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CCGrid 2022 : IEEE International Symposium on Cluster Computing and the Grid

CCGrid 2022 : IEEE International Symposium on Cluster Computing and the Grid

Taormina, Italy

Submission Deadline: Wednesday 24 Nov 2021

Conference Dates: May 16, 2022 - May 19, 2022

Research
Impact Score 4.12

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Ranking & Metrics Impact Score is a novel metric devised to rank conferences based on the number of contributing top scientists in addition to the h-index estimated from the scientific papers published by top scientists. See more details on our methodology page.

Research Impact Score: 4.12
Contributing Top Scientist: 37
Papers published by Top Scientists 57
Research Ranking (Computer Science) 147

Conference Call for Papers

The 22nd IEEE/ACM international Symposium on Cluster, Cloud and Internet Computing (CCGrid 2022) is a leading forum to disseminate and 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:

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.

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.

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

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

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.

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

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

Applications: Data Science, Artificial Intelligence, Machine Learning, Cyber-Physical Systems, e-Health, Internet of Things (IoT)-enabled Smart Systems and Applications.

Artificial Intelligence: Large Scalable Machine Learning, AI at the Edge and in the Cloud. Cognitive computing.

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.

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-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

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