2nd International Workshop on
Testing Distributed Internet of Things Systems

September 27, 2022, in Pacific Grove, California

Co-located with the 10th IEEE International Conference on Cloud Engineering (IC2E 2022)

The 2nd International Workshop on Testing Distributed Internet of Things Systems (TDIS) will again bring together researchers and practitioners who focus on simulations, models, hybrid testbeds, test frameworks, fault injection, monitoring tools, as well as IoT experiments and applications, providing a forum for ongoing work presentations and discussions.

Thank you!

The workshop has been held on September 27th with around 25 participants. We have been impressed by the inspiring invited talks, the interesting paper presentations, and the lively discussions.

We thank the authors and the program committee for the contributions of papers and reviews. Another cordial Thank you! to all participants.

Call for Papers

The Internet of Things (IoT), cloud computing, and machine learning will allow for more adaptive cities, houses, and infrastructures. Yet, this vision of intelligent cyber-physical systems will not be implemented with centralized cloud resources alone. Such resources are simply too far away from sensor-equipped IoT devices, leading to high latencies, bandwidth bottlenecks, and unnecessary energy consumption. Additionally there are often privacy and safety requirements mandating distributed architectures. Therefore, new distributed computing paradigms and system architectures are currently emerging for the IoT that promise to provide computing and storage in proximity of edge devices.

However, the resulting heterogeneous, distributed, and dynamic environments pose significant challenges to the performance, dependability, and efficiency of distributed systems. It is also far less clear how to best create test environments and integrate domain-specific simulations to be able to efficiently assess the behavior IoT systems will exhibit in the field. Yet, continuous testing in realistic test environments is essential for many IoT systems. For instance, IoT systems might be deployed to continuously optimize the operation of critical urban infrastructures, including public transport systems, energy grids, water networks, and medical infrastructures. New versions of such IoT systems must be tested thoroughly before they can be deployed and relied on. Furthermore, the behavior of such IoT systems has to be tested under the expected computing environment conditions, including variations of such conditions, given the inherently unsteady nature of IoT environments.

The TDIS workshop aims to provide a forum for current work by researchers and practitioners in the different research areas and application domains connected to testing IoT systems. We welcome submissions that describe initial ideas and visions just as much as reports on novel approaches, practical tools, and completed projects.

Topics of Interest

Topics of interest include but are not limited to:

  • physical and hybrid IoT testbeds
  • simulation and emulation of IoT environments
  • co-simulation within IoT domains
  • model-based and model-supported approaches
  • simulation-based integration testing
  • testing and benchmarking on heterogeneous IoT devices
  • testing and benchmarking of network technologies and protocols
  • testing and benchmarking of real-time behavior
  • testing and benchmarking of fault tolerance mechanisms (fault injection, chaos engineering, etc.)
  • dependability modeling and assessments (high availability, consistency, etc.)
  • testing and modeling of resource usage and energy consumption
  • resource management and scheduling in testbeds
  • scalability and efficiency of test runs and testbeds
  • testing frameworks for edge and fog computing
  • testbed automation and orchestration
  • distributed monitoring, tracing, and error detection
  • usability of testbeds and testing frameworks
  • representativeness, reproducibility, and repeatability of test results

Important Dates

  • workshop paper submission: June 21 July 19, 2022 (final)
  • notification of acceptance: August 6, 2022
  • camera-ready submission: August 13, 2022 (firm)
  • workshop day: September 27, 2022

Workshop Program

The workshop will be held on September 27, starting from 09:00 PDT, Pacific Grove, California, co-located with IC2E 2022. The program is planned as follows:

  • 09:00 – 10:00 Morning Coffee
  • 10:00 – 10:15 Workshop Opening
  • 10:15 – 11:00 Keynote #1

    • AI workloads at Meta and their Implication on System Design. Dr. Ehsan K. Ardestani, Meta

      Abstract: AI services are widespread across many services at Meta. Organic demand for these workloads continues to grow, in addition to scaling of the workload complexity in terms of compute, data, memory, and communication requirements. This separates the design of AI platforms from traditional compute platform, in that the scaling of the complexity outpaces the rate at which the underlying compute, memory, and networking technology improves generation over generation, requiring end to end codesign and optimization of the HW and SW. This talk overviews some of the most relevant AI workloads at Meta, their compute requirements, and how it impacts the design of the underlying system.

      Speaker: Ehsan K. Ardestani is a Technical Lead Manager at Meta working on codesign of AI platforms. Ehsan has been working in the industry on architecture of several generations of General purpose and Application specific Processors, with more recent focus on computing Systems, for about a decade.

  • 11:00 – 12:00 Paper Session #1
    • Network Emulation in Large-Scale Virtual Edge Testbeds: A Note of Caution and the Way Forward. Sören Becker (Technische Universität Berlin), Tobias Pfandzelter, Nils Japke, David Bermbach (Technische Universität Berlin & Einstein Center Digital Future), and Odej Kao (Technische Universität Berlin)
    • IoTreeplay: Synchronous Distributed Traffic Replay in IoT Environments. Markus Toll, Ilja Behnke, and Odej Kao (Technische Universität Berlin)
    • Towards Energy Consumption and Carbon Footprint Testing for AI-driven IoT Services. Demetris Trihinas (University of Nicosia), Lauritz Thamsen (University of Glasgow), Jossekin Beilharz (Hasso Plattner Institute, University of Potsdam), and Moysis Symeonides (University of Cyprus)
  • 12:00 – 13:00 Lunch
  • 13:00 – 13:45 Keynote #2 (remote)

    • Experiences with cloud-based distributed training and edge support for mobile AR. Dr. Tian Guo, Worcester Polytechnic Institute

      Abstract: Deep learning (DL) has been utilized in many user-facing applications, such as augmented reality (AR). Training DL models often require access to multiple GPUs, which can be expensive to set up on-premises. In this talk, I will describe our recent work in speeding up cloud-based DL training by utilizing cheap transient servers and devising policies to manage training sessions effectively. Despite the advancement in VM-based distributed training, it can still be daunting for DL practitioners to select the proper amount of resources and configure the training cluster. To alleviate the management complexity, I will talk about a recent work for fast and cost-effective serverless-based DL training. Lastly, I will end with a use case where we leverage an edge-based DL model to support mobile AR and challenges in conducting controlled experiments.

      Speaker: Dr. Tian Guo is an Assistant Professor of Computer Science at Worcester Polytechnic Institute (WPI). She earned her Ph.D. degree from the University of Massachusetts Amherst. Her research interests include designing systems mechanisms and policies to handle trade-offs in cost, performance, and efficiency for emerging applications. Specifically, she has worked on projects at the intersection of systems and machine learning, secure machine learning, cloud/edge resource management, big data frameworks, deep learning inference, distributed training, neural architecture search, and AR/VR. Her recent work focuses on improving system support for deep learning and on the practical applications of deep learning in AR/VR. She is the recipient of the National Science Foundation CRII award, the MMSys 2020 best paper award, and the 2022 award for Outstanding Achievement by a Young Alum from The Manning College of Information and Computer Sciences, UMass Amherst.

  • 13:45 – 14:25 Paper Session #2
    • An End-to-End Framework for Benchmarking Edge-Cloud Cluster Management Techniques. Philipp Raith, Thomas Rausch, Paul Prüller, Alireza Furutanpey, and Schahram Dustdar (Vienna University of Technology)
    • Integration of C-V2X Into a Hybrid Testbed to Co-Simulate ITS Applications and Scenarios. Paul Geppert and Jossekin Beilharz (Hasso Plattner Institute, University of Potsdam)
  • 14:25 – 14:30 Closing Remarks
  • 14:30 – 15:00 Afternoon Coffee

Workshop Organizers

Workshop Chairs

Publicity Chairs

  • Ilja Behnke, Technische Universität Berlin, Germany
  • Lukas Pirl, Hasso Plattner Institute, University of Potsdam, Germany
  • Philipp Wiesner, Technische Universität Berlin, Germany

Program Committee

  • Fotis Nikolaidis, ICS-FORTH, Greece
  • Shashikant Ilager, Technische Universität Wien, Austria
  • Miguel Matos, Universidade de Lisboa, Portugal
  • Steffen Zeuch, German Research Center for Artificial Intelligence (DFKI), Germany
  • Vasileios Karakostas, University of Athens, Greece
  • Lito Michala, University of Glasgow, United Kingdom
  • Ang Li, Duke University, USA
  • Peter Tröger, Beuth University of Applied Sciences Berlin, Germany
  • Thomas Rausch, Vienna University of Technology, Austria
  • Moysis Symeonides, University of Cyprus, Cyprus
  • Eyhab Al-Masri, University of Washington Tacoma, USA
  • Eleni Tzirita Zacharatou, IT University of Copenhagen, Denmark
  • Dragi Kimovski, Alpen-Adria Universität Klagenfurt, Austria

Previous Workshop Editions

  • Our 1st workshop edition, TDIS 2021, was held online with IEEE IC2E 2021, a program of eight talks, and up to 33 participants.