With the emergence of “Industry 4.0”, the integration of cloud technologies and industrial cyber-physical systems (ICPS) becomes increasingly important to boost productivity by simplifying business operations and enhancing collaboration. By associating cloud, infrastructure platform and service applications, ICPS will promote the next generation of intelligent and autonomous systems, as well as increased quality, efficient production and sustainable industrial systems.
Along with the significant benefits, this trend comes with many associated challenges. The ICPS infrastructures and their fusion with the cloud lead to massive amounts of real-time and non-real-time data acquired for controlling particular processes, but also for supporting decision-making at system level. By means of virtualization techniques, IT services are accessed over the Internet, with data being computed in the network but not in a-priori known places. In such context, ensuring timely interaction from data collection to analysis and decision is non-trivial. Moreover, the co-existence of private industry-specific cloud services with public cross-industry cloud services within the same ecosystem entails that some cloud-based data might need to be undisclosed to users outside a particular company or domain. At the same time, private cloud data needs to be combined with data from public clouds, therefore both data security and interoperability need to be ensured. ICPS failures may result in havoc with escalated effects that may cause serious harm to people and property, therefore tackling the safety of cloud-based ICPS ecosystems is a key factor for their application in critical systems. Although cloud- assisted ICPS are increasingly important in many industrial domains, and ensuring their dependability is crucial, existing platforms do not provide satisfactory support to meet the dependability demands of industrial applications.
The overall goal of ACICS is to provide models, methods and tools that facilitate a substantial increase of dependability of cloud-based platforms for ICPS applications, with respect to consistency, security and interoperability of data, timing predictability of using shared virtual resources, together with a framework of guaranteeing QoS enforcement by formal analysis and verification.
Through ACICS, Mälardalen University and three companies, ABB, Volvo GTO, and Ericsson, will develop deep competence to boost the dependability of cloud-based platforms with respect to timing, safety, and data security of ICPS applications. We will be able to drastically enhance the current practices for the design, analysis, and virtual allocation of applications for cloud-based ICPS.
The ACICS team is composed of a strong group of researchers covering all aspects of the synergy, with proven research records, and a group of companies strategically important for Swedish industry.
Predicting Cache Behaviour of Concurrent Applications (Sep 2024) Shamoona Imtiaz, Moris Behnam, Gabriele Capannini, Jan Carlson, Marcus Jägemar 29th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA2024)
Energy-Efficient Motion Planning for Autonomous Vehicles Using UPPAAL Stratego (Jul 2024) Muhammad Naeem, Rong Gu, Cristina Seceleanu, Kim Guldstrand Larsen , Brian Nielsen , Michele Albano The 18th International Symposium on Theoretical Aspects of Software Engineering (TASE2024)
Guess and then Check: Controller Synthesis for Safe and Secure Cyber-Physical Systems (Jul 2024) Rong Gu, Zahra Moezkarimi, Marjan Sirjani 44th International Conference on Formal Techniques for Distributed Objects, Components, and Systems (FORTE 2024)
Modeling and Verification of ROS Systems Using Stochastic Timed Automata (Jun 2024) Peter Backeman, Cristina Seceleanu MRTC Report, Mälardalen Real-Time Research Centre (MRTC 2024)
Synthesizing Understandable Strategies (Nov 2023) Peter Backeman 8th International Conference on Engineering of Computer-based Systems (ECBS2023)
Synergies of Operation, Information, and Communication Technology for Solving New Societal and Industrial Challenges: Future Directions (Oct 2023) Wenbin Dai , Paulo Leitao , Kim Fung Tsang , Yang Shi , Gerhard Hancke , Lei Shu , Moris Behnam, Vyatkin Valeriy
Partner | Type |
---|---|
ABB AB | Industrial |
Ericsson AB | Industrial |
Volvo GTO | Industrial |