Conference Information
FiCloud 2024: International Conference on Future Internet of Things and Cloud
Submission Date:
2024-04-02 Extended
Notification Date:
Conference Date:
Vienna, Austria
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Call For Papers
Cloud is a modern computing platform for delivering on-demand computing services to service consumers over the Internet. Computing services include, for example, storage, memory, compute power, databases, and networking among others. Cloud services are generally provided using SaaS (Software-as-a-Service), PaaS (Platform-as-a-Service) and IaaS (Infrastructure-as-a-Service). Unlike conventional distributed computing, cloud offers flexibility, scalability, efficiency and elasticity in service provisioning.

The Internet of Things (IoT) vision is to provide a dynamic and global network infrastructure which is characterized by intelligent and self configuring capabilities. IoT is considered as an integral part of the future Internet. It is based on interoperable communication protocols in order to enable the interaction and integration of virtual as well as physical Things such as computers, smart devices, sensors, cars, refrigerators, food packages, medicines, etc. Things can be seamlessly integrated into the information network and interaction can be made through the provision of intelligent interfaces. In not so distant future, IoT will be forcing its way into every aspect of our lives and technologies including smart homes, smart cities, environment and nature, green energy, food, medicine, automotive, aerospace and aviation, telecommunication, and so on.
IoT is generally characterized by real world and small Things, limited capacity, constrained devices and the consequential issues such as less reliability, security and privacy. Cloud computing on the other hand deals mainly with virtual world and has unlimited capabilities in terms of storage and processing power. Thus cloud and IoT are the main complementary aspects of the future Internet. IoT can benefit from the unlimited capabilities and resources of cloud computing. Similarly, cloud can benefit from IoT by extending its scope to deal with real world things in a more distributed and dynamic manner. The theme of this conference is to promote the state of the art in scientific and practical research of the IoT and cloud computing. It provides a forum for bringing together researchers and practitioners from academia, industry, and public sector in an effort to present their research work and share research and development ideas in the area of IoT and cloud computing.


Software Models and Services
Software architectures; Programming models; Services provisioning and management; Requirements analysis and modelling; Service integration; SaaS, IaaS, PaaS; QoS in Cloud and IoT; SOA for Cloud and IoT.

Big Data in Cloud and IoT
Big data; NoSQL databases; Data mining; Data analytics; Storage architectures; Querying and Searching; Data quality; Data and Process Modeling; Tiny/small databases for IoT; Sensor data and stream analytics; Semantics and Ontologies.

Security, Privacy and Trust
IoT and cloud security; Privacy issues; Service Reliability in cloud and IoT; Accountability and audit; Authentication and authorization; Cryptography; Identity theft; Data loss or leakage; Trust management; Fraud Detection.

Context-aware Systems
Context-awareness in cloud and IoT; Location-aware services; Self adaptive services; Context-aware models and protocols; Application domains: Intelligent transportation, buildings, roads, water supply, environment, healthcare.

Networking and Communication Protocols
Transmission protocols; Models and algorithms; Communication protocols for datacentres; Software defined networks; Energy-efficient networks; Network security and privacy; P2P and overlay networks.

Performance Modelling and Evaluation
Performance modelling in cloud and IoT; Evaluation techniques; Performance monitoring; Scheduling and application workflows; Scalability in cloud and IoT; Fault monitoring; Capacity planning and elasticity.

AI and Machine Learning
Machine learning in cloud and IoT; Intelligent data processing; Reinforcement learning; Generative models; Feature Reduction and Extraction; Neural Networks; Supervised/Unsupervised Machine Learning; Continuous Relearning; Anomaly Detection; Pattern Recognition.

Energy Efficiency
Energy efficient service provisioning; Energy efficient resource utlization; Data storage and processing; Energy-efficient networking; Energy metrics and benchmarks; Energy-efficient hardware.

Cloud and IoT Continuum
Cloud and IoT federation, Architectures and models; Virtualization of cloud resources; Network virtualization; Cloud virtualization and IoT; Reliability and security; Inter cloud and multi-cloud.

Fog and Edge Computing
Fog and edge computing models, Cloud at Edges; IoT applications and network edges; IoT data at network edges; Infrastructure for Fog/Edge; Middelware for Fog/Edge computing; Qos in Fog/Edge computing.

Industry Track
Practical applications of cloud/IoT; Industry case studies; Cloud/IoT and Industry 4.0.
Last updated by Dou Sun in 2024-03-31
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