms. Service composition and orchestration. Software-Defined Network-enabled Systems. Micro-datacenter, cloudlet, edge, or fog computing infrastructure. Virtualized hardware: GPUs, tensor processing units, FPGAs.
    • Artificial Intelligence: Large Scalable Machine Learning, AI at the Edge and in the Cloud. Cognitive computing.
    • Cloud-to-Things continuum: Service provisioning and monitoring in a Cloud-to-Things environment; Resource elasticity in Cloud-to-Things contexts; Algorithms and systems for automated elasticity; Blockchain-based resource orchestrator; Machine learning techniques for resource orchestration; Security policies in Cloud-to-Things.

VCs: – Nectarios Koziris, National Technical University of Athens, Greece (nkoziris@cslab.ece.ntua.gr)
– Hari Subramoni, Ohio State University, USA (subramoni.1@osu.edu)

  • Track 4: Storage and I/O systems
    • Storage and I/O Systems: Distributed storage, cloud storage, Storage as a Service, data locality techniques for in-memory processing, storage in the edge.

VCs: – Suren Byna, Lawrence Berkeley National Laboratory, USA (sbyna@lbl.gov)
– Maria S. Perez, Universidad Politecnica de Madrid, Spain (mperes@fi.upm.es)

  • Track 5: Security, privacy, trust and resilience
    • Cyber-Security, Privacy and Resilient Distributed Systems: Distributed Systems security and trust. Access control. Data privacy and integrity. Regulation. Resiliency of service attacks.

VCs: – Erman Ayday, Case Western Reserve University, USA (exa208@case.edu)
– Richard Sinnott, U. Melbourne, Australia (rsinnott@unimelb.edu.au)

  • Track 6: Performance modeling, scheduling, and analysis
    • Resource Management and Scheduling: Resource allocation algorithms, profiling, modeling. Cluster, cloud, and internet computing scheduling and meta-scheduling techniques.
    • Performance Modelling and Evaluation: Performance models. Monitoring and evaluation tools. Analysis of system/application performance.

VCs: – Sameer Shende, University of Oregon, USA (sameer@cs.uoregon.edu)
– Ana Lucia Varbanescu, University of Amsterdam, Netherlands (a.l.varbanescu@uva.nl)

  • Track 7: Sustainable and green computing
    • Sustainable and Green Computing: Environment friendly computing ecosystems. Hardware/software/application energy efficiency. Power, cooling and thermal awareness.

VCs: – Young Choon Lee, Macquarie U., Australia (young.lee@mq.edu.au)
– Wu Feng, Virginia Tech, USA (feng@cs.vt.edu)

  • Track 8: Scientific and industrial applications
    • Applications: Data Science, Artificial Intelligence, Machine Learning, Cyber-Physical Systems, e-Health, Internet of Things (IoT)-enabled Smart Systems and Applications.
    • Digital Twins: Digital Twins and Industry 4.0. Digital Twins and emerging technologies linked to IoT Platforms. Digital Twin the virtual replica of a physical entity.

VCs: – Vipin Chaudhary, Case Western Reserve University, USA (vxc204@case.edu)
– Dana Petcu, West University of Timisoara, Romania (dana.petcu@e-uvt.ro)