| 1. |
- Caporuscio, Mauro, 1975-, et al.
(författare)
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Smart-troubleshooting connected devices : Concept, challenges and opportunities
- 2020
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Ingår i: Future generations computer systems. - : Elsevier. - 0167-739X .- 1872-7115. ; 111, s. 681-697
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Tidskriftsartikel (refereegranskat)abstract
- Today’s digital world and evolving technology has improved the quality of our lives but it has also come with a number of new threats. In the society of smart-cities and Industry 4.0, where many cyber-physical devices connect and exchange data through the Internet of Things, the need for addressing information security and solve system failures becomes inevitable. System failures can occur because of hardware failures, software bugs or interoperability issues. In this paper we introduce the industry-originated concept of “smart-troubleshooting” that is the set of activities and tools needed to gather failure information generated by heterogeneous connected devices, analyze them, and match them with troubleshooting instructions and software fixes. As a consequence of implementing smart-troubleshooting, the system would be able to self-heal and thus become more resilient. This paper aims to survey frameworks, methodologies and tools related to this new concept, and especially the ones needed to model, analyze and recover from failures in a (semi)automatic way. Smart-troubleshooting has a relation with event analysis to perform diagnostics and prognostics on devices manufactured by different suppliers in a distributed system. It also addresses management of appropriate product information specified in possibly unstructured formats to guide the troubleshooting workflow in identifying fault–causes and solutions. Relevant research is briefly surveyed in the paper in order to highlight current state-of-the-art, open issues, challenges to be tackled and future opportunities in this emerging industry paradigm.
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| 2. |
- Singh, Prasannjeet, et al.
(författare)
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Towards self-healing in the internet of things by log analytics and process mining
- 2020
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Ingår i: Proceedings of the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference. - Singapore : Research Publishing Services. - 9789811485930 ; , s. 4644-4651
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Konferensbidrag (refereegranskat)abstract
- The Internet of Things (IoT) will be used in increasingly complex and critical applications where heterogeneous devices will work together in connected systems. In this paper we address methods for log-analytics and process mining in order to support automatic problem detection and diagnosis in IoT. We introduce the idea of generating consistent event logs over various IoT devices in a particular format, and later a roadmap for it to be used in process mining. The paper also provides information about various statistics on process mining and its future prospects. Those methods are essential to provide a foundation for the future generation IoT systems that will be capable of self-healing. © ESREL2020-PSAM15 Organizers.Published by Research Publishing, Singapore.
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| 3. |
- Singh, Prasannjeet, et al.
(författare)
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Using log analytics and process mining to enable self-healing in the Internet of Things
- 2022
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Ingår i: Environment Systems and Decisions. - : Springer. - 2194-5403 .- 2194-5411. ; 42:2, s. 234-250
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Tidskriftsartikel (refereegranskat)abstract
- The Internet of Things (IoT) is rapidly developing in diverse and critical applications such as environmental sensing and industrial control systems. IoT devices can be very heterogeneous in terms of hardware and software architectures, communication protocols, and/or manufacturers. Therefore, when those devices are connected together to build a complex system, detecting and fixing any anomalies can be very challenging. In this paper, we explore a relatively novel technique known as Process Mining, which—in combination with log-file analytics and machine learning—can support early diagnosis, prognosis, and subsequent automated repair to improve the resilience of IoT devices within possibly complex cyber-physical systems. Issues addressed in this paper include generation of consistent Event Logs and definition of a roadmap toward effective Process Discovery and Conformance Checking to support Self-Healing in IoT.
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