ISSN: 2308-4294
ISBN: 978-1-68558-484-9

• Registered: with the Library of Congress of the United States of America (ISSN)
• Free Access: in ThinkMind Digital Library

CLOUD COMPUTING 2027 is colocated with the following events as part of ComputationWorld 2027 Congress:

• SERVICE COMPUTATION 2027, The Nineteenth International Conference on Advanced Service Computing
• CLOUD COMPUTING 2027, The Eighteenth International Conference on Services, Tools, and Architectures for Cloud Computing
• FUTURE COMPUTING 2027, The Nineteenth International Conference on Future Computational Technologies and Applications
• COGNITIVE 2027, The Nineteenth International Conference on Advanced Cognitive Technologies and Applications
• ADAPTIVE 2027, The Nineteenth International Conference on Adaptive and Self-Adaptive Systems and Applications
• CONTENT 2027, The Nineteenth International Conference on Creative Content Technologies
• PATTERNS 2027, The Nineteenth International Conference on Pervasive Patterns and Machine Learning
• COMPUTATION TOOLS 2027, The Eighteenth International Conference on Computational Logics, Algebras, Programming, Tools, and Benchmarking
• BUSTECH 2027, The Seventeenth International Conference on Business Intelligence and Technology
• AIVR 2027, The Fourth International Conference on Artificial Intelligence and Immersive Virtual Reality
• CROSS-SEC 2027, The Second International Conference on Cross-Domain Security in Distributed, Intelligent and Critical Systems

CLOUD COMPUTING 2027 General Chairs

Christoph P. Neumann Ostbayerische Technische Hochschule Amberg-Weiden Germany

Malte Prieß Kiel University of Applied Sciences Germany

		Christoph P. Neumann Ostbayerische Technische Hochschule Amberg-Weiden Germany
		Malte Prieß Kiel University of Applied Sciences Germany

CLOUD COMPUTING 2027 Steering Committee

		Carlos Becker Westphall Federal University of Santa Catarina Brazil			Aspen Olmsted Wentworth Institute of Technology, Boston USA
		Andreas Aßmuth Kiel University of Applied Sciences Germany			Alex Sim Lawrence Berkeley National Laboratory USA
		Wolfgang Forstmeier Siemens AG Germany			Kunal Rao NEC Laboratories America USA
		Herodotos Herodotou Cyprus University of Technology Cyprus

		Carlos Becker Westphall Federal University of Santa Catarina Brazil
		Aspen Olmsted Wentworth Institute of Technology, Boston USA
		Andreas Aßmuth Kiel University of Applied Sciences Germany
		Alex Sim Lawrence Berkeley National Laboratory USA
		Wolfgang Forstmeier Siemens AG Germany
		Kunal Rao NEC Laboratories America USA
		Herodotos Herodotou Cyprus University of Technology Cyprus

CLOUD COMPUTING 2027 conference tracks:

Cloud Service Computation (orchestration • composition • pervasive services • web and digital ecosystems)
Service composition, orchestration, and choreography models; AI-native service composition in Cloud systems; LLM-driven orchestration layers for service coordination; Semantics-driven service discovery and interoperability; Context-aware and adaptive service provisioning; Pervasive and ubiquitous service architectures; Quality of Service (QoS) modeling and assurance; Workflow automation and dynamic service binding; Web services and API-driven integration frameworks; Cloud - edge - IoT service coordination patterns; Trust, privacy, and resilience in service ecosystems; Service governance, auditing, and policy compliance;  AI-based optimization of service chains and lifecycles; Benchmarking and evaluation of complex service compositions; 

Reasoning and Computation Tools (logic • specification • reasoning • verification • model transformation)
Formal specification languages and modeling frameworks; Logic-based reasoning and constraint solving tools; Symbolic computation and automated theorem proving; Verification and validation of computational models; Model-driven design and transformation techniques; Domain-specific languages for system specification; Runtime monitoring and correctness assurance; Simulation and co-simulation environments; Reconfigurable and adaptive computational toolchains; Human–tool co-design and explainability in computation; Hybrid symbolic–numeric computation frameworks; Open-source and reproducible computational infrastructures

Computing Paradigms (grid • virtualization • new computation paradigms • programing models)
Quantum, neuromorphic, and bio-inspired computation paradigms; Virtualization and containerization for elastic computing; Edge–fog–cloud continuum architectures; Grid and distributed computation frameworks; Programming models for heterogeneous architectures; Green and energy-efficient computing techniques; AI-accelerated computation and algorithmic co-design; Data-centric and in-memory computation methods; Resilient and fault-tolerant distributed systems; Self-optimizing and self-healing computational infrastructures; Security and trust in virtualized computation environments; Benchmarking and performance modeling for emerging computing systems

Cloud Technologies and Architectures (cloud platforms • virtualization • orchestration • resilience)
Cloud service models: IaaS, PaaS, SaaS evolution; Cloud-native architectures and microservice deployment; Virtualization, containerization, and orchestration (Docker, Kubernetes); Software-defined networking (SDN) and network function virtualization (NFV); Multi-cloud and hybrid-cloud interoperability frameworks; Cloud resource scheduling and workload balancing; Resilience, fault tolerance, and elasticity in cloud environments; Cloud security, encryption, and access control mechanisms; Green cloud and energy-aware computing strategies; AI-driven cloud management and optimization;  Cloud observability, monitoring, and SLA assurance;  Governance, policy, and compliance in distributed cloud infrastructures

Cloud Databases  (management • as-a-service • multimodel • security • confidentiality)
Data management in the Cloud, Database-as-a-Service (DBaaS); Cloud- native databases; Distributed and federated databases; NoSQL, NewSQL and multimodel databases; In-memory and real-time cloud databases; Serverless databases; Elastic and autoscaling data stores; High availability and fault tolerance; Disaster recovery and backup in the Cloud; Data migration to and between clouds; Edge and fog databases; Cloud Data lakes and Cloud Lakehouse architectures; Cost-aware database management; Security, privacy and compliance in cloud databases; Confidential and encrypted database processing; Data governance and sovereignty; Benchmarking and evaluation of cloud databases; Cloud database case studies and applications. 

Edge, Fog, and Mobile Edge Computing (low-latency services • continuum computing • proximity intelligence)
Fog computing architectures and coordination strategies; Mobile edge computing for real-time analytics; Service migration and continuity across edge layers; Data caching, replication, and synchronization at the edge; Edge-cloud orchestration and resource allocation; Security and privacy challenges in edge/fog environments; AI and federated learning at the network edge; Edge-enabled IoT and cyber-physical applications; Energy efficiency and adaptive power management in edge systems; Edge-based digital twins and context-aware services; 5G/6G integration with fog and edge computing; Benchmarking, simulation, and standardization efforts for edge computing

Hosted and Hybrid Cloud Services (service delivery • APIs • web real-time communication • integration)
Cloudlets and localized micro-cloud infrastructures; WebRTC-based real-time cloud applications; Containerized service deployment and migration; Microservice architectures for distributed; Continuous integration and deployment pipelines in cloud environments; Cloud computing and 5G/6G service integration; Virtualized network services and programmable infrastructures; Serverless computing and event-driven architectures; Monitoring, debugging, and observability of hosted cloud services; Cloud marketplaces and API economy ecosystems; Cross-domain interoperability and compliance of hosted services

From Cloud-Native to AI-Native Cloud Systems (genAI • LLMs • agentic cloud • cognitive plans •  cloud continuum)
Generative AI architectures for Cloud-native systems; LLMs as Cloud services (LLMaaS); Agentic frameworks for Cloud autonomy; Autonomous agents managing cloud services, pipelines, and operations; Cloud Continuum for AI (Edge–Fog–Cloud AI pipelines); Partitioning generative workloads across the cloud continuum; Dynamic distribution of generative AI workloads; Model-centric APIs and LLM-based Cloud services; LLM-oriented Cloud middleware; AI-augmented Cloud development pipelines; Distributed Vector Databases and Semantic Retrieval in the Cloud; Cognitive control planes for Cloud systems

Deadlines:

Deadlines differ for special tracks. Please consult the conference home page for special tracks Call for Papers (if any).