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Language Studies and Comparative Literature including Subject Didactics

Political Science

Algebra and Analysis with Applications

Accounting and Control

Algebra and Analysis with Applications

Artificial Intelligence och Intelligent Systems

Behavioral medicine, health and lifestyle (BeMe-Health)

Biomedical Engineering

Care, Recovery and Health

Certifiable Evidences and Justification Engineering

ChiP - Children’s rights to health, protection, promotion and participation

Complex Real-Time Embedded Systems

Cyber-Physical Systems Analysis

Data Communication

Dependable Software Engineering

Digital and Circular Industrial Services

Digitalisation of Future Energy

EBITech

Engineering Mathematics

Formal Modelling and Analysis of Embedded Systems

Heterogeneous systems - hardware software co-design

Industrial AI Systems

Industrial Software Engineering

Information Design

Innovation Management

Learning and Optimisation

MIND (Mälardalen INteraction and Didactics) research group

Marketing and strategy

Model-Based Engineering of Embedded Systems

Negotiating global challenges within higher education

Neuroengineering

Normcritical perspectives in the research into social vulnerability

Product and Production Development

Programming Languages

Real-Time Systems Design

Renewable Energy

Resource efficiency

Robotics

Safety-Critical Engineering

Software Testing Laboratory

Sustainable lifestyle and health from a public health perspective

Sustainable working life

Transformative Management

Ubiquitous Computing

PSI: Pervasive Self-Optimizing Computing Infrastructures

This project aims to provide a collection of software components that can dynamically optimize the IIoT infrastructure. PSI aims to improve resource use of the system through continuous and distributed system-wide optimizations.

Concluded

Start

2021-01-01

Conclusion

2024-12-31

Research group

Project manager at MDU

No partial template found

The amount of data we produce daily is increasing exponentially thanks to the emergence of new technologies such as the Internet of Things (IoT) and Industrial IoT (IIoT). With such growth, the demands on the computing platforms increase significantly and require new and more efficient solutions for the management of the IoT infrastructure. This requires new solutions to (i) efficiently utilize the entire computing infrastructure, (ii) scale to larger data sets that cannot be moved to data centers for processing, and (iii) meet the predictability and time requirements of IIoT.

PSI (Pervasive Self-Optimizing Computing Infrastructures) aims to provide a collection of software components that can dynamically optimize the IIoT infrastructure. PSI aims to improve resource use of the system through continuous and distributed system-wide optimizations.

The project includes both theoretical and practical aspects, and it combines different research areas such as self-adapting software, control technology, optimization, distributed and real-time systems. The main goal of the project is to develop new methods for efficient use of computing resources while providing guarantees for various important performance indicators, such as response time and computing bandwidth of the system. The project will provide potentially significant progress in both the research community and in industrial applications.