Month: July 2023

Call for Papers and Experts – 30th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2024) in Hong Kong

Posted on by bennyakesson

I have the honor of being the Program Chair of the 30th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2024), located in Hong Kong May 13-16 next year. Please see the Call for Papers below.

Soon, it will be time to put together the Technical Program Committee (TPC) that will review and select the papers that will appear in the conference program. If you are interested in joining the TPC of this conference, or any other conference (co-)sponsored by the Technical Community of Real-Time Systems (TCRTS), please fill out the TPC self-nomination form as soon as possible. We always welcome self-nominations from our own community, but this year we especially encourage self-nominations from the academic performance engineering community, as well as members of the industry that work with real-time requirements or performance engineering, defined in a broad sense.

If you have any questions, please feel to reach out to me. If want to self-nominate, click this link. A self-nomination is not a firm commitment, it is just a declaration of interest that may result in an invitation.

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30th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS 2024)

Hong Kong, May 13-16, 2024

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CALL FOR PAPERS

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RTAS is a top-tier conference with a focus on time-sensitive systems. RTAS’24 invites papers describing case studies, applications, methodologies, and algorithms that contribute to the state of practice in design, implementation, verification, validation, and evolution of time-sensitive systems. RTAS’24 consists of two tracks:

  • Track 1. Systems and Applications;
  • Track 2. Applied Methodologies and Foundations.

In both tracks, papers must consider some kind of timing requirements. The timing requirements of interest are broadly defined and include not only classical hard real-time constraints, but also soft real-time, probabilistic, quality-of-service (QoS), throughput or latency requirements. The application area can be any type of time-sensitive systems, ranging from resource-constrained embedded systems to cyber-physical systems (CPS), cloud/edge/fog computing systems, cloud data centers, Internet of Things (IoT), mobile computing, robotics,  smart grid, and smart cities, as well as middleware and frameworks, machine learning in or for time-sensitive systems and signal processing algorithms that execute in real time. RTAS welcomes both papers backed by formal proofs, as well as papers that focus exclusively on empirical validation of timing requirements, e.g., using traces or performance models inferred from operational data. Research results from fundamental research, (case-driven) applied research, and (pragmatic) industry practice are all in scope.

RTAS’24 follows a double-anonymous peer reviewing process: author identities and affiliations will not be revealed to reviewers. Authors will have the opportunity to provide a response to reviews before acceptance decisions are made, solely to provide clarifications and correct misconceptions. The response will not allow authors to introduce new material beyond the original submission, or promise such material for the camera-ready version. There will be an optional evaluation process for accepted papers that assesses the reproducibility of the work.

Track 1: Systems and Applications

This track focuses on research of an empirical nature pertaining to (system- or component-) level analysis, optimization, and verification, as well as applications, runtime software, and hardware architectures for time-sensitive systems.

Topics relevant to this track include, but are not limited to:

  • time-sensitive applications
  • real-time and embedded operating systems,
  • hypervisors and runtime frameworks,
  • hardware architectures, memory hierarchies, FPGAs, GPUs and accelerators,
  • time-sensitive networks, CPS/IoT infrastructure,
  • microservice technologies, cloud and edge computing, real-time artificial intelligence and machine learning,
  • application profiling, WCET analysis, compilers, tools, benchmarks and case studies.

Papers discussing design and implementation experiences on real industrial systems are especially encouraged. Papers submitted to this track should focus on specific systems and implementations. Authors must include a section with experimental results performed on a real implementation, or demonstrate applicability to an industrial case study or working system. The experiment or case study discussions must highlight the key lessons learned. Simulation-based results are acceptable for architectural simulation, or other cases where authors clearly motivate why it is not feasible to develop and evaluate a real system.

Empirical survey-based research focused on the real-time systems field is also welcome in this track. This type of research uses surveys, questionnaires, interviews, use cases or other empirical techniques to obtain information about the past / current / future state of play in the research, design, development, verification, validation, and deployment of time-sensitive systems.

Track 2: Applied Methodologies and Foundations

This track focuses on fundamental models, and analysis techniques/methods that are applicable to time-sensitive systems to solve specific problems. The track welcomes knowledge-based models, models built from operational data, as well as a combination, and different types of analysis methods, including analytical, statistical, or probabilistic methods. Topics relevant to this track include, but are not limited to:

  • modelling languages, modelling methods, model learning, model validation and calibration,
  • scheduling and resource allocation,
  • system-level optimization and co-design techniques,
  • design space exploration,
  • verification and validation methodologies.

Papers must describe the main context or use case for the proposed methods giving clear motivating examples based on real systems. The system models and any assumptions used in the derivation of the methods must be applicable to real systems, and reflect actual needs. Papers must include a section on experimental results, preferably including a case study based on information from a real system. The use of synthetic workloads and models is acceptable if appropriately motivated and used to provide a systematic evaluation.

Important Dates

Submission Deadline (firm): October 31, 2023
Author Response Period: January 8-12, 2024
Author Notification: January 19, 2024
Conference Date: May 13-16, 2024

 

Bridging the Gap: Rethinking Real-Time Systems for Industry Success and Model-Driven Performance Engineering

Posted on by bennyakesson

The real-time systems community is shrinking and needs to bridge the gap between academic research an industry practice. In my pitch at ECRTS, I shared our view on model-driven system performance engineering for cyber-physical systems and encouraged the community increase its scope and take a broader responsibility for timing-related issues in systems to achieve those goals. This means working in more of the focus areas that we have identified in our vision and validated with our industry partners, but also reconsidering some directions in areas where work is already taking place. This means less focus on hard real-time requirements and formal methods and more focus on:

• system-level KPIs instead of meeting deadlines in subsystems
• soft real-time requirements
• timing requirements beyond software
• system performance modelling, model calibration, and model learning
• data-driven performance analysis, optimization, verification, and diagnostics, e.g. using traces

I encouraged the community to have a look at our vision for model-based system performance engineering for industrial cyber-physical systems and asked to think about how they could contribute through their current and future work.

Please have a look at our vision here.

Thanks to Bram van der Sanden, Kuan-Hsun Chen, Mitra Nasri, Geoffrey Nelissen, and Twan Basten for their help preparing the pitch.

Scaling the Future: Master Thesis Defense on Scalability in Simulation Environments for Distributed Cyber-Physical Systems

Posted on by bennyakesson

Today, we celebrate that Herman Kelder successfully defended his master thesis “Scalability in System-Level Simulation Environments for Distributed Cyber-Physical Systems“. This work was carried out in the context of the DSE2.0 project, where we address the complex scientific challenges involved in performing design-space exploration (DSE) for complex distributed cyber-physical systems (dCPS), such as lithography machines. Three key challenges in this context are: 1) automatically modelling the application and platform based on data from the running system, 2) scalable search and pruning algorithms that help navigate large design spaces efficiently, and 3) scalable simulation environments that allow many design points to be efficiently evaluated concurrently.

Herman’s thesis addresses the last of these three challenges. To facilitate scalable and efficient DSE for dCPS, an evaluation environment is proposed, implemented, and evaluated. The research considers key design considerations for developing a distributed evaluation workflow that can dynamically be adapted to enable efficient and scalable exploration of the vast design space of complex, distributed cyber-physical systems. Evaluation of the proposed environment employs a set of system models, representing design points within a DSE process, to assess the solution and its behavior, performance, capability, and applicability in addressing the scalability challenge in the context of DSE for dCPS. During the evaluation, the performance and behavior are investigated in three areas: (i) Simulation Campaign, (ii) Task Management Configuration, and (iii) Parallel Discrete-Event Simulation (PDES). Throughout the evaluation, it is demonstrated that the proposed environment is capable of providing scalable and efficient evaluation of design points in the context of DSE for dCPS. Furthermore, the proposed solution enables designers and researchers to tailor it to their environment through dynamic complex workflows and interactions, workload-level and task-level parallelism, and simulator and compute environment agnosticism.

Herman executed his project meticulously and delivered excellent research results, both in terms of concepts and implementation. Thank you very much for your contributions Herman and we hope to work with you again at some point.

Keynote Address Explores Performance Engineering in Cloud-Connected Cyber-Physical Systems

Posted on by bennyakesson

I had the honor of being invited as keynote speaker at RT-Cloud 2023. The keynote discussed the increasing complexity of cyber-physical systems (CPS) in the Dutch high-tech systems industry and a gradual transition towards microservice architectures and cloud-connected systems. This transition challenges our experience with performance engineering in the CPS domain, as we adapt our methods to embrace new tools and technologies. To make the presentation concrete, I discussed two projects that I am currently working on, a project on performance verification of microservice architectures together with Thales, and a project about performance engineering and service continuity in the compute continuum, together with Philips and TU/e and other TRANSACT partners. I would like to thank Johan Eker and Luca Abeni for the invitation and all participants for their attention and questions.