Parallel and Distributed Computing (PDC) is an important research area today and has a strong contribution to the advancements in science, engineering, and society at large. Its evolution is characterized by the continuous development of new approaches in the modeling, design, analysis, evaluation, and programming of parallel and distributed computing applications and systems. 

The goal of the 21st International Symposium on Parallel and Distributed Computing (ISPDC 2022) is to bring together researchers, engineers, and practitioners for the purpose of sharing their experiences in the development of new algorithms, applications, architectures for parallel and distributed computing, as well as modeling and simulation, visualization, and data analytics. 

We cordially invite you to submit your contributions to ISPDC 2022. The event will host invited talks, presentations of contributed papers, and industrial sessions. The Proceedings of the ISPDC 2022 conference will be published in IEEE Xplore digital library (conference record #_____), indexed by Scopus (Elsevier) and Web of Science (WoS). 

Authors are invited to submit manuscripts that present original and unpublished research in all areas of parallel and distributed computing and applications. The ISPDC 2022 conference scope is focused on, but not limited to, the following topics:

Architectures and Environments for Parallel/Distributed Computing and Mobile Computing

    Methods and Tools for Parallel and Distributed Programming Design/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, 
    Embedded, Mobile and Network Environments

Parallel and Distributed Computing – Algorithms and Models for 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

Performance Modeling, Management, and Optimization

    Performance Modeling, Analysis and Evaluation for Parallel/Distributed System
    Scheduling and Load Balancing
    Resource Management
    Execution Control Optimization
    Optimization and Dependability

Parallel and Distributed Computing for Large Scale Applications

    Scalable Algorithms and Applications
    Urban Networks and Applications
    Vehicular Networks
    Parallel, Distributed and Mobile Big-Data Management
    Smart Applications
    Ubiquitous Distributed Computing

Parallel/Distributed Embedded Computing for Critical Systems

    Collaborative Computing
    P2P Computing
    Mobile and Ubiquitous Computing
    Web Services and Internet Computing
    Distributed Software Components
    Multi-agent Systems
    Parallel Embedded Systems Programming
    Highly Embedded Parallel Systems Support for Programming
    FPGA and SoC/NoC Solutions
    Real-time Distributed and Parallel Systems
    Reactive Distributed and Parallel Systems

Cloud and Edge Computing

    Cloud Resource Provisioning and Allocation
    Pricing of Cloud Resources
    Cloud Performance and Capacity Management
    Green Cloud Computing
    Mobile Clouds
    Cloud Computing Techniques for Big Data
    Storage Architectures for Clouds and Big Data Processing
    Fog Computing and Networking architectures
    Edge-Cloud Interactions and Enabling Protocols
    System and Service Management
    Edge Resource Management
    Distributed Data Centers
    Edge Data Analytics
    Edge Caching

Security and Privacy in Distributed Systems 

    Cloud Security and Privacy
    Virtualization-based Security
    Operating System Level Security
    Security and Privacy of Data 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
    Adversary Emulation
    Applied Cryptography
    End-host Security
    Applications of Machine Learning in Distributed Systems Security
    Machine Learning Models for Malware Detection
    Big Data Techniques for Security Reasoning

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
    Data Anonymity and Privacy
    IoT and Blockchain
    Decentralized Artificial Intelligence

Connectivity and Interactivity

    IoT
    Social Networks
    QoS in Distributed Systems
    Visualization of Massively Parallel Data