mdh.sePublications
Change search
Refine search result
1 - 10 of 10
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Causevic, Aida
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Vahabi, Maryam
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Enabling Safe, Secure and Reliable Data Communication in IoT AAL Healthcare Applications2017In: Medicinteknikdagarna 2017 MTD 2017, 2017Conference paper (Refereed)
  • 2.
    Faragardi, H. R.
    et al.
    University of Innsbruck, Innsbruck, Austria.
    Vahabi, Maryam
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fahringer, T.
    University of Innsbruck, Innsbruck, Austria.
    An efficient placement of sinks and SDN controller nodes for optimizing the design cost of industrial IoT systems2018In: Software, practice & experience, ISSN 0038-0644, E-ISSN 1097-024X, Vol. 48, no 10, p. 1893-1919Article in journal (Refereed)
    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%.

  • 3.
    Fotouhi, Hossein
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Vahabi, Maryam
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Rabet, Iliar
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Alves, Mário
    Politecnico do Porto, ISEP/IPP, Porto, Portugal.
    MobiFog: Mobility Management Framework for Fog-assisted IoT Networks2019In: IEEE Global Conference on Internet of Things GCIoT'19, 2019Conference paper (Refereed)
    Abstract [en]

    Mobility is becoming a challenging issue in upcoming IoT applications, where it is crucial to employ mobile entities. Patients with sensors attached to their body in health monitoring application, AGVs in industrial monitoring and factory automation applications, cars with several sensing devices in vehicular applications are a few examples of use cases with the need for mobile nodes. In parallel, Fog computing has revolutionized network architecture, while enabling local processing of measurements, and reducing bandwidth overhead, which results in a more reliable system and real-time support. However, mobility management is a missing framework within the mobile IoT networks with Fog computing architecture. This paper provides a simple and generic seamless handoff model, dubbed as MobiFog, where it addresses the handoff mechanism with zero delay, while providing high reliability.

  • 4.
    Fotouhi, Hossein
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Vahabi, Maryam
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tomasic, Ivan
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Petrovic, Nikola
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. ES (Embedded Systems).
    IPv6 connectivity in eHealth IoT networks2018In: Medicinteknikdagarna 2018 MTD 2018, Umeå, Sweden, 2018Conference paper (Refereed)
  • 5.
    Gardasevic, Gordana
    et al.
    University of Banja Luka, Bosnia-Herzegovina.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tomasic, Ivan
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Vahabi, Maryam
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Heterogeneous IoT-based Architecture for Remote Monitoring of Physiological and Environmental Parameters2018In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Volume 225, 2018, p. 48-53Conference paper (Refereed)
    Abstract [en]

    A heterogeneous Internet of Things (IoT) architecture for remote health monitoring (RHM) is proposed, that employs Bluetooth and IEEE 802.15.4 wireless connectivity. The RHM system encompasses Shimmer physiological sensors with Bluetooth radio, and OpenMote environmental sensors with IEEE 802.15.4 radio. This system architecture collects measurements in a relational database in a local server to implement a Fog node for fast data analysis as well as in a remote server in the Cloud. 

  • 6.
    Rabet, Iliar
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Vahabi, Maryam
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Particle Filter for Handoff Prediction in SDN-based IoT Networks2020Conference paper (Refereed)
    Abstract [en]

    Standard implementation of RPL protocol has struggled to limit the impact of mobility on the throughput of the IoT network. Handoff process is of great importance to optimize the trade-off between the control overhead (for maintaining the network topology), and the delay, caused by nodes mobility. In this work, We have proposed a method for predicting future handoffs through fusion of RSSI value and Inertial Measurement Unit (IMU) information using particle filter, which is known for accuracy albeit it needs higher computation capacity. The provided analytical model indicates lower network interruption with the proposed method.

  • 7.
    Vahabi, Maryam
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Heterogeneous network for health monitoring applications2017In: Medicinteknikdagarna 2017 MTD 2017, 2017Conference paper (Refereed)
  • 8.
    Vahabi, Maryam
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Faragardi, H. R.
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    An analytical model for deploying mobile sinks in industrial Internet of Things2018In: 2018 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2018, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 155-160Conference paper (Refereed)
    Abstract [en]

    Nowadays, the Industrial Internet of Things (IIoT) has the potential to be implemented in factories and supply chains to improve manufacturing efficiency. It is becoming more common to use mobile robots in such factories for further improvements. Adding data collection capability to the mobile robots would realize the mobile sink deployment in future factories. As it is important to reduce the deployment cost, we are aiming at a network with minimum number of mobile sinks while ensuring network reliability and timeliness. In this paper, we analytically model a given trajectory for the motion of mobile sinks and the routing of mobile sinks along the trajectory in an IIoT system. We introduce an optimization problem in the form of Integer Linear Programming (ILP) to specify the minimum number of required mobile sinks to reduce deployment cost of an IIoT system, and also to identify the routing of multiple mobile sinks along a given trajectory. The proposed ILP model can be solved by several existing off-the-shelf ILP-solvers. 

  • 9.
    Vahabi, Maryam
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    FIREWORK: Fog orchestration for secure IoT networks2019In: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 284, 2019, p. 311-317Conference paper (Refereed)
    Abstract [en]

    Recent advances in Internet of Things (IoT) connectivity have made IoT devices prone to Cyber attacks. Moreover, vendors are eager to provide autonomous and open source device, which in turn adds more security threat to the system. In this paper, we consider network traffic attack, and provide a Fog-assisted solution, dubbed as FIRE- WORK, that reduces risk of security attacks by periodically monitor- ing network traffic, and applying traffic isolation techniques to overcome network congestion and performance degradation.

  • 10.
    Vahabi, Maryam
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Evaluating a Remote Health Monitoring Application Powered by Bluetooth2019In: 11th International Conference on e-Health e-Health'19, 2019, p. 67-74-Conference paper (Refereed)
    Abstract [en]

    It has become widely accepted that the Internet of Things (IoT) devices and technologies are the key enablers for many emerging applications including remote health monitoring. Various physiological sensing devices have been designed and equipped with different radio technologies. The choice of radio hardware plays an important role on the overall performance of the system since it imposes some limitations on the delivered quality of service. Hence, it is critical to properly evaluate the embedded radio technology based on the application requirements. In this paper, we perform extensive experiments on Shimmer physiological sensors that is one of the leading providers of wearable wireless sensor products powered by Bluetooth classic radio. Shimmer sensors are designed and used for monitoring various human health information such as temperature, heart rate, movement, etc. We review and investigate different scenarios in which Shimmer devices are used by medical practitioners to monitor the ECG signal and the movement of a human. This study shows that the Shimmer device can provide reliable data delivery by using a specific configuration. For instance, employing a maximum number of seven Shimmer devices attached on a body at home environment within the range of at most 5 m and with the sampling rate of 512 Hz would result in a reasonable quality of service, while varying these parameters may degrade the overall performance. Mobility of human body, noisy environment, and higher packet transmission rates are some examples that will reduce the system quality. © Copyright 2019 IADIS Press All rights reserved.

1 - 10 of 10
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf