Authors are invited to submit manuscripts in the form or short (5 pages) or full papers (8 pages) that present original and unpublished research as well oral communications (1-4 pages description) about previously published work, position papers, and results from R&D projects in all areas of parallel and distributed computing and applications. The IEEE ISPDC 2023 conference scope is focused on, but not limited to, the following topics:

Efficient Support for the Computing Continuum (combining HPC, Cloud and Edge Computing)

• Cloud Resource Provisioning and Allocation
• Pricing of Cloud Resources
• Cloud Performance and Capacity Management
• Green Cloud Computing
• Cloud Computing Techniques for Big Data
• Storage Architectures for Clouds and Big Data Processing
• Distributed Data Centers
• Fog Computing and Networking architectures
• Edge-Cloud Interactions and Enabling Protocols
• Edge Resource Management
• IoT
• Edge Data Analytics
• Edge Caching
• Collaborative Computing
• Web Services and Internet Computing
• Multi-agent Systems
• Real-time and Reactive Distributed and Parallel Systems
• System and Service Management

Algorithms and Models for Large Scale Applications

• Algorithms, Models and Formal Verification
• Model Checking for Parallel Computing
• Algorithms for Data Science, Data Exploration and Graph Analytics
• Parallel Programming Paradigms and APIs
• GPU Programming
• Bio-Inspired and Nature-Inspired Parallel Algorithms
• Parallel and Distributed Algorithms for Deep Learning
• Social Networks
• Scalable Algorithms and Applications
• Urban Networks and Applications
• Vehicular Networks
• Parallel, Distributed Big-Data Management
• Smart Applications
• Visualization of Massively Parallel Data
• Decentralized Artificial Intelligence

Architectures and Environments for Parallel and Distributed Computing

• Methods and Tools for Parallel and Distributed Programming Design and Analysis
• Multi-Cores, Clusters and Grid Computing
• Architectures and Software for In-Memory Computing
• Systems Architectures for Graph Computing/Processing
• Innovative Systems Architectures for Big Data Processing
• Virtualization
• Network Architectures for HPC and Data Centers

Performance Modeling, Analysis and Evaluation for Parallel and Distributed Systems

• Scheduling and Load Balancing
• Resource Management
• Execution Control Optimization
• Performance Modeling, Management and Optimization
• QoS in Distributed Systems
• Energy Efficiency
• Green and Sustainable Computing

Security and Privacy in Parallel and Distributed Systems

• Cloud Security and Privacy
• Virtualization-based Security
• Operating System Level Security
• Data Security and Privacy in Social Networks
• Security of Distributed IoT Systems
• Penetration Testing of Distributed Applications
• Security Tools for Distributed Applications (Programming Languages, Compilers, Analysis Tools etc.)
• Security and Privacy of Distributed Mobile Applications
• Network Security and Isolation
• Adversary Emulation
• Applied Cryptography
• Isolation Techniques
• Applications of Machine Learning in Distributed Systems Security
• Machine Learning Models for Malware Detection
• Big Data Techniques for Security Reasoning
• Data Anonymity and Privacy
• Software Defined Networks

Blockchain and Distributed Ledgers

• Distributed Consensus
• Transaction Throughput and Scalability Issues
• Decentralized Application Development using Smart Contracts
• Asset Tracking and Financial Services
• Blockchain and Energy Systems

Mobile and Embedded Computing

• Parallel Embedded Systems Programming
• Highly Embedded Parallel Systems Support for Programming
• FPGA and SoC/NoC Solutions
• Embedded, Mobile and Network Environments
• Mobile and Ubiquitous Distributed Computing
• Mobile Data Management
• Mobile Clouds