| 1. |
- Crnkovic, Ivica, et al.
(författare)
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Classification and Survey of Component Models
- 2010
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Konferensbidrag (refereegranskat)abstract
- As component-based software engineering is growing and its usage expanding, more and more component models are developed. In this paper we present a survey of software component models in which models are described and classified respecting the classification framework for component models proposed by Crnković et. al. This framework specifies several groups of important principles and characteristics of component models: lifecycle, constructs, specification and management of extra-functional properties, and application domain. This paper gives examples three component models using the classification framework.
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| 2. |
- Gürdür, Didem, 1983-, et al.
(författare)
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Knowledge Representation of Cyber-physical Systems for Monitoring Purpose
- 2018
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Ingår i: 51st CIRP Conference on Manufacturing Systems. - : Elsevier. ; , s. 468-473
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Konferensbidrag (refereegranskat)abstract
- Automated warehouses, as a form of cyber-physical systems (CPSs), require several components to work collaboratively to address the common business objectives of complex logistics systems. During the collaborative operations, a number of key performance indicators (KPI) can be monitored to understand the proficiency of the warehouse and control the operations and decisions. It is possible to drive and monitor these KPIs by looking at both the state of the warehouse components and the operations carried out by them. Therefore, it is necessary to represent this knowledge in an explicit and formally-specified data model and provide automated methods to derive the KPIs from the representation. In this paper, we implement a minimalistic data model for a subset of warehouse resources using linked data in order to monitor a few KPIs, namely sustainability, safety and performance. The applicability of the approach and the data model is illustrated through a use case. We demonstrate that it is possible to develop minimalistic data models through Open Services for Lifecycle Collaboration (OSLC) resource shapes which enables compatibility with the declarative and procedural knowledge of automated warehouse agents specified in Planning Domain Definition Language (PDDL).
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| 3. |
- Jörgensen, Nils, et al.
(författare)
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RoboPlan5G : Coordinating Cloud-Controlled Mobile Robots with 5G Network Configuration
- 2023
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Ingår i: 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation, ETFA 2023. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- With the emergence of Industry 4.0, comes an increasing need for multi-robot coordination and communication to efficiently complete joint tasks. A critical technology is the fifth generation (5G) mobile network, which enables cloud-controlled robots to execute tasks with differentiated quality-of-service (QoS) features. While there has been significant research on multi-robot planning, the integration with the capabilities of realistic network systems has been limited. In this paper, we introduce RoboPlan5G, a framework for 5G-aware robot planning. We propose a joint state-search model that includes task planning coordination in conjunction with 5G physical resource block (PRB) allocation. This process ensures efficient usage of the limited indoor 5G spectrum and effective service performance, while still aiming for the completion of tasks in the shortest possible time frame. Scenarios are generated in an Industry 4.0 environment, where the planner is shown to decrease the required 5G spectrum allocation by 50%, and on average improve the plan quality by 45% while maintaining a small computation time.
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| 4. |
- Larsson Forsberg, Albin, et al.
(författare)
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Network Parameter Control in Cellular Networks through Graph-basedMulti-agent Constrained Reinforcement Learning
- 2023
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Ingår i: 2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- Cellular networks are growing in complexity at increasing speed and the geographical locations in which they are deployed in are getting denser. Traditional control methods fall short in providing a scalable and dynamic way of adapting the network to new conditions. Distributed multi-agent reinforcement learning successfully addresses scalability problems seen in centralized approaches. The question of achieving learning with constraint satisfaction in distributed systems is still left unanswered in the state-of-the-art. In this work, we aim to perform distributed multi-agent constrained reinforcement learning in order to learn a policy online while satisfying imposed constraints. We use a coordination graph to model the interactions between agents and decompose the global value function.A conservative safety critic is trained in parallel to evaluate the safety of proposed actions. Our method allows for separate training of both the critic and the value network independently of each other, and hence offers flexibility in how and when to train the different models. The results are compared to a baseline using no safety critic. Simulations show that the agents succeed in learning a policy that can satisfy the constraints, while still maximizing the objective.
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| 5. |
- Mubeen, Saad, et al.
(författare)
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A Perspective on Ensuring Predictability in Time-critical and Secure Cooperative Cyber Physical Systems
- 2019
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Ingår i: 2019 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT). - : IEEE. - 9781538663769 ; , s. 1379-1384
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Konferensbidrag (refereegranskat)abstract
- Recent advancement in the development of embedded systems and in the integration of operational and industrial technologies has accelerated the progress of cyber-physical systems (CPSs) development. Cooperation of such systems allows to achieve new functionalities. However, often these systems are time-critical; hence, the developers of these systems are required to provide guarantees of the systems' properties, such as predictability and security. In this paper, we start by glancing through the research devoted to developing time predictable and secure embedded systems. Thereon, we extend the discussion to time-critical and secure CPSs and point out the challenges related to ensuring predictability during their development. In this context, we emphasize the importance of security as a prerequisite for time predictability. Moreover, we identify the gaps in the state of the art and describe our view on ensuring predictability in time-critical and secure CPSs.
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| 6. |
- Mubeen, Saad, et al.
(författare)
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Timing Predictability and Security in Safety-Critical Industrial Cyber-Physical Systems : A Position Paper
- 2020
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Ingår i: Applied Sciences. - : MDPI. - 2076-3417. ; 10:9
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Tidskriftsartikel (refereegranskat)abstract
- Cyber Physical Systems (CPSs) are systems that are developed by seamlessly integrating computational algorithms and physical components, and they are a result of the technological advancement in the embedded systems and distributed systems domains, as well as the availability of sophisticated networking technology. Many industrial CPSs are subject to timing predictability, security and functional safety requirements, due to which the developers of these systems are required to verify these requirements during the their development. This position paper starts by exploring the state of the art with respect to developing timing predictable and secure embedded systems. Thereafter, the paper extends the discussion to time-critical and secure CPSs and highlights the key issues that are faced when verifying the timing predictability requirements during the development of these systems. In this context, the paper takes the position to advocate paramount importance of security as a prerequisite for timing predictability, as well as both security and timing predictability as prerequisites for functional safety. Moreover, the paper identifies the gaps in the existing frameworks and techniques for the development of time- and safety-critical CPSs and describes our viewpoint on ensuring timing predictability and security in these systems. Finally, the paper emphasises the opportunities that artificial intelligence can provide in the development of these systems.
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| 7. |
- Nayyar, Raghu, et al.
(författare)
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Visualizing Autonomous Warehouse Data Streams Through User-Centered Design
- 2019
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Ingår i: Proceedings of The Fifth International Conference on Big Data, Small Data, Linked Data and Open DataALLDATA 2019.
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Konferensbidrag (refereegranskat)abstract
- This paper summarizes the work is done, which is carried out to develop and evaluate a dashboard design that visualizes a stream of data from different entities involved in autonomous warehouses, as a subset of cyber-physical systems. The dashboard is designed and developed through User- Centered Design (UCD) methodologies based on two iterations of feedback sessions with the stakeholders. During these sessions, semi-structured expert opinion interviews are conducted. The paper discusses the different stages involved in building the proposed dashboard design, the design decisions, the technical aspects of the libraries used, and the results of the feedback sessions towards the end of the project. It also presents the implemented dashboard as proof of development efforts and explains its different functionalities. The study concludes by evaluating the dashboard through the semi-structured interviews with the respective stakeholders and suggests features for further development.
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| 8. |
- Vulgarakis Feljan, Aneta, et al.
(författare)
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A Framework for Knowledge Management and Automated Reasoning Applied on Intelligent Transport Systems
- 2017
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Rapport (populärvet., debatt m.m.)abstract
- Cyber-Physical Systems in general, and Intelligent Transport Systems (ITS) in particular use heterogeneous data sources combined with problem solving expertise in order to make critical decisions that may lead to some form of actions e.g., driver notifications, change of traffic light signals and braking to prevent an accident. Currently, a major part of the decision process is done by human domain experts, which is time-consuming, tedious and error-prone. Additionally, due to the intrinsic nature of knowledge possession this decision process cannot be easily replicated or reused. Therefore, there is a need for automating the reasoning processes by providing computational systems a formal representation of the domain knowledge and a set of methods to process that knowledge. In this paper, we propose a knowledge model that can be used to express both declarative knowledge about the systems’ components, their relations and their current state, as well as procedural knowledge representing possible system behavior. In addition, we introduce a framework for knowledge management and automated reasoning (KMARF). The idea behind KMARF is to automatically select an appropriate problem solver based on formalized reasoning expertise in the knowledge base, and convert a problem definition to the corresponding format. This approach automates reasoning, thus reducing operational costs, and enables reusability of knowledge and methods across different domains. We illustrate the approach on a transportation planning use case.
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