ISORC has become established as the leading event devoted to state-of-the-art research in the field of object/component/service-oriented real-time distributed computing (ORC) technology. In addition to the main conference, ISORC 2024 will host a special session dedicated to posters and demos, where participants will be able to show prototypes, tools, simulators, and systems, which demonstrate the applicability of real-time computing to different applications.

Best Paper and Student Paper Awards will be delivered during the conference.

Main Theme and Topics

We solicit high-quality papers pertaining to all aspects of ORC technology and especially those that are well aligned with the 2024 theme. Authors are encouraged to consider submissions with a practical orientation and validation related to Case Studies & Applications in this area. The specific ORC focus areas include, but are not limited to:

    Software architectures for real-time distributing computing: programming paradigms, ORC paradigms, object/component models, languages, synchronous languages.

    Distributed Real-Time Image, video and Stream Processing: Real Time Deep Learning, Real Time Methods and Algorithms, Federated Learning Techniques for Image Segmentation and Algorithm, distributed and parallel AI/ML Target Detection and Tracking, Real-Time stream processing with Kafka Apache Spark and Apache Flink, AI/ML for real time image and video processing, distributed Digital Signal Processing in Communications, decentralized emerging technologies for real time, real time Image and signal processing Applications

    Distributed Communication for Emerging and Future Networks: Real-time communications, networked platforms, protocols (WPAN, LPWAN, NB-IoT, 5G cellulars), Internet QoS, Peer-to-Peer computing, sensor networks, VANETS and V2V and V2I communications, time-predictable systems and hardware, Time Sensitive Networking, AI-powered Metaverse, real-time packet processing for future networking infrastructures, Network Function Virtualization (NFV), Network Slicing, Digital twin for NGN and real-time data processing, .

    Blockchain and Distributed Ledger Technology (DLT) for Distributed Computing: Blockchains architectures and their interoperability and scalability, Layer-2 solutions (e.g., state and side channels, DeFi protocols and NFTs, optimistic rollup Bundle, Zero Knowledge Rollup, off-chain), Layer 3 Blockchain protocols (e.g., interoperable protocols and cross-chain DApps, cross-chain RT applications), Self-Sovereign Identity (SSI), consensus protocols and smart contracts, Blockchain oracles, Cryptographic techniques, etc.

    Artificial Intelligence and Machine Learning for Real Time Distributed Computing: Real-time machine learning, Parallel and distributed AI/ML approaches, Federated Learning, TinyML, and EdgeAI for real-time IoT, trusted and dependable systems, complex systems of systems, model maintenance, Ensemble Machine Learning Models for real-time IoT and CPS , Large Language Model (LLM) for future in Next Generation Communications.

    CyberSecurity and Security of Distributed Real Time IoT Systems: Cyber security of critical infrastructures, cyber defense of real-time IoT, Zero Trusted Architecture for Real-time IoT, Data Encryption, Privacy-preserving, Homomorphic encryption, Arbitrary code execution, Backdoors, Code injection, Botnets, Ensemble Learning for Anomalies and Attacks Detection, etc.

    Optimization Approaches for Distributed Real Time IoT and CPS and Cloud Computing: Optimization Algorithms, methods, and heuristics, unconstrained nonlinear, graph and concave quadratic functions, constrained nonlinear, convex optimization, combinatorial, metaheuristics.

    Sustainable and Green Computing Transformation in edge to cloud continuum: Green energy for sustainable edge-cloud computing and green networking, distributed IoT for the digital and green transformation, sustainable hardware and software for Edge-Cloud, green software engineering and power modeling for for Edge-Cloud, carbon neutrality computation and networking for Edge-Cloud and Real-Time Systems, green network slicing and virtualization, data center sustainability, sustainable energy beyond 5G (B5G) Mobile Networks.

    Formal Verification and Model Checking for Distributed Real-Time CPS and Cloud Computing: Real time System validation, Statistical model checking, Formal Methods and Models for Distributed Real-Time Systems, Formal verification technology of IoT and Real Time Distributed Computing, Reduction and Abstraction Techniques for Model Checking.

    Ontology-based Knowledge Modeling for Real-Time and Distributed IoT and CPS: Knowledge and reasoning framework for decision support for CPS, methodologies and semantics for model-based systems engineering, Ontology-Based Simulation of IoT and Real time CPS, .

    Dependability, Fault tolerance, and Resilience of Distributed Real-Time IoT: Fault Tolerance, Safety, Reliability, autonomic reconfiguration, Autonomic Resilience of Distributed Real time CPS, Availability, Durability, Reliability, and Resilience of Real time CPS and Cloud Computing, .

    Algorithms for real-time analytics: real-time stream processing solutions including clustering, classification, mining and inferencing, machine and deep learning, statistical modeling, Digital Twin Real-Time Predictive Analytics, stream correlation and sampling.

    Distributed management, monitoring, performance evaluation: monitoring mechanisms & infrastructures, performance & clusters monitoring (Kubernetes, Grafana, prometheus, etc.), Distributed Network Monitoring and Management tools and techniques, timing evaluation, dependability, end-to-end QoS, system/infrastructure overheads, fault detection and recovery time, large-scale evaluations and field studies.

    Operating systems, Middleware and System software: real-time kernels, operating systems, virtualization/container mechanisms and distribution middleware for ORC, supporting QoS management and performance, decentralized processing and scalability, extensibility, synchronization, resource allocation, scheduling, energy efficiency, timing analysis, fault tolerance and resilience, security.

    IoT Applications: medical devices, Intelligent Transportation Systems, industrial automation systems and Industry 4.0, Internet of Things and Smart Grids, embedded and cyber-physical systems (automotive, avionics, autonomous vehicles, consumer electronics, building systems, sensors, etc), multimedia processing, RT Web-based Applications, QoS-Aware and real-time Cloud/Edge/Fog Computing, real-time packet processing for future networking infrastructures and Network Function Virtualization (NFV), Network Slicing, Blockchain for Real-Time IoT applications, Distributed Ledger Technology (DLT) for Real-time Log Management, decentralized real-time data network, Digital Twins for IoT Industries, time-sensitive social dispersed computing.