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  • 1.
    Bate, Iain
    et al.
    University of York.
    Poulding, Simon
    University of York.
    Call for Papers: Practical Aspects of Search-Based Software Engineering2009Ingår i: Software, practice & experience, ISSN 0038-0644, E-ISSN 1097-024X, Vol. 39, nr 9, s. 867-868Artikel i tidskrift (Övrigt vetenskapligt)
  • 2.
    Bate, Iain
    et al.
    University of York.
    Poulding, Simon
    University of York.
    Editorial for the special issue on search-based software engineering2011Ingår i: Software, practice & experience, ISSN 0038-0644, E-ISSN 1097-024X, Vol. 41, nr 5, s. 467-468Artikel i tidskrift (Övrigt vetenskapligt)
  • 3.
    Cederbladh, Johan
    et al.
    Mälardalens universitet, Akademin för innovation, design och teknik, Inbyggda system.
    Eramo, R.
    Department of Communication Science, University of Teramo, Teramo, Italy.
    Muttillo, V.
    Department of Political Science, University of Teramo, Teramo, Italy.
    Strandberg, P. E.
    Research and Development, Westermo Network Technologies AB, Västerås, Sweden.
    Experiences and challenges from developing cyber-physical systems in industry-academia collaboration2024Ingår i: Software, practice & experience, ISSN 0038-0644, E-ISSN 1097-024XArtikel i tidskrift (Refereegranskat)
    Abstract [en]

    Cyber-physical systems (CPSs) are increasing in developmental complexity. Several emerging technologies, such as Model-based engineering, DevOps, and Artificial intelligence, are expected to alleviate the associated complexity by introducing more advanced capabilities. The AIDOaRt research project investigates how the aforementioned technologies can assist in developing complex CPSs in various industrial use cases. In this paper, we discuss the experiences of industry and academia collaborating to improve the development of complex CPSs through the experiences in the research project. In particular, the paper presents the results of two working groups that examined the challenges of developing complex CPSs from an industrial and academic perspective when considering the previously mentioned technologies. We present five identified challenge areas from developing complex CPSs and discuss them from the perspective of industry and academia: data, modeling, requirements engineering, continuous software and system engineering, as well as intelligence and automation. Furthermore, we highlight practical experience in collaboration from the project via two explicit use cases and connect them to the challenge areas. Finally, we discuss some lessons learned through the collaborations, which might foster future collaborative efforts. 

  • 4.
    Faragardi, H. R.
    et al.
    University of Innsbruck, Innsbruck, Austria.
    Vahabi, Maryam
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Fotouhi, Hossein
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Nolte, Thomas
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Fahringer, T.
    University of Innsbruck, Innsbruck, Austria.
    An efficient placement of sinks and SDN controller nodes for optimizing the design cost of industrial IoT systems2018Ingår i: Software, practice & experience, ISSN 0038-0644, E-ISSN 1097-024X, Vol. 48, nr 10, s. 1893-1919Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Recently, a growing trend has emerged toward using Internet of Things (IoT) in the context of industrial systems, which is referred to as industrial IoT. To deal with the time-critical requirements of industrial applications, it is necessary to consider reliability and timeliness during the design of an industrial IoT system. Through the separation of the control plane and the data plane, software-defined networking provides control units (controllers) coexisting with sink nodes, efficiently coping with network dynamics during run-time. It is of paramount importance to select a proper number of these devices (i.e., software-defined networking controllers and sink nodes) and locate them wisely in a network to reduce deployment cost. In this paper, we optimize the type and location of sinks and controllers in the network, subject to reliability and timeliness as the prominent performance requirements in time-critical IoT systems through ensuring that each sensor node is covered by a certain number of sinks and controllers. We propose PACSA-MSCP, an algorithm hybridizing a parallel version of the max-min ant system with simulated annealing for multiple-sink/controller placement. We evaluate the proposed algorithm through extensive experiments. The performance is compared against several well-known methods, and it is shown that our approach outperforms those methods by lowering the total deployment cost by up to 19%. Moreover, the deviation from the optimal solution achieved by CPLEX is shown to be less than 2.7%.

  • 5.
    Faragardi, Hamid Reza
    et al.
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Dehnavi, Saed
    University of Tehran, Iran.
    Nolte, Thomas
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.
    Kargahi, Mehdi
    An energy-aware resource provisioning scheme for real-time applications in a cloud data center2018Ingår i: Software, practice & experience, ISSN 0038-0644, E-ISSN 1097-024X, Vol. 48, nr 10, s. 1734-1757Artikel i tidskrift (Refereegranskat)
  • 6.
    Nhan Vo, Van
    et al.
    International School, Duy Tan University, Vietnam.
    Nguyen, Gia Tri
    International School, Duy Tan University, Vietnam.
    So-In, Chakchai
    Khon Kaen University, Khon Kaen, Thailand.
    Tran, Hung
    Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system. Nguyen Tat Thanh University, Vietnam.
    Surasak, Sanguanpong
    Kasetsart University, Bangkok, Thailand.
    Secrecy Performance in the Internet of Things: Optimal Energy Harvesting Time Under Constraints of Sensors and Eavesdroppers2020Ingår i: Software, practice & experience, ISSN 0038-0644, E-ISSN 1097-024X, Vol. 25, nr 1, s. 193-210Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this paper, we investigate the physical layer security (PLS) performance for the Internet of Things (IoT), which is modeled as an IoT sensor network (ISN). The considered system consists of multiple power transfer stations (PTSs), multiple IoT sensor nodes (SNs), one legitimate fusion center (LFC) and multiple eavesdropping fusion centers (EFCs), which attempt to extract the transmitted information at SNs without an active attack. The SNs and the EFCs are equipped with a single antenna, while the LFC is equipped with multiple antennas. Specifically, the SNs harvest energy from the PTSs and then use the harvested energy to transmit the information to the LFC. In this research, the energy harvesting (EH) process is considered in the following two strategies: 1) the SN harvests energy from all PTSs, and 2) the SN harvests energy from the best PTS. To guarantee security for the considered system before the SN sends the packet, the SN’s power is controlled by a suitable power policy that is based on the channel state information (CSI), harvested energy, and security constraints. An algorithm for the nearly optimal EH time is implemented. Accordingly, the analytical expressions for the existence probability of secrecy capacity and secrecy outage probability (SOP) are derived by using the statistical characteristics of the signal-to-noise ratio (SNR). In addition, we analyze the secrecy performance for various system parameters, such as the location of system elements, the number of PTSs, and the number of EFCs. Finally, the results of Monte Carlo simulations are provided to confirm the correctness of our analysis and derivation.

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