Big Data and Cloud Computing: Select Proceedings of ICBCC 2022

ISBN-13: 9789819910502 / Angielski

V. Neelanarayanan; Lipo Wang; Xavier Fernando

Opis

The book presents papers from the 7th International Conference on Big Data and Cloud Computing Challenges (ICBCC 2022). The book includes high-quality, original research on various aspects of big data and cloud computing, offering perspectives from the industrial and research communities on addressing the current challenges in the field. This book discusses key issues and highlights recent advances in a single broad topic applicable to different sub-fields by exploring various multidisciplinary technologies. This book supports the transfer of vital knowledge to next-generation researchers, students, and practitioners in academia and industry.

Spis treści

Table of contents:

Track 1: Architecture

Sample topics include,

- 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

 

Track 2: MapReduce

Sample topics include,

-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

 

Track 3: 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

 

Track 4: 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

Track 5: 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

 

Track 6. 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

 

           Track 7. 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

 

           Track 8.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

 

           Track 9. 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

 

           Track 10. 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

 

           Track 11. 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

 

           Track 12. 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

 

           Track 13. Recent trends

 

-Semantic Cloud

-Mobile Cloud

-e-Healthcare Applications in Cloud

-Cloud analytics for Internet of Things (IoT)

-Smart Grid

-Fog Computing

-Edge Computing

-Deep Learning

-CNN

 

O autorze

Neelanarayanan Venkataraman received his Master of Science in Computer Science from Madurai Kamaraj University, India, in 1995 and his Ph.D. from IT University of Copenhagen, Denmark, in 2012. Currently, he is Professor at VIT University, Chennai, India. Before joining VIT University, he worked as Scientist at the Centre for Advanced Computing (CDAC), India, and as Lecturer at Madurai Kamaraj University, India, and its affiliated institutions. His areas of research include distributed computing such as grid and cloud computing, context-aware computing, network management and security, XML-based security technologies, and e-communities. He has initiated several international research collaborations with universities in Europe, Australia, and South Korea as Research Group Coordinator and Chief Investigator at VIT University. He was instrumental in initiating joint research collaboration between VIT University and industries such as CDAC, SET, and DLink. He served as Head of the department in Cyber-Physical Systems between 2019 and 2023. As head of the department, he was responsible for the design and development of curriculum and syllabi for undergraduate and postgraduate specialization programs. He was instrumental in setting cyber-physical systems lab and an industry 4.0 lab at VIT University, Chennai.

 

Lipo Wang received a bachelor’s degree from the National University of Defense Technology (China) and a Ph.D. from Louisiana State University (USA). He is presently on the faculty of the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His research interest is artificial intelligence with applications to image/video processing, biomedical engineering, communications, control, and power systems. He has 350+ publications, a US patent in neural networks, and a patent in systems to his credit. He has co-authored 2 monographs and (co-)edited 15 books. He was Keynote Speaker for 36 international conferences. He is/was Associate Editor/Editorial Board Member of 30 international journals, including 4 IEEE Transactions, and Guest Editor for 15 journal special issues. He was a member of the Board of Governors of the International Neural Network Society, IEEE Computational Intelligence Society (CIS), and the IEEE Biometrics Council.

 

Xavier Fernando is a Professor at the Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada. He has (co-)authored over 200 research articles, and two books (one translated into Mandarin), and holds a few patents and non-disclosure agreements. He is the Director of Ryerson Communications Lab. He was an IEEE Communications Society Distinguished Lecturer and delivered close to over 50 invited talks and keynote presentations all over the world. His research interests are in signal processing for optical/wireless communication systems. He mainly focuses on physical and MAC layer issues. He has a special interest in underground communications systems of cognitive radio systems, visible light communications, and wireless positioning systems.

 

Ahmed F. Zobaa received his B.Sc. (Hons), M.Sc., and Ph.D. degrees in Electrical Power & Machines from Cairo University, Egypt, in 1992, 1997, and 2002, respectively. He received his Postgraduate Certificate in Academic Practice from the University of Exeter, the UK, in 2010. He received the Doctoral of Science from Brunel University London, the UK, in 2017. Currently, he is Reader in electrical and power engineering. His main areas of expertise include power quality, (marine) renewable energy, smart grids, energy efficiency, and lighting applications.