| 1. |
- Ghaderi, Adnan, et al.
(författare)
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Design challenges in hardware development of time-sensitive networking : A research plan
- 2019
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Ingår i: CEUR Workshop Proceedings, Volume 2457. - : CEUR-WS.
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Konferensbidrag (refereegranskat)abstract
- Time-Sensitive Networking (TSN) is a set of ongoing projects within the IEEE standardization to guarantee timeliness and low-latency communication based on switched Ethernet for industrial applications. The huge demand is mainly coming from industries where intensive data transmission is required, such as in the modern vehicles where cameras, lidars and high-bandwidth modern sensors are connected. The TSN standards are evolving over time, hence the hardware needs to change depending upon the modifications. In addition, high performance hardware is required to obtain a full benefit from the standards. In this paper, we present a research plan for developing novel techniques to support a parameterized and modular hardware IP core of the multi-stage TSN switch fabric in VHSIC (Very High Speed Integrated Circuit) Hardware Description Language (VHDL), which can be deployed in any Field-Programmable-Gate-Array (FPGA) devices. We present the challenges on the way towards the mentioned goal.
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| 2. |
- Abdi, Somayeh, et al.
(författare)
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Cognitive and Time Predictable Task Scheduling in Edge-cloud Federation
- 2022
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Ingår i: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665499965
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Konferensbidrag (refereegranskat)abstract
- In this paper, we present a hierarchical model for time predictable task scheduling in edge-cloud computing architecture for industrial cyber-physical systems. Regarding the scheduling problem, we also investigate the common problem-solving approaches and discuss our preliminary plan to realize the proposed architecture. Furthermore, an Integer linear programming (ILP) model is proposed for task scheduling problem in the cloud layer. The model considers timing and security requirements of applications and the objective is to minimize the financial cost of their execution.
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| 3. |
- Abdi, Somayeh, et al.
(författare)
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Task Offloading in Edge-cloud Computing using a Q-Learning Algorithm
- 2024
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Ingår i: International Conference on Cloud Computing and Services Science, CLOSER - Proceedings. - : Science and Technology Publications, Lda. - 9789897587016 ; , s. 159-166
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Task offloading is a prominent problem in edge−cloud computing, as it aims to utilize the limited capacityof fog servers and cloud resources to satisfy the QoS requirements of tasks, such as meeting their deadlines.This paper formulates the task offloading problem as a nonlinear mathematical programming model to maximizethe number of independent IoT tasks that meet their deadlines and to minimize the deadline violationtime of tasks that cannot meet their deadlines. This paper proposes two Q-learning algorithms to solve theformulated problem. The performance of the proposed algorithms is experimentally evaluated with respect toseveral algorithms. The evaluation results demonstrate that the proposed Q-learning algorithms perform wellin meeting task deadlines and reducing the total deadline violation time.
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| 4. |
- Afshar, Sara Zargari, et al.
(författare)
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Investigating Alternatives for System Architectures to Enhance Discrete Manufacturing
- 2019
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Ingår i: International Journal of Distributed Sensor Networks. - Sweden : SAGE Publications. - 1550-1329 .- 1550-1477. ; 15:8
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Tidskriftsartikel (refereegranskat)abstract
- This article investigates the possibility of advancing discrete manufacturing using system architectures that are developed for Collaborative Process Automation Systems. Collaborative Process Automation System is a technology that has the potential to achieve production excellence for process industry. However, not much attention has been paid on using the architectures based on Collaborative Process Automation Systems for discrete manufacturing domains. In this article, we propose a base architecture consisting of three layers, and we discuss various alternatives to make the communications among the layers. We consider legacy components in the proposal, in contrast to most of the related works. In order to show the practicality of the proposed alternatives, we present an example that has been implemented in an ongoing project at ABB Robotics in Sweden.
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| 5. |
- Agerskans, Natalie, et al.
(författare)
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Critical Factors for Selecting and Integrating Digital Technologies to Enable Smart Production : A Data Value Chain Perspective
- 2023
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Ingår i: IFIP Advances in Information and Communication Technology. - : Springer Science and Business Media Deutschland GmbH. - 9783031436611 ; , s. 311-325
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Konferensbidrag (refereegranskat)abstract
- With the development towards Industry 5.0, manufacturing companies are developing towards Smart Production, i.e., using data as a resource to interconnect the elements in the production system to learn and adapt accordingly for a more resource-efficient and sustainable production. This requires selecting and integrating digital technologies for the entire data lifecycle, also referred to as the data value chain. However, manufacturing companies are facing many challenges related to building data value chains to achieve the desired benefits of Smart Production. Therefore, the purpose of this paper is to identify and analyze the critical factors of selecting and integrating digital technologies for efficiently benefiting data value chains for Smart Production. This paper employed a qualitative-based multiple case study design involving manufacturing companies within different industries and of different sizes. The paper also analyses two Smart Production cases in detail by mapping the data flow using a technology selection and integration framework to propose solutions to the existing challenges. By analyzing the two in-depth studies and additionally two reference cases, 13 themes of critical factors for selecting and integrating digital technologies were identified.
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| 6. |
- Agerskans, Natalie
(författare)
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Digital Technologies for Enabling Smart Production : Examining the Aspects of Selection and Integration
- 2023
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- With the development towards Industry 5.0, manufacturing companies are developing towards smart production. In smart production, data is used as a resource to interconnect different elements in the production system to learn and adapt to changing production conditions. Common objectives include human-centricity, resource-efficiency, and sustainable production. To enable these desired benefits of smart production, there is a need to use digital technologies to create and manage the entire flow of data. To enable smart production, it is essential to deploy digital technologies in a way so that collected raw data is converted into useful data that can be applied by equipment or humans to generate value or reduce waste in production. This requires consideration to the data flow within the production system, i.e., the entire process of converting raw data into useful data which includes data management aspects such as the collection, analysis, and visualization of data. To enable a good data flow, there is a need to combine several digital technologies. However, many manufacturing companies are facing challenges when selecting suitable digital technologies for their specific production system. Common challenges are related to the overwhelming number of advanced digital technologies available on the market, and the complexity of production system and digital technologies. This makes it a complex task to understand what digital technologies to select and the recourses and actions needed to integrate them in the production system.Against this background, the purpose of this licentiate thesis is to examine the selection and integration of digital technologies to enable smart production within manufacturing companies. More specifically, this licentiate thesis examines the challenges and critical factors of selecting and integrating digital technologies for smart production. This was accomplished by performing a qualitative-based multiple case study involving manufacturing companies within different industries and of different sizes. The findings show that identified challenges and critical factors are related to the different phases of the data value chain: data sources and collection, data communication, data processing and storage, and data visualisation and usage. General challenges and critical factors that were related to all phases of the data value chain were also identified. Moreover, the challenges and critical factors were related to people, process, and technology aspects. This shows that there is a need for holistic perspective on the entire data value chain and different production system elements when digital technologies are selected and integrated. Furthermore, there is a need to define a structured process for the selection and integration of digital technologies, where both management and operational level are involved.
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| 7. |
- Agerskans, Natalie, et al.
(författare)
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Enabling Smart Production : The Role of Data Value Chain
- 2022
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Ingår i: Advances in Production Management Systems. Smart Manufacturing and Logistics Systems: Turning Ideas into Action. - Cham : Springer Science and Business Media Deutschland GmbH. - 9783031164101 ; , s. 477-485
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Konferensbidrag (refereegranskat)abstract
- To stay competitive, manufacturing companies are developing towards Smart Production which requires the use of digital technologies. However, there is a lack of guidance supporting manufacturing companies in selecting and integrating a combination of suitable digital technologies, which is required for Smart Production. To address this gap, the purpose of this paper is twofold: (i) to identify the main challenges of selecting and integrating digital technologies for Smart Production, and (ii) to propose a holistic concept to support manufacturing companies in mitigating identified challenges in order to select and integrate a combination of digital technologies for Smart Production. This is accomplished by using a qualitative-based multiple case study design. This paper identifies current challenges related to selection and integration of digital technologies. To overcome these challenges and achieve Smart production, the concept of data value chain was proposed, i.e., a holistic approach to systematically map and improve data flows within the production system. © 2022, IFIP International Federation for Information Processing.
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| 8. |
- Aglianò, Simone, et al.
(författare)
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Resource Management and Control in Virtualized SDN Networks
- 2018
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Ingår i: CSI International Symposium on Real-Time and Embedded Systems and Technologies REST'18. - 9781538614754 ; , s. 47-53
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Konferensbidrag (refereegranskat)abstract
- Software defined networking and network virtual-ization are widely considered promising techniques for reducing the complexity of network management in many contexts that require high Quality of Service (QoS) and the support for heterogeneous architectures. In this paper we address a network architecture, here called a virtualized SDN network, that combines the benefits of SDN and virtualization. To cope with the demand for efficiently sharing a platform among several services, here a resource management mechanism to reserve and control network resources among various services in the virtualized SDN networks is proposed. The mechanism is implemented on an SDN controller and a set of experiments show the effectiveness of the proposed approach.
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| 9. |
- Al-Dulaimy, Auday, et al.
(författare)
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Fault Tolerance in Cloud Manufacturing : An Overview
- 2023
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Ingår i: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST. - : Springer Science and Business Media Deutschland GmbH. - 9783031318900 ; , s. 89-101
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Konferensbidrag (refereegranskat)abstract
- Utilizing edge and cloud computing to empower the profitability of manufacturing is drastically increasing in modern industries. As a result of that, several challenges have raised over the years that essentially require urgent attention. Among these, coping with different faults in edge and cloud computing and recovering from permanent and temporary faults became prominent issues to be solved. In this paper, we focus on the challenges of applying fault tolerance techniques on edge and cloud computing in the context of manufacturing and we investigate the current state of the proposed approaches by categorizing them into several groups. Moreover, we identify critical gaps in the research domain as open research directions. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
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| 10. |
- Al-Dulaimy, Auday, et al.
(författare)
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TOLERANCER : A fault tolerance approach for cloud manufacturing environments
- 2022
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Ingår i: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665499965
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Konferensbidrag (refereegranskat)abstract
- The paper presents an approach to solve the software and hardware related failures in edge-cloud environments, more precisely, in cloud manufacturing environments. The proposed approach, called TOLERANCER, is composed of distributed components that continuously interact in a peer to peer fashion. Such interaction aims to detect stress situations or node failures, and accordingly, TOLERANCER makes decisions to avoid or solve any potential system failures. The efficacy of the proposed approach is validated through a set of experiments, and the performance evaluation shows that it responds effectively to different faults scenarios.
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