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Papadopoulos, Alessandro, ProfessorORCID iD iconorcid.org/0000-0002-1364-8127
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Publications (10 of 121) Show all publications
Lager, A., Miloradović, B., Spampinato, G., Nolte, T. & Papadopoulos, A. (2023). A Scalable Heuristic for Mission Planning of Mobile Robot Teams. In: IFAC-PapersOnLine: . Paper presented at IFAC-PapersOnLine (pp. 7865-7872). Elsevier B.V. (2)
Open this publication in new window or tab >>A Scalable Heuristic for Mission Planning of Mobile Robot Teams
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2023 (English)In: IFAC-PapersOnLine, Elsevier B.V. , 2023, no 2, p. 7865-7872Conference paper, Published paper (Refereed)
Abstract [en]

In this work, we investigate a task planning problem for assigning and planning a mobile robot team to jointly perform a kitting application with alternative task locations. To this end, the application is modeled as a Robot Task Scheduling Graph and the planning problem is modeled as a Mixed Integer Linear Program (MILP). We propose a heuristic approach to solve the problem with a practically useful performance in terms of scalability and computation time. The experimental evaluation shows that our heuristic approach is able to find efficient plans, in comparison with both optimal and non-optimal MILP solutions, in a fraction of the planning time.

Place, publisher, year, edition, pages
Elsevier B.V., 2023
Keywords
Mobile Robotics, Task Planning
National Category
Robotics
Identifiers
urn:nbn:se:mdh:diva-66134 (URN)10.1016/j.ifacol.2023.10.021 (DOI)2-s2.0-85184958013 (Scopus ID)9781713872344 (ISBN)
Conference
IFAC-PapersOnLine
Available from: 2024-02-26 Created: 2024-02-26 Last updated: 2024-02-26Bibliographically approved
Miloradović, B., Bigorra, E. M., Nolte, T. & Papadopoulos, A. (2023). Challenges in the Automated Disassembly Process of Electric Vehicle Battery Packs. 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 >>Challenges in the Automated Disassembly Process of Electric Vehicle Battery Packs
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]

The surge in the development and adoption of Electric Vehicles (EVs) globally is a trend many countries are paying close attention to. This inevitably means that a significant number of EV batteries will soon reach their End-of-Life (EoL). This looming issue reveals a notable challenge: there's currently a lack of sustainable strategies for managing Lithium-ion Batteries (LiBs) when they reach their EoL stage. The process of disassembling these battery packs is challenging due to their intricate design, involving several different materials and components integrated tightly for performance and safety. Consequently, effective disassembly and subsequent recycling procedures require highly specialized methods and equipment, and involve significant safety and health risks. Moreover, existing recycling technologies often fail to recover all valuable and potentially hazardous materials, leading to both economic and environmental loss. This paper provides an overview and analysis of possible challenges arising in the domain of automated battery disassembly and recycling of EV batteries that reached their EoL. We provide insight into the disassembly process as well as optimization of the disassembly sequence with the goal of minimizing the overall cost and environmental footprint.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
Automated Battery Disassem-bly, Battery Recycling, Electric Vehicles, Battery Pack, Electronic Waste, Environmental technology, Health risks, Lithium-ion batteries, Disassembly process, Electric vehicle batteries, End of lives, Life stages, Performance, Safety and healths, Sustainable strategies, Recycling
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:mdh:diva-64708 (URN)10.1109/ETFA54631.2023.10275389 (DOI)2-s2.0-85175453751 (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
Alhashimi, A., Nolte, T. & Papadopoulos, A. (2023). Change-Point and Model Estimation with Heteroskedastic Noise and Unknown Model Structure. In: Int. Conf. Control, Decis. Inf. Technol., CoDIT: . Paper presented at 9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023 (pp. 2126-2132). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Change-Point and Model Estimation with Heteroskedastic Noise and Unknown Model Structure
2023 (English)In: Int. Conf. Control, Decis. Inf. Technol., CoDIT, Institute of Electrical and Electronics Engineers Inc. , 2023, p. 2126-2132Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we investigate the problem of modeling time-series as a process generated through (i) switching between several independent sub-models; (ii) where each sub-model has heteroskedastic noise, and (iii) a polynomial bias, describing nonlinear dependency on system input. First, we propose a generic nonlinear and heteroskedastic statistical model for the process. Then, we design Maximum Likelihood (ML) parameters estimation method capable of handling heteroscedasticity and exploiting constraints on model structure. We investigate solving the intractable ML optimization using population-based stochastic numerical methods. We then find possible model change-points that maximize the likelihood without over-fitting measurement noise. Finally, we verify the usefulness of the proposed technique in a practically relevant case study, the execution-time of odometry estimation for a robot operating radar sensor, and evaluate the different proposed procedures using both simulations and field data.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
Maximum likelihood estimation, Population statistics, Stochastic systems, Change modeling, Change point estimation, Maximum likelihood parameter estimations, Model estimation, Modelling time, Nonlinear dependencies, Parameter estimation method, Statistic modeling, Submodels, Times series, Numerical methods
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-64852 (URN)10.1109/CoDIT58514.2023.10284232 (DOI)2-s2.0-85177439031 (Scopus ID)9798350311402 (ISBN)
Conference
9th 2023 International Conference on Control, Decision and Information Technologies, CoDIT 2023
Available from: 2023-11-29 Created: 2023-11-29 Last updated: 2024-01-18Bibliographically approved
Johansson, B., Rågberger, M., Papadopoulos, A. & Nolte, T. (2023). Consistency before Availability: Network Reference Point based Failure Detection for Controller Redundancy. 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 >>Consistency before Availability: Network Reference Point based Failure Detection for Controller Redundancy
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]

Distributed control systems constitute the automation solution backbone in domains where downtime is costly. Redundancy reduces the risk of faults leading to unplanned downtime. The Industry 4.0 appetite to utilize the device-to-cloud continuum increases the interest in network-based hardware-agnostic controller software. Functionality, such as controller redundancy, must adhere to the new ground rules of pure network dependency. In a standby controller redundancy, only one controller is the active primary. When the primary fails, the backup takes over. A typical network-based failure detection uses a cyclic message with a known interval, a.k.a. a heartbeat. Such a failure detection interprets heartbeat absences as a failure of the supervisee; consequently, a network partitioning could be indistinguishable from a node failure. Hence, in a network partitioning situation, a conventional heartbeat-based failure detection causes more than one active controller in the redundancy set, resulting in inconsistent outputs. We present a failure detection algorithm that uses network reference points to prevent network partitioning from leading to dual primary controllers. In other words, a failure detection that prioritizes consistency before availability.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
Distributed parameter control systems, Maintenance, Redundancy, Active controller, Automation solutions, Detection algorithm, Failure detection, In networks, Network partitioning, Network-based, Node failure, Point-based, Reference points, Controllers
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-64700 (URN)10.1109/ETFA54631.2023.10275664 (DOI)2-s2.0-85175422976 (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
Friebe, A., Markovic, F., Papadopoulos, A. & Nolte, T. (2023). Continuous-Emission Markov Models for Real-Time Applications: Bounding Deadline Miss Probabilities. In: Proc. IEEE Real Time Embedded Technol. Appl. Symp. RTAS: . Paper presented at Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS (pp. 14-26). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Continuous-Emission Markov Models for Real-Time Applications: Bounding Deadline Miss Probabilities
2023 (English)In: Proc. IEEE Real Time Embedded Technol. Appl. Symp. RTAS, Institute of Electrical and Electronics Engineers Inc. , 2023, p. 14-26Conference paper, Published paper (Refereed)
Abstract [en]

Probabilistic approaches have gained attention over the past decade, providing a modeling framework that enables less pessimistic analysis of real-time systems. Among the different proposed approaches, Markov chains have been shown effective for analyzing real-time systems, particularly in estimating the pending workload distribution and deadline miss probability. However, the state-of-the-art mainly considered discrete emission distributions without investigating the benefits of continuous ones. In this paper, we propose a method for analyzing the workload probability distribution and bounding the deadline miss probability for a task executing in a reservation-based server, where execution times are described by a Markov model with Gaussian emission distributions. The evaluation is performed for the timing behavior of a Kalman filter for Furuta pendulum control. Deadline miss probability bounds are derived with a workload accumulation scheme. The bounds are compared to 1) measured deadline miss ratios of tasks running under the Linux Constant Bandwidth Server with SCHED-DEADLINE, 2) estimates derived from a Markov Model with discrete-emission distributions (PROSIT), 3) simulation-based estimates, and 4) an estimate assuming independent execution times. The results suggest that the proposed method successfully upper bounds actual deadline miss probabilities. Compared to the discrete-emission counterpart, the computation time is independent of the range of the execution times under analysis, and resampling is not required.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
Deadline Miss Probability, Hidden Markov Model, Probabilistic Schedulability Analysis, Real-time systems, Computer operating systems, Continuous time systems, Hidden Markov models, Interactive computer systems, Probability distributions, Continuous emission, Emission distribution, Hidden-Markov models, Markov modeling, Probabilistic schedulability analyse, Probabilistics, Real - Time system, Real-time application, Schedulability analysis, Real time systems
National Category
Control Engineering
Identifiers
urn:nbn:se:mdh:diva-63914 (URN)10.1109/RTAS58335.2023.00009 (DOI)001017772500002 ()2-s2.0-85164535864 (Scopus ID)9798350321760 (ISBN)
Conference
Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS
Available from: 2023-07-26 Created: 2023-07-26 Last updated: 2023-12-04Bibliographically approved
Markovic, F., Roux, P., Bozhko, S., Papadopoulos, A. & Brandenburg, B. B. (2023). CTA: A Correlation-Tolerant Analysis of the Deadline-Failure Probability of Dependent Tasks. In: Proc. Real Time Syst. Symp.: . Paper presented at Proceedings - Real-Time Systems Symposium (pp. 317-330). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>CTA: A Correlation-Tolerant Analysis of the Deadline-Failure Probability of Dependent Tasks
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2023 (English)In: Proc. Real Time Syst. Symp., Institute of Electrical and Electronics Engineers Inc. , 2023, p. 317-330Conference paper, Published paper (Refereed)
Abstract [en]

Estimating the worst-case deadline failure probability (WCDFP) of a real-time task is notoriously difficult, primarily because a task's execution time typically depends on prior activations (i.e., history dependence) and the execution of other tasks (e.g., via shared inputs). Previous analyses have either assumed that execution times are probabilistically independent (which is unrealistic and unsafe), or relied on complex upper-bounding abstractions such as probabilistic worst-case execution time (pWCET), which mask dependencies with pessimism. Exploring an analytically novel direction, this paper proposes the first closed-form upper bound on WCDFP that accounts for dependent execution times. The proposed correlation-tolerant analysis (CTA), based on Cantelli's inequality, targets fixed-priority scheduling and requires only two basic summary statistics of each task's ground- truth execution time distribution: upper bounds on the mean and standard deviation (for any possible job-arrival sequence). Notably, CTA does not use pWCET, nor does it require the full execution-time distribution to be known. Core parts of the analysis have been verified with the Coq proof assistant. Empirical comparison with state-of-the-art WCDFP analyses reveals that CTA can yield significantly improved bounds (e.g., a lower WCDFP than any pWCET-based method for 70% of the workloads tested at 90% pWCET utilization and 60% average utilization). Beyond accuracy gains, the favorable results highlight the potential of the previously unexplored analytical direction underlying CTA.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
concentration inequality, probability theory, real-time systems, scheduling, Interactive computer systems, Theorem proving, Dependent tasks, Failure Probability, Probabilistics, Real - Time system, Real-time tasks, Time distribution, Upper Bound, Worst-case execution time, Real time systems
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-66151 (URN)10.1109/RTSS59052.2023.00035 (DOI)2-s2.0-85185346442 (Scopus ID)9798350328578 (ISBN)
Conference
Proceedings - Real-Time Systems Symposium
Available from: 2024-02-28 Created: 2024-02-28 Last updated: 2024-02-28Bibliographically approved
Leander, B., Johansson, B., Lindström, T., Holmgren, O., Nolte, T. & Papadopoulos, A. (2023). Dependability and Security Aspects of Network-Centric Control. 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 >>Dependability and Security Aspects of Network-Centric Control
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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]

Industrial automation and control systems are responsible for running our most important infrastructures, providing electricity and clean water, producing medicine and food, along with many other services and products we take for granted. The safe and secure operation of these systems is therefore of great importance.One of the emerging trends in industrial automation systems is the transition from static hierarchical controller-centric systems to flexible network-centric systems. This transition has a great impact on the characteristics of industrial automation systems. In this article we describe the network-centric design strategy for industrial automation systems and describe the impact on dependability and security aspects that this strategy brings, looking at both challenges and possibilities.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
Automation, Network security, Clean waters, Emerging trends, Flexible networks, Hierarchical controllers, Industrial automation and control systems, Industrial automation system, Network-centric controls, Network-centric design, Network-centric system, Security aspects, Hierarchical systems
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-64705 (URN)10.1109/ETFA54631.2023.10275344 (DOI)2-s2.0-85175480429 (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
Salman Shaik, M., Papadopoulos, A., Mubeen, S. & Nolte, T. (2023). Dispatching Deadline Constrained Jobs in Edge Computing 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 >>Dispatching Deadline Constrained Jobs in Edge Computing 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]

The edge computing paradigm extends the architectural space of real-time systems by bringing the capabilities of the cloud to the edge. Unlike cloud-native systems designed for mean response times, real-time industrial embedded systems are designed to control a single physical system, such as a manipulator arm or a mobile robot, that requires temporal predictability. We consider the problem of dispatching and scheduling of jobs with deadlines that can be offloaded to the edge and propose DAL, a deadline-aware load balancing and scheduling framework that leverages the availability of on-demand computing resources along with an on-arrival dispatching scheme to manage temporal requirements of such offloaded applications. The evaluation indicates that DAL can achieve reasonably good performance even when execution times, arrival times, and deadlines vary.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2023
Keywords
Edge computing, Embedded systems, Interactive computer systems, Manipulators, Architectural space, Computing paradigm, Computing system, Embedded-system, Mean response time, Native system, Physical systems, Real - Time system, Real- time, Real time systems
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-64690 (URN)10.1109/ETFA54631.2023.10275562 (DOI)2-s2.0-85175455753 (Scopus ID)9798350339918 (ISBN)
Conference
IEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Available from: 2023-11-13 Created: 2023-11-13 Last updated: 2023-11-13Bibliographically approved
Salman Shaik, M., Papadopoulos, A., Mubeen, S. & Nolte, T. (2023). Evaluating Dispatching and Scheduling Strategies for Firm Real-Time Jobs in Edge Computing. In: IECON Proc: . Paper presented at IECON Proceedings (Industrial Electronics Conference). IEEE Computer Society
Open this publication in new window or tab >>Evaluating Dispatching and Scheduling Strategies for Firm Real-Time Jobs in Edge Computing
2023 (English)In: IECON Proc, IEEE Computer Society , 2023Conference paper, Published paper (Refereed)
Abstract [en]

We consider the problem of on-arrival dispatching and scheduling jobs with stochastic execution times, inter-arrival times, and deadlines in multi-server fog and edge computing platforms. In terms of mean response times, it has been shown that size-based scheduling policies, when combined with dispatching policies such as join-shortest-queue, provide better performance over policies such as first-in-first-out. Since job sizes may not always be known apriori, prediction-based policies have been shown to perform reasonably well. However, little is known about the performance of prediction-based policies for jobs with firm deadlines. In this paper, we address this issue by considering the number of jobs that complete within their deadlines as a performance metric and investigate, using simulations, the performance of a prediction-based shortest-job-first scheduling policy for the considered metric and compare it against scheduling policies that prioritize based on deadlines (EDF) and arrival times (FIFO). The evaluation indicates that in under-loaded conditions, the prediction-based policy is outperformed by both FIFO and EDF policies. However, in overloaded scenarios, the prediction-based policy offers slightly better performance.

Place, publisher, year, edition, pages
IEEE Computer Society, 2023
Keywords
Forecasting, Stochastic systems, Edge computing, Inter-arrival time, Multiservers, Performance, Prediction-based, Real- time, Scheduling jobs, Scheduling policies, Scheduling strategies, Stochastics
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-65149 (URN)10.1109/IECON51785.2023.10312523 (DOI)2-s2.0-85179512797 (Scopus ID)9798350331820 (ISBN)
Conference
IECON Proceedings (Industrial Electronics Conference)
Available from: 2023-12-21 Created: 2023-12-21 Last updated: 2023-12-21Bibliographically approved
Al-Dulaimy, A., Ashjaei, S. M., Behnam, M., Nolte, T. & Papadopoulos, A. (2023). Fault Tolerance in Cloud Manufacturing: An Overview. In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol 495: . Paper presented at 13th International Conference on Mobile Computing, Applications, and Services, MobiCASE 2022, Messina, 17 November 2022 through 18 November 2022 (pp. 89-101). Springer Science and Business Media Deutschland GmbH
Open this publication in new window or tab >>Fault Tolerance in Cloud Manufacturing: An Overview
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2023 (English)In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol 495, Springer Science and Business Media Deutschland GmbH , 2023, p. 89-101Conference paper, Published paper (Refereed)
Abstract [en]

Utilizing edge and cloud computing to empower the profitability of manufacturing is drastically increasing in modern industries. As a result of that, several challenges have raised over the years that essentially require urgent attention. Among these, coping with different faults in edge and cloud computing and recovering from permanent and temporary faults became prominent issues to be solved. In this paper, we focus on the challenges of applying fault tolerance techniques on edge and cloud computing in the context of manufacturing and we investigate the current state of the proposed approaches by categorizing them into several groups. Moreover, we identify critical gaps in the research domain as open research directions. 

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH, 2023
Keywords
Cloud computing, Cloud manufacturing, CMfg, Edge computing, Fault tolerance, MaaS, Manufacturing as a Service, Reliability
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-63500 (URN)10.1007/978-3-031-31891-7_7 (DOI)2-s2.0-85161360896 (Scopus ID)9783031318900 (ISBN)
Conference
13th International Conference on Mobile Computing, Applications, and Services, MobiCASE 2022, Messina, 17 November 2022 through 18 November 2022
Available from: 2023-06-21 Created: 2023-06-21 Last updated: 2023-06-26Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-1364-8127

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