CCGrid 2019 : IEEE International Symposium on Cluster Computing and the Grid

  in Conferences   Posted on October 8, 2018

Conference Information

Submission Deadline Friday 07 Dec 2018
Conference & Submission Link
Conference Dates May 14, 2019 - May 17, 2019
Conference Address Larnaca, Cyprus
Proceedings indexed by
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Google Scholar H5-index: 37
CORE 2017 Rating: A
Guide2Research Overall Ranking: 83
Category Rankings
Networks and Communications 24
Web, Mobile & Multimedia Technologies 14

Conference Call for Papers

CCGrid 2019 will have a focus on important and immediate issues that are significantly influencing all aspects of cluster, cloud, grid and edge computing.

Topics of interest include, but are not limited to:

Applications and Data Science: Applications to real and complex problems in science, engineering, business, and society; user studies; experiences with large-scale deployments, systems, or applications.
Architecture and Networking: Design and use of emergent system architectures; multicores; power and cooling; power-efficient (\”green\”) computing; security and reliability; high availability solutions; high performance GPU applications.
Cloud Computing: Development, evaluation, and optimization of cloud architectures; software tools and techniques for clouds; virtual machines (VMs), containers, unikernels and microservices.
Autonomic Computing, Datacenters, and Cyberinfrastructure: Self-managed behavior, models and technologies; autonomic paradigms and systems (control-based, bio-inspired, emergent, etc.); datacenter-level security; rack-scale systems.
Programming Models and Runtime Systems: Programming models, systems software and environments for cluster, cloud, and grid computing; fault-tolerant systems, programs and algorithms.
Performance Modelling and Evaluation: Prediction, modeling, and analysis; monitoring and evaluation tools; benchmarks and testbeds.
Scheduling and Resource Management: Techniques to schedule jobs and resources on cluster, cloud, and grid computing platforms; SLA definition and enforcement.
Storage and I/O Systems: System design and optimization for big data processing in cluster and cloud environment.
Edge Computing: Micro-datacenter, cloudlet, edge, or fog computing infrastructure; edge and stream processing.

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