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  • 1.
    Alawadi, Sadi
    et al.
    Blekinge Inst Technol, Dept Comp Sci, S-37179 Karlskrona, Sweden.;Univ Santiago de Compostela, Comp Graph & Data Engn COGRADE Res Grp, Santiago De Compostela 15705, Spain..
    Alkharabsheh, Khalid
    Al Balqa Appl Univ, Prince Abdullah bin Ghazi Fac Informat & Commun Te, Software Engn Dept, As Salt 19117, Jordan..
    Alkhabbas, Fahed
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Kebande, Victor R.
    Blekinge Inst Technol, Dept Comp Sci, S-37179 Karlskrona, Sweden..
    Awaysheh, Feras M.
    Univ Tartu, Inst Comp Sci, Delta Res Ctr, EE-51009 Tartu, Estonia..
    Palomba, Fabio
    Univ Salerno, Dept Comp Sci, I-84084 Fisciano, Italy..
    Awad, Mohammed
    Arab Amer Univ, Dept Comp Syst Engn, Jenin 00970, Palestine..
    FedCSD: A Federated Learning Based Approach for Code-Smell Detection2024Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 12, s. 44888-44904Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Software quality is critical, as low quality, or "Code smell," increases technical debt and maintenance costs. There is a timely need for a collaborative model that detects and manages code smells by learning from diverse and distributed data sources while respecting privacy and providing a scalable solution for continuously integrating new patterns and practices in code quality management. However, the current literature is still missing such capabilities. This paper addresses the previous challenges by proposing a Federated Learning Code Smell Detection (FedCSD) approach, specifically targeting "God Class," to enable organizations to train distributed ML models while safeguarding data privacy collaboratively. We conduct experiments using manually validated datasets to detect and analyze code smell scenarios to validate our approach. Experiment 1, a centralized training experiment, revealed varying accuracies across datasets, with dataset two achieving the lowest accuracy (92.30%) and datasets one and three achieving the highest (98.90% and 99.5%, respectively). Experiment 2, focusing on cross-evaluation, showed a significant drop in accuracy (lowest: 63.80%) when fewer smells were present in the training dataset, reflecting technical debt. Experiment 3 involved splitting the dataset across 10 companies, resulting in a global model accuracy of 98.34%, comparable to the centralized model's highest accuracy. The application of federated ML techniques demonstrates promising performance improvements in code-smell detection, benefiting both software developers and researchers.

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  • 2.
    Alawadi, Sadi
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Mera, David
    Centro Singular de Investigación en Tecnoloxías da Información (CiTIUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain.
    Fernandez-Delgado, Manuel
    Centro Singular de Investigación en Tecnoloxías da Información (CiTIUS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain.
    Alkhabbas, Fahed
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Olsson, Carl Magnus
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    A comparison of machine learning algorithms for forecasting indoor temperature in smart buildings2020Ingår i: Energy Systems, Springer Verlag, ISSN 1868-3967, E-ISSN 1868-3975, Vol. 13, s. 689-705Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The international community has largely recognized that the Earth's climate is changing. Mitigating its global effects requires international actions. The European Union (EU) is leading several initiatives focused on reducing the problems. Specifically, the Climate Action tries to both decrease EU greenhouse gas emissions and improve energy efficiency by reducing the amount of primary energy consumed, and it has pointed to the development of efficient building energy management systems as key. In traditional buildings, households are responsible for continuously monitoring and controlling the installed Heating, Ventilation, and Air Conditioning (HVAC) system. Unnecessary energy consumption might occur due to, for example, forgetting devices turned on, which overwhelms users due to the need to tune the devices manually. Nowadays, smart buildings are automating this process by automatically tuning HVAC systems according to user preferences in order to improve user satisfaction and optimize energy consumption. Towards achieving this goal, in this paper, we compare 36 Machine Learning algorithms that could be used to forecast indoor temperature in a smart building. More specifically, we run experiments using real data to compare their accuracy in terms of R-coefficient and Root Mean Squared Error and their performance in terms of Friedman rank. The results reveal that the ExtraTrees regressor has obtained the highest average accuracy (0.97%) and performance (0,058%) over all horizons.

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  • 3.
    Alkhabbas, Fahed
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    An Approach to Engineer and Realize Emergent Configurations in the Internet of Things2018Ingår i: Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings, ACM Digital Library, 2018, s. 448-449Konferensbidrag (Refereegranskat)
    Abstract [en]

    The Internet of Things (IoT) is a fast propagating technology that is expected to emerge in almost all aspects of our daily life. The IoT environment is well known for being dynamic and uncertain. Connected devices, and their software, can be discovered at runtime and might also become suddenly unavailable. The involvement of the human in the loop complicates more the scene. People's activities are stochastic and their needs are not always predictable. Therefore, coping with the dynamic IoT environment should be considered as a first class requirement when engineering IoT systems. A useful concept for supporting this effort is Emergent Configurations (ECs). An EC consists of a dynamic set of devices that cooperate temporarily to achieve a user goal. This PhD work aims to use the concept of ECs as a basis for a novel approach for realizing IoT systems. More specifically, this thesis aims at: (i) producing characterization models for IoT systems and ECs; (ii) proposing a concrete architecture and an approach for realizing ECs.

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  • 4.
    Alkhabbas, Fahed
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Realizing Emergent Configurations in the Internet of Things2020Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    The Internet of Things (IoT) is a fast-spreading technology that enables new types of services in several domains such as transportation, health, and building automation. To exploit the potential of the IoT effectively, several challenges have to be tackled, including the following ones that we study in this thesis. First, the proposed IoT visions provide a fragmented picture, leading to a lack of consensus about IoT systems and their constituents. To piece together the fragmented picture of IoT systems, we systematically identified their characteristics by analyzing existing taxonomies. More specifically, we identified seventeen characteristics of IoT systems, and grouped them into two categories, namely, elements and quality aspects of IoT systems. Moreover, we conducted a survey to identify the factors that drive the deployment decisions of IoT systems in practice. A second set of challenges concerns the environment of IoT systems that is often dynamic and uncertain. For instance, due to the mobility of users and things, the set of things available in users' environment might change suddenly. Similarly, the status of IoT systems’ deployment topologies (i.e., the deployment nodes and their interconnections) might change abruptly. Moreover, environmental conditions monitored and controlled through IoT devices, such as ambient temperature and oxygen levels, might fluctuate suddenly. The majority of existing approaches to engineer IoT systems rely on predefined processes to achieve users’ goals. Consequently, such systems have significant shortcomings in coping with dynamic and uncertain environments. To address these challenges, we used the concept of Emergent Configurations (ECs) to engineer goal-driven IoT systems. An EC is an IoT system that consists of a dynamic set of things that cooperate temporarily to achieve a user goal. To realize ECs, we proposed an abstract architectural approach, comprising an architecture and processes, as well as six novel approaches that refine the abstract approach. The developed approaches support users to achieve their goals seamlessly in arbitrary environments by enabling the dynamic formation, deployment, enactment, and self-adaptation of IoT systems. The approaches exploit different techniques and focus on different aspects of ECs. Moreover, to better support users in dynamic and uncertain environments, we investigated the automated configuration of those environments based on users' preferences. 

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  • 5.
    Alkhabbas, Fahed
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Towards Emergent Configurations in the Internet of Things2018Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    The Internet of Things (IoT) is a fast-spreading technology that enables new types of services in several domains, such as transportation, health, and building automation. To exploit the potential of the IoT effectively, several challenges have to be tackled including the following ones. First, the proposed IoT visions provide a fragmented picture, leading to a lack of consensus about IoT systems and their constituents. A second set of challenges concerns the environment of IoT systems that is often dynamic and uncertain, e.g. devices can appear and be discovered at runtime as well as become suddenly unavailable. Additionally, the in- volvement of human users complicates the scene as people’s activities are not always predictable . The majority of existing approaches to en- gineer IoT systems rely on predefined processes to achieve users’ goals. Consequently, such systems have significant shortcomings in coping with dynamic and uncertain environments. To piece together the fragmented picture of IoT systems, we sys- tematically identified their characteristics by analyzing and synthesizing existing taxonomies. To address the challenges related to the IoT envir- onment and the involvement of human users, we used the concept of Emergent Configurations (ECs) to engineer IoT systems. An EC consists of a dynamic set of devices that cooperate temporarily to achieve a user goal. To realize this vision, we proposed novel approaches that enable users to achieve their goals by supporting the automated formation, en- actment, and self-adaptation of IoT systems.

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  • 6.
    Alkhabbas, Fahed
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Alawadi, Sadi
    School of Information Technology, Halmstad University,Halmstad,Sweden.
    Ayyad, Majed
    Birzeit University,Department of Computer Science,Palestine.
    Spalazzese, Romina
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    ART4FL: An Agent-Based Architectural Approach for Trustworthy Federated Learning in the IoT2023Ingår i: 2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC), Institute of Electrical and Electronics Engineers (IEEE), 2023Konferensbidrag (Refereegranskat)
    Abstract [en]

    The integration of the Internet of Things (IoT) and Machine Learning (ML) technologies has opened up for the development of novel types of systems and services. Federated Learning (FL) has enabled the systems to collaboratively train their ML models while preserving the privacy of the data collected by their IoT devices and objects. Several FL frameworks have been developed, however, they do not enable FL in open, distributed, and heterogeneous IoT environments. Specifically, they do not support systems that collect similar data to dynamically discover each other, communicate, and negotiate about the training terms (e.g., accuracy, communication latency, and cost). Towards bridging this gap, we propose ART4FL, an end-to-end framework that enables FL in open IoT settings. The framework enables systems' users to configure agents that participate in FL on their behalf. Those agents negotiate and make commitments (i.e., contractual agreements) to dynamically form federations. To perform FL, the framework deploys the needed services dynamically, monitors the training rounds, and calculates agents' trust scores based on the established commitments. ART4FL exploits a blockchain network to maintain the trust scores, and it provides those scores to negotiating agents' during the federations' formation phase.

  • 7.
    Alkhabbas, Fahed
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Alawadi, Sadi
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Spalazzese, Romina
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Activity Recognition and User Preference Learning for Automated Configuration of IoT Environments2020Ingår i: IoT '20: Proceedings of the 10th International Conference on the Internet of Things, New York, United States: ACM Digital Library, 2020, s. 1-8, artikel-id 3Konferensbidrag (Refereegranskat)
    Abstract [en]

    Internet of Things (IoT) environments encompass different types of devices and objects that offer a wide range of services. The dynamicity and uncertainty of those environments, including the mobility of users and devices, make it hard to foresee at design time available devices, objects, and services. For the users to benefit from such environments, they should be proposed services that are relevant to the specific context and can be provided by available things. Moreover, environments should be configured automatically based on users' preferences. To address these challenges, we propose an approach that leverages Artificial Intelligence techniques to recognize users' activities and provides relevant services to support users to perform their activities. Moreover, our approach learns users' preferences and configures their environments accordingly by dynamically forming, enacting, and adapting goal-driven IoT systems. In this paper, we present a conceptual model, a multi-tier architecture, and processes of our approach. Moreover, we report about how we validated the feasibility and evaluated the scalability of the approach through a prototype that we developed and used.

  • 8.
    Alkhabbas, Fahed
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Alsadi, Mohammed
    Department of Computer Science, Norwegian University of Science and Technology, 7491 Trondheim, Norway.
    Alawadi, Sadi
    Department of Information Technology, Uppsala University, 75105 Uppsala, Sweden; Center for Applied Intelligent Systems Research, School of Information Technology, Halmstad University, 30118 Halmstad, Sweden.
    Awaysheh, Feras M
    Institute of Computer Science, Delta Research Centre, University of Tartu, 51009 Tartu, Estonia.
    Kebande, Victor R.
    Department of Computer Science (DBlekinge Institute of Technology, 37179 Karlskrona, Sweden.
    Moghaddam, Mahyar T
    The Maersk Mc-Kinney Moller Institute (MMMI), University of Southern Denmark, 5230 Odense, Denmark.
    ASSERT: A Blockchain-Based Architectural Approach for Engineering Secure Self-Adaptive IoT Systems.2022Ingår i: Sensors, E-ISSN 1424-8220, Vol. 22, nr 18, artikel-id 6842Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Internet of Things (IoT) systems are complex systems that can manage mission-critical, costly operations or the collection, storage, and processing of sensitive data. Therefore, security represents a primary concern that should be considered when engineering IoT systems. Additionally, several challenges need to be addressed, including the following ones. IoT systems' environments are dynamic and uncertain. For instance, IoT devices can be mobile or might run out of batteries, so they can become suddenly unavailable. To cope with such environments, IoT systems can be engineered as goal-driven and self-adaptive systems. A goal-driven IoT system is composed of a dynamic set of IoT devices and services that temporarily connect and cooperate to achieve a specific goal. Several approaches have been proposed to engineer goal-driven and self-adaptive IoT systems. However, none of the existing approaches enable goal-driven IoT systems to automatically detect security threats and autonomously adapt to mitigate them. Toward bridging these gaps, this paper proposes a distributed architectural Approach for engineering goal-driven IoT Systems that can autonomously SElf-adapt to secuRity Threats in their environments (ASSERT). ASSERT exploits techniques and adopts notions, such as agents, federated learning, feedback loops, and blockchain, for maintaining the systems' security and enhancing the trustworthiness of the adaptations they perform. The results of the experiments that we conducted to validate the approach's feasibility show that it performs and scales well when detecting security threats, performing autonomous security adaptations to mitigate the threats and enabling systems' constituents to learn about security threats in their environments collaboratively.

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  • 9.
    Alkhabbas, Fahed
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Ayyad, Majed
    Mihailescu, Radu-Casian
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    A Commitment-Based Approach to Realize Emergent Configurations in the Internet of Things2017Ingår i: Software Architecture Workshops (ICSAW), 2017 IEEE International Conference on, IEEE, 2017, s. 88-91Konferensbidrag (Refereegranskat)
    Abstract [en]

    The Internet of Things (IoT) involves intelligent, heterogeneous, autonomous and often distributed things which interact and collaborate to achieve common goals. A useful concept for supporting this effort is Emergent Configuration (EC), which consists of a dynamic set of things, with their functionalities and services, that cooperate temporarily to achieve a goal. In this paper we introduce a commitment-based approach that exploits the concept of commitments to realize ECs. More specifically, (i) we present a conceptual model for commitment-based ECs, (ii) we use the smart meeting room scenario to illustrate how ECs are realized via commitments.

  • 10.
    Alkhabbas, Fahed
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    De Sanctis, Martina
    Gran Sasso Sci Inst, Comp Sci Dept, Laquila, Italy..
    Bucchiarone, Antonio
    Fdn Bruno Kessler, Trento, Italy..
    Cicchetti, Antonio
    Mälardalen Univ, IDT Dept, Västerås, Sweden..
    Spalazzese, Romina
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Iovino, Ludovico
    Gran Sasso Sci Inst, Comp Sci Dept, Laquila, Italy..
    ROUTE: A Framework for Customizable Smart Mobility Planners2022Ingår i: IEEE 19TH INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE (ICSA 2022), Institute of Electrical and Electronics Engineers (IEEE), 2022, s. 169-179Konferensbidrag (Refereegranskat)
    Abstract [en]

    Multimodal journey planners are used worldwide to support travelers in planning and executing their journeys. Generated travel plans usually involve local mobility service providers, consider some travelers' preferences, and provide travelers information about the routes' current status and expected delays. However, those planners cannot fully consider the special situations of individual cities when providing travel planning services. Specifically, authorities of different cities might define customizable regulations or constraints of movements in the cities (e.g., due to construction works or pandemics). Moreover, with the transformation of traditional cities into smart cities, travel planners could leverage advanced monitoring features. Finally, most planners do not consider relevant information impacting travel plans, for instance, information that might be provided by travelers (e.g., a crowded square) or by mobility service providers (e.g., changing the timetable of a bus). To address the aforementioned shortcomings, in this paper, we propose ROUTE, a framework for customizable smart mobility planners that better serve the needs of travelers, local authorities, and mobility service providers in the dynamic ecosystem of smart cities. ROUTE is composed of an architecture, a process, and a prototype developed to validate the feasibility of the framework. Experiments' results show that the framework scales well in both centralized and distributed deployment settings.

  • 11.
    Alkhabbas, Fahed
    et al.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Martina, De Sanctis
    Spalazzese, Romina
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Bucchiarone, Antonio
    Davidsson, Paul
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Marconi, Annapaola
    Enacting Emergent Configurations in the IoT Through Domain Objects2018Ingår i: Proceedings of ICSOC 2018: Service-Oriented Computing, Springer, 2018, s. 279-294Konferensbidrag (Refereegranskat)
    Abstract [en]

    The Internet of Things (IoT) pervades more and more aspects of our lives and often involves many types of smart connected objects and devices. User’s IoT environment changes dynamically, e.g., due to the mobility of the user and devices. Users can fully benefit from the IoT only when they can effortlessly interact with it. To accomplish this in a dynamic and heterogenous environment, we make use of Emergent Configurations (ECs), which consist of a set of things that connect and cooperate temporarily through their functionalities, applications, and services, to achieve a user goal. In this paper, we: (i) present the IoT-FED architectural approach to enable the automated formation and enactment of ECs. IoT-FED exploits heterogeneous and independently developed things, IoT services, and applications which are modeled as Domain Objects (DOs), a service-based formalism. Additionally, we (ii) discuss the prototype we developed and the experiments run in our IoT lab, for validation purposes.

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  • 12.
    Alkhabbas, Fahed
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Murturi, Ilir
    Spalazzese, Romina
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Dustdar, Schahram
    A Goal driven Approach for Deploying Self-adaptive IoT Systems2020Ingår i: Proceedings: 2020 IEEE International Conference on Software Architecture (ICSA), Salvador, Brazil, 16-20 March 2020 / [ed] Lisa O’Conner, 2020, s. 146-156Konferensbidrag (Refereegranskat)
    Abstract [en]

    Engineering Internet of Things (IoT) systems is a challenging task partly due to the dynamicity and uncertainty of the environment including the involvement of the human in the loop. Users should be able to achieve their goals seamlessly in different environments, and IoT systems should be able to cope with dynamic changes. Several approaches have been proposed to enable the automated formation, enactment, and self-adaptation of goal-driven IoT systems. However, they do not address deployment issues. In this paper, we propose a goal-driven approach for deploying self-adaptive IoT systems in the Edge-Cloud continuum. Our approach supports the systems to cope with the dynamicity and uncertainty of the environment including changes in their deployment topologies, i.e., the deployment nodes and their interconnections. We describe the architecture and processes of the approach and the simulations that we conducted to validate its feasibility. The results of the simulations show that the approach scales well when generating and adapting the deployment topologies of goal-driven IoT systems in smart homes and smart buildings.

  • 13.
    Alkhabbas, Fahed
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Spalazzese, Romina
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Cerioli, Maura
    Leotta, Maurizio
    Reggio, Gianna
    On the Deployment of IoT Systems: An Industrial Survey2020Ingår i: 2020 IEEE International Conference on Software Architecture Companion (ICSA-C), 2020Konferensbidrag (Refereegranskat)
    Abstract [en]

    Internet of Things (IoT) systems are complex and multifaceted, and the design of their architectures needs to consider many aspects at a time. Design decisions concern, for instance, the modeling of software components and their interconnections, as well as where to deploy the components within the available hardware infrastructure in the Edge-Cloud continuum. A relevant and challenging task, in this context, is to identify optimal deployment models due to all the different aspects involved, such as extra-functional requirements of the system, heterogeneity of the hardware resources concerning their processing and storage capabilities, and constraints like legal issues and operational cost limits. To gain insights about the deployment decisions concerning IoT systems in practice, and the factors that influence those decisions, we report about an industrial survey we conducted with 66 IoT architects from 18 countries across the world. Each participant filled in a questionnaire that comprises 15 questions. By analyzing the collected data, we have two main findings: (i) architects rely on the Cloud more than the Edge for deploying the software components of IoT systems, in the majority of the IoT application domains; and (ii) the main factors driving deployment decisions are four: reliability, performance, security, and cost.

  • 14.
    Alkhabbas, Fahed
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Spalazzese, Romina
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    An Agent-based Approach to Realize Emergent Configurationsin the Internet of Things2020Ingår i: Electronics, E-ISSN 2079-9292, Vol. 9, nr 9, artikel-id 1347Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The Internet of Things (IoT) has enabled physical objects and devices, often referred to as things, to connect and communicate. This has opened up for the development of novel types of services that improve the quality of our daily lives. The dynamicity and uncertainty of IoT environments, including the mobility of users and devices, make it hard to foresee at design time available things and services. Further, users should be able to achieve their goals seamlessly in arbitrary environments. To address these challenges, we exploit Artificial Intelligence (AI) to engineer smart IoT systems that can achieve user goals and cope with the dynamicity and uncertainty of their environments. More specifically, the main contribution of this paper is an approach that leverages the notion of Belief-Desire-Intention agents and Machine Learning (ML) techniques to realize Emergent Configurations (ECs) in the IoT. An EC is an IoT system composed of a dynamic set of things that connect and cooperate temporarily to achieve a user goal. The approach enables the distributed formation, enactment, adaptation of ECs, and conflict resolution among them. We present a conceptual model of the entities of the approach, its underlying processes, and the guidelines for using it. Moreover, we report about the simulations conducted to validate the feasibility of the approach and evaluate its scalability. View Full-Text

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  • 15.
    Alkhabbas, Fahed
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Spalazzese, Romina
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Architecting Emergent Configurations in the Internet of Things2017Ingår i: Proceedings: 2017 IEEE International Conference on Software Architecture (ICSA), IEEE, 2017, s. 221-224Konferensbidrag (Refereegranskat)
    Abstract [en]

    The Internet of Things (IoT) has a great potential to change our lives. Billions of heterogeneous, distributed, intelligent, and sometimes mobile devices, will be connected and offer new types of applications and ways to interact. The dynamic environment of the IoT, the involvement of the human in the loop, and the runtime interactions among devices and applications, put additional requirements on the systems' architecture. In this paper, we use the Emergent Configurations (ECs) concept as a way to engineer IoT systems and propose an architecture for ECs. More specifically, we discuss (i) how connected devices and applications form ECs to achieve users' goals and (ii) how applications are run and adapted in response to runtime context changes including, e.g., the sudden unavailability of devices, by exploiting the Smart Meeting Room case.

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  • 16.
    Alkhabbas, Fahed
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Spalazzese, Romina
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Characterizing Internet of Things Systems through Taxonomies: A Systematic Mapping Study2019Ingår i: Internet of Things: Engineering Cyber Physical Human Systems, E-ISSN 2542-6605, Vol. 7, artikel-id 100084Artikel, forskningsöversikt (Refereegranskat)
    Abstract [en]

    During the last decade, a large number of different definitions and taxonomies of Internet of Things (IoT) systems have been proposed. This has resulted in a fragmented picture and a lack of consensus about IoT systems and their constituents. To provide a better understanding of this issue and a way forward, we have conducted a Systematic Mapping Study (SMS) of existing IoT System taxonomies. In addition, we propose a characterization of IoT systems synthesized from the existing taxonomies, which provides a more holistic view of IoT systems than previous taxonomies. It includes seventeen characteristics, divided into two groups: elements and quality aspects. Finally, by analyzing the results of the SMS, we draw future research directions.

  • 17.
    Alkhabbas, Fahed
    et al.
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Spalazzese, Romina
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    Davidsson, Paul
    Malmö universitet, Internet of Things and People (IOTAP). Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).
    ECo-IoT: An Architectural Approach for Realizing Emergent Configurations in the Internet of Things2018Ingår i: Software Architecture: Proceeding of 12th European Conference on Software Architecture, ECSA 2018, Springer, 2018, s. 86-102Konferensbidrag (Refereegranskat)
    Abstract [en]

    The rapid proliferation of the Internet of Things (IoT) is changing the way we live our everyday life and the society in general. New devices get connected to the Internet every day and, similarly, new IoT services and applications exploiting them are developed across a wide range of domains. The IoT environment typically is very dynamic, devices might suddenly become unavailable and new ones might appear. Similarly, users enter and/or leave the IoT environment while being interested in fulfilling their individual needs. These key aspects must be considered while designing and realizing IoT systems. In this paper we propose ECo-IoT, an architectural approach to enable the automated formation and adaptation of Emergent Configurations (ECs) in the IoT. An EC is formed by a set of things, with their services, functionalities, and applications, to realize a user goal. ECs are adapted in response to (un)foreseen context changes e.g., changes in available things or due to changing or evolving user goals. In the paper, we describe: (i) an architecture and a process for realizing ECs; and (ii) a prototype we implemented for (iii) the validation of ECo-IoT through an IoT scenario that we use throughout the paper.

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  • 18.
    Alkhabbas, Fahed
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Spalazzese, Romina
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Emergent Configurations in the Internet of Things as System of Systems2017Ingår i: Proceedings: 2017 IEEE/ACM Joint 5th International Workshop on Software Engineering for Systems-of-Systems and 11th Workshop on Distributed Software Development, Software Ecosystems and Systems-of-Systems (JSOS), IEEE, 2017, s. 70-71Konferensbidrag (Refereegranskat)
    Abstract [en]

    Systems of Systems (SoS) and the Internet of Things (IoT) have many common characteristics. For example, their constituents are heterogeneous, often autonomous, and distributed. Moreover, both IoT systems and SoS achieve their intended goals by means of the dynamic collaboration and coordination among their constituents. In this paper, by using the notion of Emergent Configurations (ECs) as a means to engineer IoT systems, we show how ECs in the IoT can be regarded both as systems and SoS by exploiting two scenarios.

  • 19.
    Alkhabbas, Fahed
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Spalazzese, Romina
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Human-Centric Emergent Configurations: Supporting the User Through Self-configuring IoT Systems2021Ingår i: Advances in Neuroergonomics and Cognitive Engineering: Proceedings of the AHFE 2021 Virtual Conferences on Neuroergonomics and Cognitive Engineering, Industrial Cognitive Ergonomics and Engineering Psychology, and Cognitive Computing and Internet of Things, July 25-29, 2021, USA / [ed] Hasan Ayaz; Umer Asgher; Lucas Paletta, Springer, 2021, s. 411-418Konferensbidrag (Refereegranskat)
    Abstract [en]

    The Internet of Things (IoT) is revolutionizing our environments with novel types of services and applications by exploiting the large number of diverse connected things. One of the main challenges in the IoT is to engineer systems to support human users to achieve their goals in dynamic and uncertain environments. For instance, the mobility of both users and devices makes it infeasible to always foresee the available things in the users’ current environments. Moreover, users’ activities and/or goals might change suddenly. To support users in such environments, we developed an initial approach that exploits the notion of Emergent Configurations (ECs) and mixed initiative techniques to engineer self-configuring IoT systems. An EC is a goal-driven IoT system composed of a dynamic set of temporarily connecting and cooperating things. ECs are more flexible and usable than IoT systems whose constituents and interfaces are fully specified at design time

  • 20.
    Alkhabbas, Fahed
    et al.
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Spalazzese, Romina
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö högskola, Fakulteten för teknik och samhälle (TS). Malmö högskola, Internet of Things and People (IOTAP).
    IoT-based Systems of Systems2016Ingår i: Proceedings of the 2nd edition of Swedish Workshop on the Engineering of Systems of Systems (SWESOS 2016), Chalmers , 2016, s. 34-37Konferensbidrag (Refereegranskat)
    Abstract [en]

    Systems of Systems(SoS) and theInternet of Things(IoT)have many common characteristics. For example, their constituents are heterogeneous, autonomous and often distributed. Moreover, both IoT and SoS achieve intended goals by means of the highly dynamic cooperation among their constituents. In this paper we study the relation between IoT and SoS. We discuss the characteristics of both concepts and highlight common aspects. Furthermore, we introduce the conceptSystem of Emergent Configurations (SoECs) to describe IoT-based SoS.

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  • 21.
    Fakhouri, Hussam N
    et al.
    Department of Data Science and Artificial Intelligence, The University of Petra, Amman, Jordanc.
    Alawadi, Sadi
    Department of Computer Science, Blekinge Institute of Technology, Karlskrona, Sweden; Computer Graphics and Data Engineering (COGRADE) Research Group, University of Santiago de Compostela, Santiago de Compostela, Spain.
    Awaysheh, Feras M
    Institute of Computer Science, Delta Research Centre, University of Tartu, Tartu, Estonia.
    Alkhabbas, Fahed
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Zraqou, Jamal
    Virtual and Augment Reality Department, Faculty of Information Technology, University of Petra, Amman, Jordan.
    A cognitive deep learning approach for medical image processing2024Ingår i: Scientific Reports, E-ISSN 2045-2322, Vol. 14, nr 1, artikel-id 4539Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In ophthalmic diagnostics, achieving precise segmentation of retinal blood vessels is a critical yet challenging task, primarily due to the complex nature of retinal images. The intricacies of these images often hinder the accuracy and efficiency of segmentation processes. To overcome these challenges, we introduce the cognitive DL retinal blood vessel segmentation (CoDLRBVS), a novel hybrid model that synergistically combines the deep learning capabilities of the U-Net architecture with a suite of advanced image processing techniques. This model uniquely integrates a preprocessing phase using a matched filter (MF) for feature enhancement and a post-processing phase employing morphological techniques (MT) for refining the segmentation output. Also, the model incorporates multi-scale line detection and scale space methods to enhance its segmentation capabilities. Hence, CoDLRBVS leverages the strengths of these combined approaches within the cognitive computing framework, endowing the system with human-like adaptability and reasoning. This strategic integration enables the model to emphasize blood vessels, accurately segment effectively, and proficiently detect vessels of varying sizes. CoDLRBVS achieves a notable mean accuracy of 96.7%, precision of 96.9%, sensitivity of 99.3%, and specificity of 80.4% across all of the studied datasets, including DRIVE, STARE, HRF, retinal blood vessel and Chase-DB1. CoDLRBVS has been compared with different models, and the resulting metrics surpass the compared models and establish a new benchmark in retinal vessel segmentation. The success of CoDLRBVS underscores its significant potential in advancing medical image processing, particularly in the realm of retinal blood vessel segmentation.

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  • 22.
    Spalazzese, Romina
    et al.
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    De Sanctis, Martina
    Gran Sasso Science Institute (GSSI), L’Aquila, Italy.
    Alkhabbas, Fahed
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Davidsson, Paul
    Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT). Malmö universitet, Internet of Things and People (IOTAP).
    Shaping IoT Systems Together: The User-System Mixed-Initiative Paradigm and Its Challenges2023Ingår i: Software Architecture: 17th European Conference, ECSA 2023, Istanbul, Turkey, September 18–22, 2023, Proceedings / [ed] Bedir Tekinerdogan, Catia Trubiani, Chouki Tibermacine, Patrizia Scandurra, Carlos E. Cuesta, Springer, 2023, s. 221-229Konferensbidrag (Refereegranskat)
    Abstract [en]

    Internet of Things (IoT) systems are often complex and have to deal with many challenges at the same time, both from a human and technical perspective. In this vision paper, we (i) describe IoT-Together , the Mixed-initiative Paradigm that we devise for IoT user-system collaboration and (ii) critically analyze related architectural challenges.

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