| 1. |
- Ghaderi, Adnan, et al.
(author)
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Design challenges in hardware development of time-sensitive networking : A research plan
- 2019
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In: CEUR Workshop Proceedings, Volume 2457. - : CEUR-WS.
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Conference paper (peer-reviewed)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.
(author)
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Cognitive and Time Predictable Task Scheduling in Edge-cloud Federation
- 2022
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In: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665499965
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Conference paper (peer-reviewed)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.
(author)
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Cost-aware workflow offloading in edge-cloud computing using a genetic algorithm
- 2024
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In: Journal of Supercomputing. - : Springer. - 0920-8542 .- 1573-0484.
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Journal article (peer-reviewed)abstract
- The edge-cloud computing continuum effectively uses fog and cloud servers to meet the quality of service (QoS) requirements of tasks when edge devices cannot meet those requirements. This paper focuses on the workflow offloading problem in edge-cloud computing and formulates this problem as a nonlinear mathematical programming model. The objective function is to minimize the monetary cost of executing a workflow while satisfying constraints related to data dependency among tasks and QoS requirements, including security and deadlines. Additionally, it presents a genetic algorithm for the workflow offloading problem to find near-optimal solutions with the cost minimization objective. The performance of the proposed mathematical model and genetic algorithm is evaluated on several real-world workflows. Experimental results demonstrate that the proposed genetic algorithm can find admissible solutions comparable to the mathematical model and outperforms particle swarm optimization, bee life algorithm, and a hybrid heuristic-genetic algorithm in terms of workflow execution costs.
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| 4. |
- Abdi, Somayeh, et al.
(author)
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Task Offloading in Edge-cloud Computing using a Q-Learning Algorithm
- 2024
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In: International Conference on Cloud Computing and Services Science, CLOSER - Proceedings. - : Science and Technology Publications, Lda. - 9789897587016 ; , s. 159-166
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Conference paper (other academic/artistic)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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| 5. |
- Afshar, Sara Zargari, et al.
(author)
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Investigating Alternatives for System Architectures to Enhance Discrete Manufacturing
- 2019
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In: International Journal of Distributed Sensor Networks. - Sweden : SAGE Publications. - 1550-1329 .- 1550-1477. ; 15:8
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Journal article (peer-reviewed)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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| 6. |
- Agerskans, Natalie, et al.
(author)
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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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In: IFIP Advances in Information and Communication Technology. - : Springer Science and Business Media Deutschland GmbH. - 9783031436611 ; , s. 311-325
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Conference paper (peer-reviewed)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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| 7. |
- Aglianò, Simone, et al.
(author)
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Resource Management and Control in Virtualized SDN Networks
- 2018
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In: CSI International Symposium on Real-Time and Embedded Systems and Technologies REST'18. - 9781538614754 ; , s. 47-53
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Conference paper (peer-reviewed)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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| 8. |
- Al-Dulaimy, Auday, et al.
(author)
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Fault Tolerance in Cloud Manufacturing : An Overview
- 2023
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In: 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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Conference paper (peer-reviewed)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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| 9. |
- Al-Dulaimy, Auday, et al.
(author)
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The computing continuum : From IoT to the cloud
- 2024
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In: Internet of Things. - : Elsevier B.V.. - 2543-1536 .- 2542-6605. ; 27
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Journal article (peer-reviewed)abstract
- In the era of the IoT revolution, applications are becoming ever more sophisticated and accompanied by diverse functional and non-functional requirements, including those related to computing resources and performance levels. Such requirements make the development and implementation of these applications complex and challenging. Computing models, such as cloud computing, can provide applications with on-demand computation and storage resources to meet their needs. Although cloud computing is a great enabler for IoT and endpoint devices, its limitations make it unsuitable to fulfill all design goals of novel applications and use cases. Instead of only relying on cloud computing, leveraging and integrating resources at different layers (like IoT, edge, and cloud) is necessary to form and utilize a computing continuum. The layers’ integration in the computing continuum offers a wide range of innovative services, but it introduces new challenges (e.g., monitoring performance and ensuring security) that need to be investigated. A better grasp and more profound understanding of the computing continuum can guide researchers and developers in tackling and overcoming such challenges. Thus, this paper provides a comprehensive and unified view of the computing continuum. The paper discusses computing models in general with a focus on cloud computing, the computing models that emerged beyond the cloud, and the communication technologies that enable computing in the continuum. In addition, two novel reference architectures are presented in this work: one for edge–cloud computing models and the other for edge–cloud communication technologies. We demonstrate real use cases from different application domains (like industry and science) to validate the proposed reference architectures, and we show how these use cases map onto the reference architectures. Finally, the paper highlights key points that express the authors’ vision about efficiently enabling and utilizing the computing continuum in the future.
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| 10. |
- Al-Dulaimy, Auday, et al.
(author)
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TOLERANCER : A fault tolerance approach for cloud manufacturing environments
- 2022
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In: IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665499965
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Conference paper (peer-reviewed)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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