Yesterday, Jesse Liauw-A-Fong, a student of the Master of Software Engineering program at UvA, defended his thesis Local Anomaly Detection in Smart Public Transport Vehicles. This research was conducted externally at a company called Ximedes. Jessie’s research is addressing the problem of detecting anomalies, such as a loss of cloud connection, in Smart Public Transport Vehicles (SPTV), such as buses, trams, and metros, comprising many complex heterogeneous systems. It emphasizes the importance of local, context-aware anomaly detection due to the dynamic nature of SPTVs and explores the generalization of anomaly detection, particularly addressing performance, normal region, and quality challenges. The research proposes a unified data collection framework comparing agent-based and agent-less methods, advocating for an agent-based approach for its adaptability and integration ease. It also quantitatively evaluates three local anomaly detection algorithms on real data from a specific bus line. We thank Jessie for his contributions to our research and wish him the best of luck in his future career.
MasCot Program: Bridging Academia and Industry for High-Tech Innovation in Bits & Chips Feature
An article about strategic academic programming at TNO-ESI has appeared in Bits & Chips. The MasCot program, a collaboration co-funded by ESI and the Dutch research council NWO, is designed to tackle the increasing complexity of high-tech equipment. The program addresses the pressing need for advanced engineering methodologies through four projects covering essential topics, such as design space exploration during early system design, scheduling, verification, and restructuring of evolving software. In the article, I explain how the 3-million-euro program facilitates the transition of academic research into practical industrial applications, creating an innovation funnel that spans from academic research through applied research to industrial embedding. The program’s strategic approach not only mitigates the risks associated with high-reward, complex projects but also fosters a symbiotic relationship between academia, industry, and TNO, allowing for a continuous exchange of knowledge, challenges, and innovations.
Master Thesis Shines Light on Hardware Dimensioning for Cyber-Physical Systems
On Wednesday, Marijn Vollaard defended his master thesis “Hardware Dimensioning for Microservice-based Cyber-Physical Systems: A Profiling and Performance Prediction Method” at the University of Amsterdam. This research has been supervised by Ben Pronk and myself as a part of a project with TNO-ESI.
The thesis addresses the problem of determining the number of homogeneous compute nodes needed for a particular variant of a cyber-physical system to meet its timing requirements. This is important in early discussions with customers and bidding processes, since it affects the size and cost of the resulting system. To this end, the thesis proposes a structured hardware dimensioning methodology comprising a profiling method and a performance prediction method. The four novel contributions of the thesis are: 1) A component-based profiling method, 2) a performance prediction method, 3) a structured hardware dimensioning methodology, and 4) validation of the approach, using a case study that represents a prototype of a CPS. Experimental evaluations on the case study show that the predicted performance differs from measurements on the application by at most 20%, which is satisfactory for hardware dimensioning decisions for new product variants.
The defense went well and Marijn confidently presented his story and convincingly answered the questions of the audience. The examination committee, impressed by his work, awarded his thesis a well-deserved grade of 8. As we bid farewell to Marijn, embarking on his next career adventure, we also extend our heartfelt congratulations. He certainly has much to be proud of. We wish him all the best on his travels and in his future pursuits.
