https://www.mdu.se/

mdu.sePublications
Change search
Refine search result
1 - 13 of 13
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Bakhshi Valojerdi, Zeinab
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Persistent Fault-Tolerant Storage at the Fog Layer2021Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    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.

    Download full text (pdf)
    fulltext
  • 2.
    Bakhshi Valojerdi, Zeinab
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Balador, Ali
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. RISE SICS Västerås, Sweden.
    An Overview on Security and Privacy Challenges and Their Solutions in Fog-Based Vehicular Application2019In: 2019 IEEE 30TH INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (IEEE PIMRC WORKSHOPS), 2019Conference paper (Refereed)
    Abstract [en]

    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.

  • 3.
    Bakhshi Valojerdi, Zeinab
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Rodriguez-Navas, Guillermo
    Nokia Bell Labs, Israel.
    A preliminary roadmap for dependability research in fog computing2020In: ACM SIGBED Review, E-ISSN 1551-3688, Vol. 16, no 4, p. 14-19Article in journal (Refereed)
    Abstract [en]

    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. 

  • 4.
    Bakhshi Valojerdi, Zeinab
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Rodriguez-Navas, Guillermo
    Nokia Bell Labs, Israel.
    Hansson, Hans
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Dependable Fog Computing: A Systematic Literature Review2019In: Proceedings - 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019, 2019, p. 395-403, article id 8906732Conference paper (Refereed)
    Abstract [en]

    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.

    Download full text (pdf)
    fulltext
  • 5.
    Bakhshi Valojerdi, Zeinab
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Rodriguez-Navas, Guillermo
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Hansson, Hans
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fault-tolerant Permanent Storage for Container-based Fog Architectures2021In: Proceedings of the 2021 22nd IEEE International Conference on Industrial Technology (ICIT), 2021, p. 722-729Conference paper (Refereed)
    Abstract [en]

    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.

  • 6.
    Bakhshi Valojerdi, Zeinab
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Rodriguez-Navas, Guillermo
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Hansson, Hans
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Using UPPAAL to Verify Recovery in a Fault-tolerant Mechanism Providing Persistent State at the Edge2021In: 26th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2021, Västerås: Institute of Electrical and Electronics Engineers (IEEE), 2021Conference paper (Refereed)
    Abstract [en]

    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.

  • 7.
    Bakhshi Valojerdi, Zeinab
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Rodriguez-Navas, Guillermo
    Hansson, Hans
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Verifying the timing of a persistent storage for stateful fog applications2022In: 6th International Conference on Computer, Software and Modeling (ICCSM), Institute of Electrical and Electronics Engineers Inc. , 2022, p. 1-8Conference paper (Refereed)
    Abstract [en]

    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.

  • 8.
    Bakhshi, Zeinab
    Mälardalen University, School of Innovation, Design and Engineering.
    Lightweight Persistent Storage for Industrial Applications2023Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Clouds are large computer centers that offer remote access to computing and storage resources, making them popular for business and web applications. They are now being considered for use in safety-critical applications such as factories, but lack sufficient time predictability, which makes it challenging to use them in these time-sensitive applications. To overcome this limitation, an intermediate layer, the fog layer, is introduced to provide computational resources closer to the network edge. However, this new computing paradigm faces its own challenges in resource management, scalability, and reliability due to resource constrained nodes. Lightweight virtualization technologies like containerization can solve the performance-reliability dichotomy in fog computing and provide built-in fault tolerance mechanisms. By studying a robotic use-case, we realized the critical importance of persistent data storage for stateful applications, such as many control applications. However, container-based solutions lack fault-tolerant persistent storage. In this thesis, we identify new challenges associated with leveraging container-based architectures, particularly the importance of persistent storage for stateful applications. We investigate the design possibilities for persistent fault-tolerant storage and propose a solution adapted to container-based fog architectures and tailored for stateful applications. The solution provides scalability, auto recovery, and re-integration after failures at application and node levels. Key elements are a replicated data structure and a storage container, using a consensus protocol for distributed data consistency and fault tolerance in case of node failures. The fault tolerance and consistency of the solution are modeled and verified, and its timing requirements evaluated. We use simulation to evaluate the timing performance of our solution in larger set-ups. The results of our study show that although adding a consistency protocol introduces a timing overhead, the solution still meets timing requirements for the studied use-case even in presence of a set of relevant faults. By leveraging a four-dimensional approach, we also conduct a comparative analysis of our solution with other approaches from various perspectives, indicating that our solution can be applied in a broader context than initially intended.

    Download full text (pdf)
    fulltext
  • 9.
    Bakhshi, Zeinab
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Najafabadi, Zahra
    Distributed and parallel system group, University of Innsbruck, Austria.
    Rodriguez-Navas, Guillermo
    Hansson, Hans
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Prodan, Radu
    Department of Information Technology, University of Klagenfurt, Austria.
    Storage placement in continuum computing for a robotic applicationManuscript (preprint) (Other academic)
    Abstract [en]

    This paper analyzes the timing performance of a persistent storage designed for distributed containerbased architectures in industrial control applications. The storage ensures data availability andconsistency while accommodating 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 criticaldeadlines, particularly under specific failure patterns. Moreover, this evaluation method is applicablefor assessing other container-based critical applications with timing constraints that require persistentstorage. Further comparison results reveal that, while the method may underperform current centralized solutions under fault-free conditions, it outperforms the centralized solutions in failure scenarios

    Download full text (pdf)
    fulltext
  • 10.
    Bakhshi, Zeinab
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Rodriguez-Navas, Guillermo
    Nokia, Israel.
    Hansson, Hans
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Analyzing the performance of persistent storage for fault-tolerant stateful fog applications2023In: Journal of systems architecture, ISSN 1383-7621, E-ISSN 1873-6165, Vol. 144, article id 103004Article in journal (Refereed)
    Abstract [en]

    In this paper, we analyze the scalability and performance of a persistent, fault-tolerant storage approach that provides data availability and consistency in a distributed container-based architecture with intended use in industrial control applications. We use simulation to evaluate the performance of this storage system in terms of scalability and failures. As the industrial applications considered have timing constraints, the simulation results show that for certain failure patterns, it is possible to determine whether the storage solution can meet critical deadlines. The presented approach is applicable for evaluating timing constraints also of other container-based critical applications that require persistent storage.

  • 11.
    Beqiri, Lodiana
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bakhshi Valojerdi, Zeinab
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Punnekkat, Sasikumar
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Cicchetti, Antonio
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Remaining Useful Life Estimation for Railway Gearbox Bearings Using Machine Learning2023In: Lecture Notes in Computer Science, Springer Science and Business Media Deutschland GmbH , 2023, p. 62-77Conference paper (Refereed)
    Abstract [en]

    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.

  • 12.
    Salman Shaik, Mohammad
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Struhar, Vaclav
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bakhshi Valojerdi, Zeinab
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Dao, Van-Lan
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Desai, Nitin
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Papadopoulos, Alessandro
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Karagiannis, Vasileios
    TU Wien, Austria.
    Schulte, Stefan
    TU Wien, Austria.
    Venito, Alexandre
    TU Kaiserslautern, Germany.
    Enabling Fog-based Industrial Robotics Systems2020In: The 25th International Conference on Emerging Technologies and Factory Automation ETFA2020, 2020Conference paper (Refereed)
    Abstract [en]

    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.

  • 13.
    Samizadeh Nikoui, Tina
    et al.
    Islamic Azad University Tehran, Iran .
    Balador, Ali
    RISE SICS Västerås Sweden .
    Rahmani, Amir Masoud
    Islamic Azad University Tehran, Iran.
    Bakhshi, Zeinab
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Cost-Aware Task Scheduling in Fog-Cloud Environment2020Conference paper (Refereed)
    Abstract [en]

    Cloud computing provides computing and storage resources over the Internet to provide services for different industries. However, delay-sensitive applications like smart health and city applications now require computation over large amounts of data transferred to centralized cloud data centers which leads to drop in performance of such systems. The new paradigms of fog and edge computing provide new solutions by bringing resources closer to the user and provide low latency and energy efficiency compared to cloud services. It is important to find optimal placement of services and resources in the three-tier IoT to achieve improved cost and resource efficiency, higher QoS, and higher level of security and privacy. In this paper, we propose a cost-aware genetic-based (CAG) task scheduling algorithm for fog-cloud environments, which improves the cost efficiency in real-time applications with hard deadlines …

1 - 13 of 13
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf