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Punnekkat, SasikumarORCID iD iconorcid.org/0000-0001-5269-3900
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Publications (10 of 167) Show all publications
Nair, A. S., Patil, G., Agarwal, A., Pai, A. V., Raveendran, B. K. & Punnekkat, S. (2024). CAMP: a hierarchical cache architecture for multi-core mixed criticality processors. International Journal of Parallel, Emergent and Distributed Systems
Open this publication in new window or tab >>CAMP: a hierarchical cache architecture for multi-core mixed criticality processors
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2024 (English)In: International Journal of Parallel, Emergent and Distributed Systems, ISSN 1744-5760, E-ISSN 1744-5779Article in journal (Refereed) Epub ahead of print
Abstract [en]

CAMP proposes a hierarchical cache subsystem for multi-core mixed criticality processors, focusing on ensuring worst-case execution time (WCET) predictability in automotive applications. It incorporates criticality-aware locked L1 and L2 caches, reconfigurable at mode change intervals, along with criticality-aware last level cache partitioning. Evaluation using CACOSIM, Moola Multicore simulator, and CACTI simulation tools confirms the suitability of CAMP for keeping high-criticality jobs within timing budgets. A practical case study involving an automotive wake-up controller using the sniper v7.2 architecture simulator further validates its usability in real-world mixed criticality applications. CAMP presents a promising cache architecture for optimized multi-core mixed criticality systems. 

Place, publisher, year, edition, pages
Taylor and Francis Ltd., 2024
Keywords
cache coherence protocol, cache locking, cache partitioning, hierarchical cache architecture, Mixed-criticality systems, worst-case execution time (WCET), Architecture, Budget control, Cache memory, Computer architecture, Criticality (nuclear fission), Locks (fasteners), Network architecture, Bad-case execution time, Cache architecture, Cache coherence protocols, Hierarchical caches, Multi-cores, Worst-case execution time, Hierarchical systems
National Category
Computer Engineering
Identifiers
urn:nbn:se:mdh:diva-65238 (URN)10.1080/17445760.2023.2293913 (DOI)001130218200001 ()2-s2.0-85180256653 (Scopus ID)
Available from: 2024-01-03 Created: 2024-01-03 Last updated: 2024-01-17Bibliographically approved
Ali, N., Punnekkat, S. & Rauf, A. (2024). Modeling and safety analysis for collaborative safety-critical systems using hierarchical colored Petri nets. Journal of Systems and Software, 210, Article ID 111958.
Open this publication in new window or tab >>Modeling and safety analysis for collaborative safety-critical systems using hierarchical colored Petri nets
2024 (English)In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 210, article id 111958Article in journal (Refereed) Published
Abstract [en]

Context: Collaborative systems enable multiple independent systems to work together towards a common goal. These systems can include both human-system and system-system interactions and can be found in a variety of settings, including smart manufacturing, smart transportation, and healthcare. Safety is an important consideration for collaborative systems because one system's failure can significantly impact the overall system performance and adversely affect other systems, humans or the environment. Goal: Fail-safe mechanisms for safety-critical systems are designed to bring the system to a safe state in case of a failure in the sensors or actuators. However, a collaborative safety-critical system must do better and be safe-operational, for e.g., a failure of one of the members in a platoon of vehicles in the middle of a highway is not acceptable. Thus, failures must be compensated, and compliance with safety constraints must be ensured even under faults or failures of constituent systems. Method: In this paper, we model and analyze safety for collaborative safety-critical systems using hierarchical Coloured Petri nets (CPN). We used an automated Human Rescue Robot System (HRRS) as a case study, modeled it using hierarchical CPN, and injected some specified failures to check and confirm the safe behavior in case of unexpected scenarios. Results: The system behavior was observed after injecting three types of failures in constituent systems, and then safety mechanisms were applied to mitigate the effect of these failures. After applying safety mechanisms, the HRRS system's overall behavior was again observed both in terms of verification and validation, and the simulated results show that all the identified failures were mitigated and HRRS completed its mission. Conclusion: It was found that the approach based on formal methods (CPN modeling) can be used for the safety analysis, modeling, validation, and verification of collaborative safety-critical systems like HRRS. The hierarchical CPN provides a rigorous way of modeling to implement complex collaborative systems. 

Place, publisher, year, edition, pages
Elsevier Inc., 2024
Keywords
Colored Petri-nets, Petri nets, Safety analysis, Safety-critical
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-65686 (URN)10.1016/j.jss.2024.111958 (DOI)2-s2.0-85182283594 (Scopus ID)
Available from: 2024-01-24 Created: 2024-01-24 Last updated: 2024-02-20Bibliographically approved
Markovic, T., Leon, M., Leander, B. & Punnekkat, S. (2023). A Modular Ice Cream Factory Dataset on Anomalies in Sensors to Support Machine Learning Research in Manufacturing Systems. IEEE Access, 11, 29744-29758
Open this publication in new window or tab >>A Modular Ice Cream Factory Dataset on Anomalies in Sensors to Support Machine Learning Research in Manufacturing Systems
2023 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 11, p. 29744-29758Article in journal (Refereed) Published
Abstract [en]

A small deviation in manufacturing systems can cause huge economic losses, and all components and sensors in the system must be continuously monitored to provide an immediate response. The usual industrial practice is rather simplistic based on brute force checking of limited set of parameters often with pessimistic pre-defined bounds. The usage of appropriate machine learning techniques can be very valuable in this context to narrow down the set of parameters to monitor, define more refined bounds, and forecast impending issues. One of the factors hampering progress in this field is the lack of datasets that can realistically mimic the behaviours of manufacturing systems. In this paper, we propose a new dataset called MIDAS (Modular Ice cream factory Dataset on Anomalies in Sensors) to support machine learning research in analog sensor data. MIDAS is created using a modular manufacturing simulation environment that simulates the ice cream-making process. Using MIDAS, we evaluated four different supervised machine learning algorithms (Logistic Regression, Decision Tree, Random Forest, and Multilayer Perceptron) for two different problems: anomaly detection and anomaly classification. The results showed that multilayer perceptron is the most suitable algorithm with respect to model accuracy and execution time. We have made the data set and the code for the experiments publicly available, to enable interested researchers to enhance the state of the art by conducting further studies.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2023
Keywords
Sensors, Temperature sensors, Anomaly detection, Mixers, Manufacturing systems, Behavioral sciences, Cooling, Artificial neural networks, Machine learning, Supervised learning, Anomaly classification, artificial neural network, manufacturing dataset, sensor data
National Category
Computer Sciences
Identifiers
urn:nbn:se:mdh:diva-62361 (URN)10.1109/ACCESS.2023.3252901 (DOI)000965953800001 ()2-s2.0-85149838041 (Scopus ID)
Available from: 2023-05-03 Created: 2023-05-03 Last updated: 2023-05-03Bibliographically approved
Govardhan Rao, S. B., Castellanos Ardila, J. P. & Punnekkat, S. (2023). A Systematic Review of β-factor Models in the Quantification of Common Cause Failures. In: Proc. - Euromicro Conf. Softw. Eng. Adv. Appl., SEAA: . Paper presented at Proceedings - 2023 49th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2023 (pp. 262-269). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>A Systematic Review of β-factor Models in the Quantification of Common Cause Failures
2023 (English)In: Proc. - Euromicro Conf. Softw. Eng. Adv. Appl., SEAA, Institute of Electrical and Electronics Engineers Inc. , 2023, p. 262-269Conference paper, Published paper (Refereed)
Abstract [en]

Safety systems, i.e., systems whose malfunction can result in catastrophic consequences, are usually designed with redundancy in mind to reach high levels of reliability. However, Common Cause Failures (CCF), i.e., single failure events affecting multiple components or functions in a system, can threaten the desired reliability. To solve this problem, practitioners must use proven methods, such as those recommended by standards, to support CCF quantification. In particular, the β-factor model has become the de-facto model since the safety standard IEC 61508 considers it. As such standard applies to all industries, practitioners must figure out the industrial-specific implementation procedures. In this paper, we conducted a systematic literature review to understand how the β-factor model has been used in practice. As a result, we found 20 different models, which are industry/project-specific extensions of the first β-factor model proposed for the nuclear sector. We further classified those models by considering how the β-factor is estimated, and the level of redundancy support. Tool support for the models and their industrial use are also outlined. Finally, we present a discussion that covers the implication of our findings. Our study targets practitioners and researchers interested in using current β-factor models or evolving new ones for specific project needs.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
Common Cause Failure, Systematic Literature Review, β-factor model, Safety factor, Catastrophic consequences, Factor model, Failure events, Multiple components, Multiple function, Safety standard, Systematic Review, Β-factor model, Redundancy
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-65955 (URN)10.1109/SEAA60479.2023.00048 (DOI)2-s2.0-85183323422 (Scopus ID)9798350342352 (ISBN)
Conference
Proceedings - 2023 49th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2023
Available from: 2024-02-07 Created: 2024-02-07 Last updated: 2024-02-07Bibliographically approved
Desai, N., Dobrin, R. & Punnekkat, S. (2023). A Topology-specific Tight Worst-case Analysis of Strict Priority Traffic in Real-time Systems. In: IEEE Int. Conf. Emerging Technol. Factory Autom., ETFA: . Paper presented at IEEE International Conference on Emerging Technologies and Factory Automation, ETFA. Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>A Topology-specific Tight Worst-case Analysis of Strict Priority Traffic in Real-time Systems
2023 (English)In: IEEE Int. Conf. Emerging Technol. Factory Autom., ETFA, Institute of Electrical and Electronics Engineers Inc. , 2023Conference paper, Published paper (Refereed)
Abstract [en]

Tight end-to-end worst-case delay bounds for periodic traffic streams are essential for time sensitive networks. In this paper, we provide an algorithm to compute a tight (and accurate) end-to-end worst-case bound by considering distinct topological patterns and the manner in which streams enter and leave switches. This refined analysis uses non-preemptive, strict-priority arbitration mechanism commonly deployed in Ethernet switches. Compared to the state-of-the-art that considers all higher and equal priority interference as contributing to the worst-case bound, we present an analytical approach for computing a tighter worst-case delay bound and prove through discrete event simulations that only a certain number of equal-priority interference streams can actually affect the worst-case case. Our results enable efficient resource allocation and have implications for online re-configuration mechanisms for time-sensitive factory communication systems.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
Real-time networks, Strict-priority traffic, TSN, Worst-case delay, Discrete event simulation, Interactive computer systems, Online systems, Topology, Bad-case delay, Delay bound, End to end, Periodic traffic, Real - Time system, Real time network, Traffic streams, Worst-case analysis, Real time systems
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-64694 (URN)10.1109/ETFA54631.2023.10275348 (DOI)2-s2.0-85175426336 (Scopus ID)9798350339918 (ISBN)
Conference
IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Available from: 2023-11-09 Created: 2023-11-09 Last updated: 2023-11-09Bibliographically approved
Castellanos Ardila, J. P., Punnekkat, S., Hansson, H. & Grante, C. (2023). Arguing Operational Safety for Mixed Traffic in Underground Mining. In: 2023 18th Annual System of Systems Engineering Conference, SoSe 2023: . Paper presented at 2023 18th Annual System of Systems Engineering Conference, SoSe 2023, Lille 14 June 2023 through 16 June 2023. Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Arguing Operational Safety for Mixed Traffic in Underground Mining
2023 (English)In: 2023 18th Annual System of Systems Engineering Conference, SoSe 2023, Institute of Electrical and Electronics Engineers Inc. , 2023Conference paper, Published paper (Refereed)
Abstract [en]

Practitioners report improved productivity as one of the main benefits of using autonomous dump trucks in underground mining. However, manned vehicles are still needed to transport materials and personnel in the tunnels, which requires practices that may diminish autonomy benefits. Thus, both fleets shall be efficiently mixed to maximize the autonomy potential. In addition, sufficient safety shall be demonstrated for operations approval. This paper proposes a strategy to populate a GSN (Goal Structuring Notation) structure to argue for the sufficient safety of mixed traffic operations in underground mining. Our strategy considers SoS (System of Systems) concepts to describe the operations baseline and the initial argumentation line, i.e., risk reduction mitigation strategies for existing SoS components. Such a strategy is further detailed with risk reduction mitigation arguments for control systems. Mitigation strategies at both levels are derived from safety analysis supported by STPA (System-Theoretic Process Analysis), a safety analysis technique that aligns well with the SoS perspective. We also incorporate regulatory frameworks addressing machinery to align the arguments with mandatory statements of the machinery directive. Our strategy combines SoS concepts with analysis techniques and regulatory frameworks to facilitate safety case argumentation for operations approval in the European mining context. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
GSN, Harmonized Standards, Machinery Directive, Mixed Traffic, Safety Case Arguments, SoS, STPA, Mining, Safety engineering, Goal structuring notation, Process analysis, Safety case, Safety case argument, System-of-systems, System-theoretic process analyse, Underground mining, Mine trucks
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-63961 (URN)10.1109/SoSE59841.2023.10178525 (DOI)2-s2.0-85166732836 (Scopus ID)9798350327236 (ISBN)
Conference
2023 18th Annual System of Systems Engineering Conference, SoSe 2023, Lille 14 June 2023 through 16 June 2023
Available from: 2023-08-16 Created: 2023-08-16 Last updated: 2023-08-16Bibliographically approved
Nair, A. S., Pai, A. V., Patil, G., Raveendran, B. K. & Punnekkat, S. (2023). CLAMP: Criticality Aware Coherency Protocol for Locked Multi-level Caches in Multi-core Processors. In: Lect. Notes Networks Syst.: . Paper presented at Lecture Notes in Networks and Systems (pp. 371-381). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>CLAMP: Criticality Aware Coherency Protocol for Locked Multi-level Caches in Multi-core Processors
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2023 (English)In: Lect. Notes Networks Syst., Springer Science and Business Media Deutschland GmbH , 2023, p. 371-381Conference paper, Published paper (Refereed)
Abstract [en]

Cyber-physical systems that combine sensing, computing, control and networking with physical items and infrastructure, such as automotive, avionics and robotics, are rapidly becoming mixed criticality systems (MCS). The increasing expectations for computing ability and predictable temporal behaviour of these systems necessitate substantial enhancements in their memory subsystem architecture. The use of locked caches to have predictable execution time is one such optimization. There is no comprehensive method in order to manage coherency in locked caches in any of the current cache coherence protocols like MOESI. CLAMP—A criticality aware coherency protocol for locked multi-level caches in multi-core processors is an updated variant of MOESI and as an extension of MOESIL, to improve the data consistency of locked caches. The work CLAMP proposes an improvised locked cache coherence protocol for multiple levels of cache in multi-core MCS, whereas MOESIL is restricted to two-level cache architecture. Experiments using real-time benchmark programs on CACOSIM reveal an average cache miss rate reduction of 18% for high-criticality jobs.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2023
Keywords
Cache locking, Cache optimization, Cache partitioning, Hierarchical cache architecture, Mixed criticality systems, Multi-core/many core architecture, Cache memory, Criticality (nuclear fission), Embedded systems, Hierarchical systems, Internet protocols, Locks (fasteners), Memory architecture, Cache architecture, Hierarchical caches, Many-core architecture, Mixed-criticality systems, Multi-cores, Network architecture
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-64431 (URN)10.1007/978-981-99-0483-9_30 (DOI)2-s2.0-85171348053 (Scopus ID)9789819904822 (ISBN)
Conference
Lecture Notes in Networks and Systems
Available from: 2023-10-09 Created: 2023-10-09 Last updated: 2023-10-09Bibliographically approved
Ali, N. & Punnekkat, S. (2023). Composite Hazard Analysis of System of Systems for Mixed-traffic Automation in Underground Mine. In: International Conference on Ubiquitous and Future Networks, ICUFN: . Paper presented at 14th International Conference on Ubiquitous and Future Networks, ICUFN 2023, Paris, France, 4 July through 7 July 2023 (pp. 445-450). IEEE Computer Society, July
Open this publication in new window or tab >>Composite Hazard Analysis of System of Systems for Mixed-traffic Automation in Underground Mine
2023 (English)In: International Conference on Ubiquitous and Future Networks, ICUFN, IEEE Computer Society, 2023, Vol. July, p. 445-450Conference paper, Published paper (Refereed)
Abstract [en]

Hazard analysis for a single system focuses on identifying and evaluating potential hazards associated with the individual system, its components, and their interactions. There are well-established hazard analysis techniques that are widely used to identify hazards for single systems. However, unlike single systems, hazard analysis in a System of Systems (SoS) must focus on analyzing the potential hazards (including emergent ones) that can arise from the interactions between multiple individual systems. This type of analysis considers the complex interactions between systems and the interdependence between their components and the environment in which they operate. Therefore, it is necessary to understand the application scenarios of SoS and to employ a systematic approach to identify all potential hazards. This paper applies the Composite Hazard Analysis Technique (CompHAT) to an industrial case study from a mining and equipment domain. The results show that the CompHAT is useful in identifying the interaction faults and their propagation routes between components of a constituent system and between constituent systems in an SoS. We also report that, due to the tool support, CompHAT can be beneficial for safety engineers to trace the faults in the network of an SoS in a more efficient and effective manner.

Place, publisher, year, edition, pages
IEEE Computer Society, 2023
Keywords
Hazard Analysis, Safety, System of Systems, Underground Mine, Hazards, Mining, Analysis techniques, Application scenario, Hazards analysis, Individual systems, Mixed traffic, Potential hazards, System focus, System hazards, System-of-systems
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-65189 (URN)10.1109/ICUFN57995.2023.10200169 (DOI)2-s2.0-85169294705 (Scopus ID)9798350335385 (ISBN)
Conference
14th International Conference on Ubiquitous and Future Networks, ICUFN 2023, Paris, France, 4 July through 7 July 2023
Available from: 2023-12-21 Created: 2023-12-21 Last updated: 2023-12-21Bibliographically approved
Colaco, L., Jain, P., Nair, A. S., Raveendran, B. K. & Punnekkat, S. (2023). mcDVFS: cycle conserving DVFS scheduler for multi-core mixed criticality systems. International Journal of Parallel, Emergent and Distributed Systems
Open this publication in new window or tab >>mcDVFS: cycle conserving DVFS scheduler for multi-core mixed criticality systems
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2023 (English)In: International Journal of Parallel, Emergent and Distributed Systems, ISSN 1744-5760, E-ISSN 1744-5779Article in journal (Refereed) Published
Abstract [en]

Multi-core architectures have grown to be a popular choice for deploying Mixed Criticality Systems (MCS). The focus of research in MCS has been to provide timing assurances for jobs with different criticality levels. Due to their significant processing demands and energy-aware/constrained nature, energy conservation in these systems is becoming mandatory. This article presents, mcDVFS, an energy management technique based on Dynamic-Voltage-and-Frequency-Scaling for multi-core MCS. mcDVFS achieves significant energy reduction while maintaining timing guarantees. It also prioritizes quality of service whenever feasible. Extensive experimental simulations show energy savings of ≈ 52% and 34% when compared to EDF-VD and EDF-VD with QoS. 

Place, publisher, year, edition, pages
Taylor and Francis Ltd., 2023
Keywords
DVFS, Energy efficiency, mixed criticality systems, multi-core, quality of service, Computer architecture, Criticality (nuclear fission), Dynamic frequency scaling, Voltage scaling, Dynamic voltage and frequency scaling, Energy aware, Focus of researches, Management techniques, Mixed-criticality systems, Multi-cores, Multicore architectures, ON dynamics, Quality-of-service
National Category
Energy Systems
Identifiers
urn:nbn:se:mdh:diva-63968 (URN)10.1080/17445760.2023.2243420 (DOI)001043584500001 ()2-s2.0-85166944327 (Scopus ID)
Available from: 2023-08-16 Created: 2023-08-16 Last updated: 2023-08-23Bibliographically approved
Leon, M., Markovic, T. & Punnekkat, S. (2023). Multi-Objective Optimization on Autoencoder for Feature Encoding and Attack Detection on Network Data. In: GECCO Companion - Proc. Genet. Evol. Comput. Conf. Companion: . Paper presented at GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (pp. 379-382). Association for Computing Machinery, Inc
Open this publication in new window or tab >>Multi-Objective Optimization on Autoencoder for Feature Encoding and Attack Detection on Network Data
2023 (English)In: GECCO Companion - Proc. Genet. Evol. Comput. Conf. Companion, Association for Computing Machinery, Inc , 2023, p. 379-382Conference paper, Published paper (Refereed)
Abstract [en]

There is a growing number of network attacks and the data on the network is more exposed than ever with the increased activity on the Internet. Applying Machine Learning (ML) techniques for cyber-security is a popular and effective approach to address this problem. However, the data which is used by ML algorithms have to be protected. In this paper, we present a framework that combines autoencoder, multi-objective optimization algorithms, and different ML algorithms to encode the network data, reduce its size, and detect and classify the network attacks. The novel element used in this framework, with respect to earlier research, is the application of multi-objective optimization algorithms, such as Multi-Objective Differential Evolution or Non-dominated Sorting Genetic Algorithm-II, to handle the different objectives in the fitness function of the autoencoder (autoencoder decoding error and accuracy of ML algorithm). We evaluated six different ML algorithms for attack detection and classification on network dataset UNSWNB15. The performance of the proposed framework is compared with single-objective Differential Evolution. The results showed that Multi-Objective Differential Evolution outperforms the counterparts for attack detection, while all the evaluated algorithms showed similar performance for attack classification.

Place, publisher, year, edition, pages
Association for Computing Machinery, Inc, 2023
Keywords
cybersecurity, differential evolution, genetic algorithm, machine learning, multi-objective optimization, Classification (of information), Computer crime, Encoding (symbols), Multiobjective optimization, Network coding, Attack detection, Auto encoders, Cyber security, Machine learning algorithms, Machine-learning, Multi-objectives optimization, Network attack, Network data, Optimization algorithms, Genetic algorithms
National Category
Computer Sciences
Identifiers
urn:nbn:se:mdh:diva-64176 (URN)10.1145/3583133.3590600 (DOI)2-s2.0-85169019405 (Scopus ID)9798400701207 (ISBN)
Conference
GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion
Available from: 2023-09-06 Created: 2023-09-06 Last updated: 2023-09-06Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0001-5269-3900

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