| 1. |
- Salman Shaik, Mohammad, et al.
(författare)
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Enabling Fog-based Industrial Robotics Systems
- 2020
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Ingår i: The 25th International Conference on Emerging Technologies and Factory Automation ETFA2020. - 9781728189567
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Konferensbidrag (refereegranskat)abstract
- Low latency and on demand resource availability enable fog computing to host industrial applications in a cloud like manner. One industrial domain which stands to benefit from the advantages of fog computing is robotics. However, the challenges in developing and implementing a fog-based robotic system are manifold. To illustrate this, in this paper we discuss a system involving robots and robot cells at a factory level, and then highlight the main building blocks necessary for achieving such functionality in a fog-based system. Further, we elaborate on the challenges in implementing such an architecture, with emphasis on resource virtualization, memory interference management, real-time communication and the system scalability, dependability and safety. We then discuss the challenges from a system perspective where all these aspects are interrelated.
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| 2. |
- Bakhshi Valojerdi, Zeinab, 1986-, et al.
(författare)
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A preliminary roadmap for dependability research in fog computing
- 2020
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Ingår i: ACM SIGBED Review. - : Association for Computing Machinery. - 1551-3688. ; 16:4, s. 14-19
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Tidskriftsartikel (refereegranskat)abstract
- Fog computing aims to support novel real-time applications by extending cloud resources to the network edge. This technology is highly heterogeneous and comprises a wide variety of devices interconnected through the so-called fog layer. Compared to traditional cloud infrastructure, fog presents more varied reliability challenges, due to its constrained resources and mobility of nodes. This paper summarizes current research efforts on fault tolerance and dependability in fog computing and identifies less investigated open problems, which constitute interesting research directions to make fogs more dependable.
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| 3. |
- Bakhshi Valojerdi, Zeinab, 1986-, et al.
(författare)
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An overview on security and privacy challenges and their solutions in fog-based vehicular application
- 2019
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Ingår i: 2019 IEEE 30th International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC Workshops 2019. - : Institute of Electrical and Electronics Engineers Inc.. - 9781538693582
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Konferensbidrag (refereegranskat)abstract
- Fog computing is an emerging computing paradigm that extends cloud services to the edge of the network by moving computation tasks from cloud to network edges to reduce response latency in a wireless network. Fog computing inherits the principle of peer-to-peer networking, decentralization, and geographical distribution from clouds. Hence, fog computing becomes an ideal platform for readily supporting vehicular applications due to its dynamic support for mobility of client-devices and low latent heterogeneous communication capabilities. Despite many advantages, a multitude of security and privacy issues affects the platforms and renders it as a target for unknown adversaries. This has significant implication in the development of safety critical applications, such as vehicular cloud and intelligent transportation system. This paper presents, an overview of existing security and privacy vulnerabilities in fog computing, particularly in vehicular networks. Moreover, state-of-the-art security and privacy solutions for fog based vehicular networks are analyzed. In conclusion, open challenges and future research directions are discussed.
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| 4. |
- Bakhshi Valojerdi, Zeinab, 1986-, et al.
(författare)
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Dependable Fog Computing : A Systematic Literature Review
- 2019
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Ingår i: Proceedings - 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019. ; , s. 395-403
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Konferensbidrag (refereegranskat)abstract
- Fog computing has been recently introduced to bridge the gap between cloud resources and the network edge. Fog enables low latency and location awareness, which is considered instrumental for the realization of IoT, but also faces reliability and dependability issues due to node mobility and resource constraints. This paper focuses on the latter, and surveys the state of the art concerning dependability and fog computing, by means of a systematic literature review. Our findings show the growing interest in the topic but the relative immaturity of the technology, without any leading research group. Two problems have attracted special interest: guaranteeing reliable data storage/collection in systems with unreliable and untrusted nodes, and guaranteeing efficient task allocation in the presence of varying computing load. Redundancy-based techniques, both static and dynamic, dominate the architectures of such systems. Reliability, availability and QoS are the most important dependability requirements for fog, whereas aspects such as safety and security, and their important interplay, have not been investigated in depth.
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| 5. |
- Bakhshi Valojerdi, Zeinab, 1986-, et al.
(författare)
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Evaluation of Storage Placement in Computing Continuum for a Robotic Application : A Simulation-Based Performance Analysis
- 2024
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Ingår i: Journal of Grid Computing. - : Springer Science+Business Media B.V.. - 1570-7873 .- 1572-9184. ; 22:2
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Tidskriftsartikel (refereegranskat)abstract
- This paper analyzes the timing performance of a persistent storage designed for distributed container-based architectures in industrial control applications. The timing performance analysis is conducted using an in-house simulator, which mirrors our testbed specifications. The storage ensures data availability and consistency even in presence of faults. The analysis considers four aspects: 1. placement strategy, 2. design options, 3. data size, and 4. evaluation under faulty conditions. Experimental results considering the timing constraints in industrial applications indicate that the storage solution can meet critical deadlines, particularly under specific failure patterns. Comparison results also reveal that, while the method may underperform current centralized solutions in fault-free conditions, it outperforms the centralized solutions in failure scenario. Moreover, the used evaluation method is applicable for assessing other container-based critical applications with timing constraints that require persistent storage.
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| 6. |
- Bakhshi Valojerdi, Zeinab, 1986-, et al.
(författare)
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Fault-tolerant Permanent Storage for Container-based Fog Architectures
- 2021
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Ingår i: Proceedings of the 2021 22nd IEEE International Conference on Industrial Technology (ICIT). ; , s. 722-729
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Konferensbidrag (refereegranskat)abstract
- Container-based architectures are widely used for cloud computing and can have an important role in the implementation of fog computing infrastructures. However, there are some crucial dependability aspects that must be addressed to make containerization suitable for critical fog applications, e.g., in automation and robotics. This paper discusses challenges in applying containerization at the fog layer and focuses on one of those challenges: provision of fault-tolerant permanent storage. The paper also presents a container-based fog architecture utilizing so-called storage containers, which combine built-in fault-tolerance mechanisms of containers with a distributed consensus protocol to achieve data consistency.
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| 7. |
- Bakhshi Valojerdi, Zeinab, 1986-
(författare)
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Persistent Fault-Tolerant Storage at the Fog Layer
- 2021
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Clouds are powerful computer centers that provide computing and storage facilities that can be remotely accessed. The flexibility and cost-efficiency offered by clouds have made them very popular for business and web applications. The use of clouds is now being extended to safety-critical applications such as factories. However, cloud services do not provide time predictability which creates a hassle for such time-sensitive applications. Moreover, delays in the data communication between clouds and the devices the clouds control are unpredictable. Therefore, to increase predictability an intermediate layer between devices and the cloud is introduced. This layer, the Fog layer, aims to provide computational resources closer to the edge of the network. However, the fog computing paradigm relies on resource-constrained nodes, creating new potential challenges in resource management, scalability, and reliability. Solutions such as lightweight virtualization technologies can be leveraged for solving the dichotomy between performance and reliability in fog computing. In this context, container-based virtualization is a key technology providing lightweight virtualization for cloud computing that can be applied in fog computing as well. Such container-based technologies provide fault tolerance mechanisms that improve the reliability and availability of application execution. By the study of a robotic use-case, we have realized that persistent data storage for stateful applications at the fog layer is particularly important. In addition, we identified the need to enhance the current container orchestration solution to fit fog applications executing in container-based architectures. In this thesis, we identify open challenges in achieving dependable fog platforms. Among these, we focus particularly on scalable, lightweight virtualization, auto-recovery, and re-integration solutions after failures in fog applications and nodes. We implement a testbed to deploy our use-case on a container-based fog platform and investigate the fulfillment of key dependability requirements. We enhance the architecture and identify the lack of persistent storage for stateful applications as an important impediment for the execution of control applications. We propose a solution for persistent fault-tolerant storage at the fog layer, which dissociates storage from applications to reduce application load and separates the concern of distributed storage. Our solution includes a replicated data structure supported by a consensus protocol that ensures distributed data consistency and fault tolerance in case of node failures. Finally, we use the UPPAAL verification tool to model and verify the fault tolerance and consistency of our solution.
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| 8. |
- Bakhshi Valojerdi, Zeinab, 1986-, et al.
(författare)
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Using UPPAAL to Verify Recovery in a Fault-tolerant Mechanism Providing Persistent State at the Edge
- 2021
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Ingår i: 26th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2021. - Västerås : Institute of Electrical and Electronics Engineers (IEEE). - 9781728129891
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Konferensbidrag (refereegranskat)abstract
- In our previous work we proposed a fault-tolerant persistent storage for container-based fog architecture. We leveraged the use of containerization to provide storage as a containerized application working along with other containers. As a fault-tolerance mechanism we introduced a replicated data structure and to solve consistency issue between the replicas distributed in the cluster of nodes, we used the RAFT consensus protocol. In this paper, we verify our proposed solution using the UPPAAL model checker. We explain how our solution is modeled in UPPAAL and present a formal verification of key properties related to persistent storage and data consistency between nodes.
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| 9. |
- Bakhshi Valojerdi, Zeinab, 1986-, et al.
(författare)
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Verifying the timing of a persistent storage for stateful fog applications
- 2022
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Ingår i: 6th International Conference on Computer, Software and Modeling (ICCSM). - : Institute of Electrical and Electronics Engineers Inc.. ; , s. 1-8
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Konferensbidrag (refereegranskat)abstract
- In this paper, we analyze the failure semantics of a persistent fault-tolerant storage solution for stateful fog applications. This storage system is a container-based solution that provides data availability and consistency in a distributed container-based fog architecture. We evaluate the behavior of this storage system with a formal model that includes all the important time parameters and temporal aspects of the solution. This allows us to verify data consistency and other fault-tolerance properties of our system model while considering application startup latency, together with synchronization intervals and delays. We prove that the solution can tolerate failures at application, node, communication and storage level with the ability to automatically recover from failures and provides data consistency within the synchronization delay defined as t time units, which we can calculate for a given system configuration.
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| 10. |
- Beqiri, Lodiana, et al.
(författare)
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Remaining Useful Life Estimation for Railway Gearbox Bearings Using Machine Learning
- 2023
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Ingår i: Lecture Notes in Computer Science. - : Springer Science and Business Media Deutschland GmbH. - 9783031433658 ; , s. 62-77
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Konferensbidrag (refereegranskat)abstract
- Gearbox bearing maintenance is one of the major overhaul cost items for railway electric propulsion systems. They are continuously exposed to challenging working conditions, which compromise their performance and reliability. Various maintenance strategies have been introduced over time to improve the operational efficiency of such components, while lowering the cost of their maintenance. One of these is predictive maintenance, which makes use of previous historical data to estimate a component’s remaining useful life (RUL). This paper introduces a machine learning-based method for calculating the RUL of railway gearbox bearings. The method uses unlabeled mechanical vibration signals from gearbox bearings to detect patterns of increased bearing wear and predict the component’s residual life span. We combined a data smoothing method, a change point algorithm to set thresholds, and regression models for prediction. The proposed method has been validated using real-world gearbox data provided by our industrial partner, Alstom Transport AB in Sweden. The results are promising, particularly with respect to the predicted failure time. Our model predicted the failure to occur on day 330, while the gearbox bearing’s actual lifespan was 337 days. The deviation of just 7 days is a significant result, since an earlier RUL prediction value is usually preferable to avoid unexpected failure during operations. Additionally, we plan to further enhance the prediction model by including more data representing failing bearing patterns.
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