ISSN:
ISBN: 978-1-68558-319-4

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

SCALABILITY 2025 is colocated with the following events as part of TechWorld 2025 Congress:

• EXPLAINABILITY 2025, The Second International Conference on Systems Explainability
• SCALABILITY 2025, The Second International Conference on Systems Scalability and Expandability
• VEHICULAR ANALYTICS 2025, The Second International Conference on Vehicular Systems
• WIRELESS ANALYTICS 2025, The Second International Conference on Wireless and Telecommunications

SCALABILITY 2025 conference tracks:

Scalability-driven Data Centers and Cloud computing solutions
Scalability concepts, challenges, and taxonomies
Scalability vs. Availability, Performance, and Resilience
Scalability vs Security in edge resources (Privacy, Trust)
Scalability and High-Performance Computing (HPC)
Opportunistic and cheap computing
Scalability: Data Center vs the Cloud Computation vs Micro Data Centers
Scalability: Clouds vs Edge clouds vs Edge computing vs Fog computing
Scalable architectures for on-site Data centers, in Cloud Data Centers and Cloud computing
Scalability mechanisms (virtualization, containerization, optimal placement of virtual machines)
Patterns-driven scalability (distribution, caching, and asynchronous processing)
Design for scalability (load balancing, preventive monitoring, predictive scalability changes)
Scalability for mobile computing (mobile devices)
Data-driven Scalability design (big data, stream data, etc.)

Scalable Systems/Platforms
Delivery models scalability (On Premise; Co-location; Hosting; Infrastructure-as-a-Service (IaaS); Platform-as-a-Service (PaaS); Software-as-a-Service (SaaS); Business-Process-as-a-Service (BPaaS))
Cost and scalability trade-off (CAPEX, OPEX)
Scalability and elasticity of Cloud Services for BPaaS
Centralized/decentralized Cloud computing versus Edge/Fog computing
Vertical, Horizontal, and Hybrid Scalability
Built-in scalability and self-triggered scalability actions
Intelligent computing and caching at the network edge

Scalable Hardware/Software Solutions
Software agile scalable methodologies
Design Scalable Software (micro-services, containerization, avoid bottlenecks, single point of failure, favor horizontal scaling, scalability architectural patterns, cashing, APIs, tracking scalability metrics. asynchronous processing, etc.)
Scalable programming
Operating Systems supporting scalability
Scalable Hardware: scalable racks, CPU speed, hardware reconfiguration via matrix, on-chip reconfiguration, scalable servers, blade servers, scalable (multiple) WAN connections, API Gateways, etc.)
Hardware Solid State Drives (SSDs)
Scalable predictive pre-cashing mechanisms
Redundancy clusters and server load balancing for failover
Scalable protocols and algorithms
Scalability in Tier Platforms

Storage/Data Bases
Data-driven frameworks in edge/fog computation
Scaling via Database-as-a-Service (DBaaS)
Emerging High Performance Computing (HPC) workloads
Storage optimization in in Deep Learning Frameworks
Data Exchange in HPC Multi-component workflows
Management frameworks for Deep learning
Multi-tiered storage to accelerate I/O, parallel I/O
Scalability of Databases, Storage, and I/O memory access
Scalability and Bottleneck on Databases access (I/O)
Scalable Storages: Databases, NoSQL storages, Service Registries, File systems, etc.
Redundancy clusters and server load balancing for failover
Scaling in NoSQL, schemaless databases

Distributed Edge/Fog Computing Scalability
Edge/Fog/Cloudlets computing- specific scalability aspects
Scalability metrics and monitoring in distributed computing environment
Horizontal and vertical scalability in edge/fog computing
Scalability in mixed systems - centralized cloud and edge/fog computing
Management, orchestration, and resource scheduling for scaling in edge/fog computing
Scalable storage and data management for edge/fog computing
Scalability of edge/fog systems in mission critical applications 
VM migration for scaling in fog/edge and mobile computing
SDN control in edge/fog computing- scalability aspects
Intelligent computing and caching at the network edge
Machine learning and Deep learning at the edge
Multi-domain, multi-operator, and end-to-end edge/fog systems
Multi-access edge (MEC) computing scalability
Edge/fog computing scalability in IoT environments
Edge computing and 5G

Scalability monitoring/management
Scaling Strategies (Manual/Scheduled/Automatic)
Tailored monitoring frameworks (e.g., AWS Cloudwatch for AWS -Amazon)
Management of incremental backup
Preventive scaling (adaptive frequency for scaling changes, dynamic, auto-scaling)
SDN control of network topology and connectivity in edge/fog computing- scalability aspects
Orchestration and management - scalability-oriented design
Multi-domain, multi-operator, and end-to-end edge/fog systems
Scalability aspects in sliced systems
Scalability of Machine Learning and Deep Learning for Pattern-based scalability
Management of cold/warm/hot stand-by scalability components insider Data Centers
Datasets for pre-testing scalability via Load tests
Autonomic and cognitive management support for scalability
Scalable solutions for managed cloud-based databases (e.g., AWS Dynamodb, Google Firestore)

Services/Access/Experiments
Client virtualization (desktop, apps)
User requirements for scalability
Interfaces and User-oriented scalability
Personalized, reactive, adaptable interactions
User scalability via "pay as you go" (with resource allocation mechanisms)
Service scalability in different platforms
Access control, QoS/QoE/SLAs, feedback interactions
Massive scalability platforms (Internet-based systems: Google, Amazon, Facebook, Twitter)
Experiences, experiments, lessons learned, open issues (OpenStack Cloud, Azure, etc.)

Where is scalability important (and counting)?
Edge computing scalability in IoT environments
Massive scalability platforms (Internet-based systems: Google, Amazon, Facebook, Twitter)
Scalability in Industry 4.0/5.0
Scalability-oriented design in 5G/6G sliced systems
Scalability for autonomous vehicles and smart health
Scalability on monitoring energy systems
Fluid dynamics - physical simulation coupled with deep learning
Neuroscience/brain models and scalable simulations
Scalable systems (hydrodynamics, nuclear reactions, gravity, thermal conduction, magnetic fields, and radiation)

Deadlines:

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