Objective

The ACM International Conference on Distributed and Event‐Based Systems (DEBS) is the premier venue for academia and industry to discuss cutting-edge research in distributed and event-based computing and data processing. DEBS 2026 will provide a forum for original research, practical insights, and experiences in distributed and event-based systems, with a focus on emerging trends and new challenges in the field.

We solicit high-quality submissions across a range of topics, with different submission options to reflect the nature of each contribution. All submissions will undergo a rigorous peer review process.

Scope

The DEBS conference covers a broad range of topics in distributed and event-based computing for various application domains and computing environments. The conference aims to present novel solutions for collecting, detecting, processing, analyzing, and responding to events through distributed middleware, systems, and platforms. DEBS 2026 welcomes submissions focusing on 1) Models, Architectures, Programming, and Query Support, 2) Systems and Software, and 3) Applications and Use-Cases on the following topics:

Systems Design and Data Management

Scalable data stream processing and complex event processing.
Dataflow execution and distributed state management.
Time series event-based database management.
Approximate event-based query processing.
Incremental computing, data structures, and materialized view maintenance for relational, graph, and stream data.
Cloud, fog, and edge computing, including serverless and FaaS.
Hardware acceleration and programmable hardware for event-based systems.
Software-defined networking and disaggregated memory architectures for event-based systems.

Security and Privacy

Security, encryption, forecasting, and in-network processing for data streams.
Sustainability, security, reliability, and resilience in event-based systems.
Scalable distributed ledger and blockchain..

AI/ML for Systems and Systems for AI/ML

Event-based systems for ML: optimizing end-to-end AI/ML pipelines using event-based systems, i.e., feature engineering, distributed training, and serving.
ML for event-based systems: improving performance using AI/ML methods.

Applications, Use-Cases and Benchmarks

Applications and use cases regarding Internet-of-Things (IoT), smart cities, virtual and extended/augmented reality, cyber-physical systems, and sensor networks.
Applications and use cases regarding enterprise, finance, healthcare, life sciences, logistics, fleet management, transport scheduling and optimization, multimedia analytics, computer/network security, and social networking.
Benchmarks for event-based systems