Objectives
PRG1467 "CRASHLESS - Cross-Layer Reliability and Self-Health Awareness for Intelligent Autonomous Systems " (01.01.2022−31.12.2026); Principal Investigator: Maksim Jenihhin; Tallinn University of Technology, School of Information Technologies, Department of Computer Systems; Financier: Estonian Research Council
CRASHLESS aims at radically new cross-layer reliability and self-health awareness technology for tomorrow's intelligent autonomous systems and IoT edge devices in Estonia and EU. The enormous complexity of today's advanced cyber-physical systems and systems of systems is multiplied by their heterogeneity and the emerging computing architectures employing AI-based autonomy. The setups, such as autonomous swarms of robotic vehicles, are already on the doorstep and call for novel approaches for reliability across all the layers. Continuous self-health awareness and infrastructure for in-field self-healing are becoming an enabling factor for new IoT edge devices and systems on the way to market. The new deep-tech by CRASHLESS equips engineers with design-phase solutions and in-field instruments for industry-scale systems and, ultimately, facilitates the user experience of the system’s crashless operation. The results are to be validated in close collaboration with Estonian companies.
Objective 1.
To develop radically new cross-layer reliability management and a self-health awareness technology for the intelligent autonomous systems practically applicable by Estonian and EU industry in the short-term and mid-term future. The CRASHLESS technology is aimed to tackle the challenge by both:
a) design-phase cross-layer reliability enhancement
b) in-field intelligent fault resilience for industry-scale systems.
Objective 2.
To establish a new sustainable research group for strengthening the national competence in cross-layer reliability and self-health awareness in intelligent autonomous systems and IoT edge devices. The group will be a base for consultancy and collaboration for Estonian technological companies and also governmental authorities. In particular, the project aims at establishing an accessible Knowledge Pool and cross-sectoral MSc and PhD training.
Supervised dissertations
Mahdi Taheri - Methods for Reliability Assessment and Enhancement of Deep Neural Network Hardware Accelerators
Supervisor: Maksim Jenihhin; Masoud Daneshtalab Defended: 2025
Ahmet Cagri Bagbaba - Methods to Optimize Functional Safety Assessment for Automotive Integrated Circuits
Supervsor: Maksim Jenihhin; CHRISTIAN SAUER Defended: 2022
Aneesh Balakrishnan - A Synthetic, Hierarchical Approach for Modelling and Managing Complex Systems' Quality and Reliability
Supervsor: Maksim Jenihhin; Dan Alexandrescu Defended: 2022
Xinhui Lai - Approaches to Extra-Functional Verification of Security and Reliability Aspects in Hardware Designs
Supervsor: Maksim Jenihhin; Jaan Raik Defended: 2022
Supervision of postdoctoral researchers
The work of the postdocs contributed to the CRASHLESS concepts.
01.08.2021−31.08.2023
Foisal AHMED "Cross-layer reliability of UAV computing platforms"
Prime University, Bangladesh
01.11.2020−31.10.2022
Dadmehr Rahbari "Optimization of Collaborative Computing for MEC in Dynamic Networks"
University of Qom, Qom, Iran
Dissertations under supervision
Natalia Cherezova - Cross-Layer Reliability and Self-Health Awareness for Intelligent Autonomous Systems
Supervisor: Maksim Jenihhin; Artur Jutman
Rama Mounika Kodamanchili - Pre-silicon validation of AI chips
Supervisor: Maksim Jenihhin
Ahsan Rafiq - Hardware Inference Engines for EDGE AI
Supervisor: Maksim Jenihhin
Publications
coming soon