International Conference on Big data and Cloud Computing at VIT

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College Name: Vellore Institute of Technology


About College:
VIT was founded in 1984 as Vellore Engineering College by the Chancellor Dr. G. Viswanathan. From its humble beginning, the institution has grown exponentially to that of having more than 33,000 students. Students from all the states of India and from more than 50 countries are studying at VIT. Deemed University status was conferred in 2001 by MHRD Govt. of India in recognition of its excellence in academics, research and extracurricular initiatives. Currently, VIT has 4 campuses – in Vellore, Chennai, Amaravati (AP) and Bhopal (MP).

Event: 6th International Conference on Big data and Cloud Computing (ICBCC 2019)

Event Date: 9th – 10th September 2019

Organized by: School of Computing Science and Engineering

Conference Tracks:

  • Architecture
    Cloud Infrastructure as a Service
    Cloud Platform as a Service
    Cloud federation and hybrid cloud infrastructure
    Programming models and systems/tools
    Green data center
    Networking technologies for data center
    Cloud system design with FPGA, GPU, and APU
    Monitoring, management and maintenance
    Economic and business models
    Dynamic resource provisioning
  • MapReduce
    Performance characterization and optimization
    MapReduce on multi-core, GPU
    MapReduce on hybrid distributed environments
    MapReduce on opportunistic / heterogeneous computing systems
    Extension of the MapReduce programming model
    Debugging and simulation of MapReduce systems
    Data-intensive applications using MapReduce
    Optimized storage for MapReduce applications
    Fault-tolerance & Self-capabilities
  • Security and Privacy
    Accountability
    Audit in clouds
    Authentication and authorization
    Cryptographic primitives
    Reliability and availability
    Trust and credential management
    Usability and security
    Security and privacy in clouds
    Legacy systems migration
    Cloud Integrity and Binding Issues
  • Services and Applications
    Cloud Service Composition
    Query and discovery models for cloud services
    Trust and Security in cloud services
    Change management in cloud services
    Organization models of cloud services
    Innovative cloud applications and experiences
    Business process and workflow management
    Service-Oriented Architecture in clouds
  • Virtualization
    Server, storage, network virtualization
    Resource monitoring
    Virtual desktop
    Resilience, fault tolerance
    Modeling and performance evaluation
    Security aspects
    Enabling disaster recovery, job migration
    Energy efficient issues
  • HPC on Cloud
    Load balancing for HPC clouds
    Middleware framework for HPC clouds
    Scalable scheduling for HPC clouds
    HPC as a Service
    Performance Modeling and Management
    Programming models for HPC clouds
    HPC cloud applications
    Optimal cloud deployment for HPC
  • Big Data Science and Foundations
    Novel Theoretical Models for Big Data
    New Computational Models for Big Data
    Data and Information Quality for Big Data
    New Data Standards
  • Big Data Infrastructure
    Cloud/Grid/Stream Computing for Big Data
    High Performance/Parallel Computing Platforms for Big Data
    Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment
    Energy efficient Computing for Big Data
    Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data
    Software Techniques and Architectures in Cloud/Grid/Stream Computing
    Big Data Open Platforms
    New Programming Models for Big Data beyond Hadoop/MapReduce, STORM
    Software Systems to Support Big Data Computing
  • Big Data Management
    Advanced database and Web Applications
    Novel Data Model and Databases for Emerging Hardware
    Data Preservation
    Data Provenance
    Interfaces to Database Systems and Analytics Software Systems
    Data Protection, Integrity and Privacy Standards and Policies
    Information Integration and Heterogeneous and Multi-structured Data Integration
    Data management for Mobile and Pervasive Computing
    Data Management in the Social Web
    Crowd sourcing
    Spatiotemporal and Stream Data Management
    Scientific Data Management
    Workflow Optimization
    Database Management Challenges: Architecture, Storage, User Interfaces
  • Big Data Search and Mining
    Social Web Search and Mining
    Web Search
    Algorithms and Systems for Big Data Search
    Distributed, and Peer-to-peer Search
    Big Data Search Architectures, Scalability and Efficiency
    Data Acquisition, Integration, Cleaning, and Best Practices
    Visualization Analytics for Big Data
    Computational Modeling and Data Integration
    Large-scale Recommendation Systems and Social Media Systems
    Cloud/Grid/Stream Data Mining- Big Velocity Data
    Link and Graph Mining
    Semantic-based Data Mining and Data Pre-processing
    Mobility and Big Data
  • Big Data Security & Privacy
    Intrusion Detection for Gigabit Networks
    Anomaly and APT Detection in Very Large Scale Systems
    High Performance Cryptography
    Visualizing Large Scale Security Data
    Threat Detection using Big Data Analytics
    Privacy Threats of Big Data
    Privacy Preserving Big Data Collection/Analytics
    HCI Challenges for Big Data Security & Privacy
    User Studies for any of the above
    Sociological Aspects of Big Data Privacy
  • Big Data Applications
    Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance
    Business, Law, Education
    Transportation, Retailing, Telecommunication
    Big Data Analytics in Small Business Enterprises (SMEs)
    Big Data Analytics in Government, Public Sector and Society in General
    Real-life Case Studies of Value Creation through Big Data Analytics
    Big Data as a Service
    Big Data Industry Standards
    Experiences with Big Data Project Deployments
  • Recent trends
    Semantic Cloud
    Mobile Cloud
    e-Healthcare Applications in Cloud
    Cloud analytics for Internet of Things (IoT)
    Smart Grid
  • Industrial Tracked
    The Industrial Track solicits papers describing implementations of Big Data solutions relevant to industrial settings. The focus of industry track is on papers that address the practical, applied, or pragmatic or new research challenge issues related to the use of Big Data in industry. We accept full papers (up to 6 pages) and extended abstracts (2-4 pages).

Paper Submission: Clickhere

Publication: All accepted papers will be Published in Smart Innovation, Systems and Technologies – Springer, and made available through SpringerLink Digital Library, one of the world’s largest scientific libraries. Proceedings are submitted for inclusion to the leading indexing services: ISI Proceedings, EI-Compendex, SCOPUS, Google Scholor and Springerlink.

Important Dates:
  • Tutorial/Workshop Proposal- 15th April, 2019
  • Full Paper/Poster Submission- 15th July, 2019
  • Notification of Acceptance- 31st July, 2019
  • Camera-Ready Papers- 10th August, 2019
Venue:
Ewing Marion Kauffman Foundation Conference Center
UNIVERSITY OF MISSOURI-KANSAS CITY (UMKC)| Kansas City | USA
Contact Details:

Vellore Institute of Technology,
Vandalur – Kelambakkam Road Chennai,
Tamil Nadu – 600 127
vijayakumar.v@vit.ac.in
Mobile: +919942057843

Event Website: Clickhere

College Website: Clickhere


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