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  • 1.
    Desai, Nitin
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Punnekkat, Sasikumar
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Enhancing Fault Detection in Time Sensitive Networks using Machine Learning2020Ingår i: 2020 International Conference on COMmunication Systems and NETworkS, COMSNETS 2020, Institute of Electrical and Electronics Engineers Inc. , 2020, s. 714-719Konferensbidrag (Refereegranskat)
    Abstract [en]

    Time sensitive networking (TSN) is gaining attention in industrial automation networks since it brings essential real-time capabilities to the Ethernet layer. Safety-critical realtime applications based on TSN require both timeliness as well as fault-tolerance guarantees. The TSN standard 802.1CB introduces seamless redundancy mechanisms for time-sensitive data whereby each data frame is sequenced and duplicated across a redundant link to prevent single points of failure (most commonly, link failures). However, a major shortcoming of 802.1CB is the lack of fault detection mechanisms which can result in unnecessary replications even under good link conditions - clearly inefficient in terms of bandwidth use. This paper proposes a machine learning-based intelligent configuration synthesis mechanism that enhances bandwidth utilization by replicating frames only when a link has a higher propensity for failure. 

  • 2.
    Desai, Nitin
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Punnekkat, Sasikumar
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Safety of fog-based industrial automation systems2019Ingår i: IoT-Fog 2019 - Proceedings of the 2019 Workshop on Fog Computing and the IoT, Association for Computing Machinery, Inc , 2019, s. 6-10Konferensbidrag (Refereegranskat)
    Abstract [en]

    The Fog computing paradigm employing multiple technologies is expected to play a key role in a multitude of industrial applications by fulfilling futuristic requirements such as flexible and enhanced computing, storage, and networking capability closer to the field devices. While performance aspects of the Fog paradigm has been the central focus of researchers, safety aspects have not received enough attention so far. In this paper, we identify various safety challenges related to the Fog paradigm and provide specific safety design aspects as a step towards enhancing safety in industrial automation scenarios. We contextualize these ideas by invoking a distributed mobile robots use-case that can benefit from the use of the Fog paradigm.

  • 3.
    Desai, Nitin
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Punnekkat, Sasikumar
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Safety-oriented flexible design of Autonomous Mobile Robot systems2019Ingår i: 2019 IEEE International Symposium on Systems Engineering ISSE 2019, Edinburgh, United Kingdom, 2019, nr 5Konferensbidrag (Refereegranskat)
    Abstract [en]

    Current industrial automation applications particularly within the smart manufacturing domain require mobility, flexibility of deployment, and scalability. In addition to these, it is important to mitigate the risk of safety hazards. In this paper we discuss a flexible, granular, and software-based system design that aims to improve both security and safety of an autonomous mobile robot (AMR) based industrial automation systems. The decentralised control architecture ensures that safety-critical functions are distributed throughout the network. To this end, we first define system-level safety requirements and identify procedures required to satisfy safety-critical functions such as emergency-stop (E-Stop). We then explain the benefits provided by the proposed system architecture vis-a-vis its resilience towards potential safety hazards.

  • 4.
    Dobrin, Radu
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Desai, Nitin
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Punnekkat, Sasikumar
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    On fault-tolerant scheduling of time sensitive networks2019Ingår i: OpenAccess Series in Informatics, Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing , 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    Time sensitive networking (TSN) is gaining attention in industrial automation networks since it brings essential real-time capabilities at the data link layer. Though it can provide deterministic latency under error free conditions, TSN still largely depends on space redundancy for improved reliability. In many scenarios, time redundancy could be an adequate as well as cost efficient alternative. Time redundancy in turn will have implications due to the need for over-provisions needed for timeliness guarantees. In this paper, we discuss how to embed fault-tolerance capability into TSN schedules and describe our approach using a simple example.

  • 5. Karagiannis, V.
    et al.
    Desai, Nitin
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Schulte, S.
    Punnekkat, Sasikumar
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Addressing the node discovery problem in fog computing2020Ingår i: OpenAccess Series in Informatics, Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing , 2020, Vol. 80Konferensbidrag (Refereegranskat)
    Abstract [en]

    In recent years, the Internet of Things (IoT) has gained a lot of attention due to connecting various sensor devices with the cloud, in order to enable smart applications such as: smart traffic management, smart houses, and smart grids, among others. Due to the growing popularity of the IoT, the number of Internet-connected devices has increased significantly. As a result, these devices generate a huge amount of network traffic which may lead to bottlenecks, and eventually increase the communication latency with the cloud. To cope with such issues, a new computing paradigm has emerged, namely: fog computing. Fog computing enables computing that spans from the cloud to the edge of the network in order to distribute the computations of the IoT data, and to reduce the communication latency. However, fog computing is still in its infancy, and there are still related open problems. In this paper, we focus on the node discovery problem, i.e., how to add new compute nodes to a fog computing system. Moreover, we discuss how addressing this problem can have a positive impact on various aspects of fog computing, such as fault tolerance, resource heterogeneity, proximity awareness, and scalability. Finally, based on the experimental results that we produce by simulating various distributed compute nodes, we show how addressing the node discovery problem can improve the fault tolerance of a fog computing system. © Vasileios Karagiannis, Nitin Desai, Stefan Schulte, and Sasikumar Punnekkat; licensed under Creative Commons License CC-BY 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020).

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