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  • 1.
    Krug, Silvia
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    MatLab Functions for Cost Estimation of IoT Data Transfers2018Data set
    Abstract [en]

    This zip folder contains the MatLab code enabling analytical cost estimation of various communication technologies suitable for the IoT.

  • 2.
    Krug, Silvia
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Bader, Sebastian
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Oelmann, Bengt
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    O'Nils, Mattias
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Suitability of Communication Technologies for Harvester-Powered IoT-Nodes2019In: IEEE International Workshop on Factory Communication Systems - Proceedings, WFCS, Institute of Electrical and Electronics Engineers (IEEE), 2019, article id 8758042Conference paper (Refereed)
    Abstract [en]

    The Internet of Things introduces Internet connectivity to things and objects in the physical world and thus enables them to communicate with other nodes via the Internet directly. This enables new applications that for example allow seamless process monitoring and control in industrial environments. One core requirement is that the nodes involved in the network have a long system lifetime, despite limited access to the power grid and potentially difficult propagation conditions. Energy harvesting can provide the required energy for this long lifetime if the node is able to send the data based on the available energy budget. In this paper, we therefore analyze and evaluate which common IoT communication technologies are suitable for nodes powered by energy harvesters. The comparison includes three different constraints from different energy sources and harvesting technologies besides several communication technologies. Besides identifying possible technologies in general, we evaluate the impact of duty-cycling and different data sizes. The results in this paper give a road map for combining energy harvesting technology with IoT communication technology to design industrial sensor nodes. 

  • 3.
    Krug, Silvia
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    O'Nils, Mattias
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    IoT Communication Introduced Limitations for High Sampling Rate Applications2018In: GI/ITG KuVS Fachgespräch Sensornetze 13. & 14. September 2018, Braunschweig : Technical Report, 2018Conference paper (Refereed)
    Abstract [en]

    Networking solutions for the Internet of Things aretypically designed for applications that require low data rates andfeature rare transmission events. The initial assumption leads to asystem design towards minimal data transfers and packet sizes.However, this can become a challenge, if applications requiredifferent traffic patterns or cooperative interaction betweendevices. Applications requiring a high sampling rate to capturethe desired phenomenon produce larger amounts of data thatneed to be transported. In this paper, we present a studyhighlighting some of the challenging aspects for such applicationsand how the choice of communication technology can limit bothapplication behavior and network structure.

  • 4.
    Krug, Silvia
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    O'Nils, Mattias
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Modeling and Comparison of Delay and Energy Cost of IoT Data Transfers2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 58654-58675Article in journal (Refereed)
    Abstract [en]

    Communication is often considered as the most costly component of a wireless sensor node. As a result, a variety of technologies and protocols aim to reduce the energy consumption for the communication especially in the Internet of Things context. In order to select the best suitable technology for a given use case, a tool that allows the comparison of these options is needed. The goal of this paper is to introduce a new modular modeling framework that enables a comparison of various technologies based on analytical calculations. We chose to model the cost for a single data transfer of arbitrary application data amounts in order to provide flexibility regarding the data amount and traffic patterns. The modeling approach covers the stack traversal of application data and thus in comparison to other approaches includes the required protocol overhead directly. By applying our models to different data amounts, we are able to show tradeoffs between various technologies and enable comparisons for different scenarios. In addition, our results reveal the impact of design decisions that can help to identify future development challenges.

  • 5.
    Krug, Silvia
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Shallari, Irida
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    O'Nils, Mattias
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    A Case Study on Energy Overhead of Different IoT Network Stacks2019In: 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), IEEE, 2019, p. 528-529Conference paper (Refereed)
    Abstract [en]

    Due to the limited energy budget for sensor nodes in the Internet of Things (IoT), it is crucial to develop energy efficient communications amongst others. This need leads to the development of various energy-efficient protocols that consider different aspects of the energy status of a node. However, a single protocol covers only one part of the whole stack and savings on one level might not be as efficient for the overall system, if other levels are considered as well. In this paper, we analyze the energy required for an end device to maintain connectivity to the network as well as perform application specific tasks. By integrating the complete stack perspective, we build a more holistic view on the energy consumption and overhead for a wireless sensor node. For better understanding, we compare three different stack variants in a base scenario and add an extended study to evaluate the impact of retransmissions as a robustness mechanism. Our results show, that the overhead introduced by the complete stack has an significant impact on the nodes energy consumption especially if retransmissions are required.

  • 6.
    Shallari, Irida
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Krug, Silvia
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    O'Nils, Mattias
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Architectural evaluation of node: server partitioning for people counting2018In: ACM International Conference Proceeding Series, New York: ACM Digital Library, 2018, article id Article No. 1Conference paper (Refereed)
    Abstract [en]

    The Internet of Things has changed the range of applications for cameras requiring them to be easily deployed for a variety of scenarios indoor and outdoor, while achieving high performance in processing. As a result, future projections emphasise the need for battery operated smart cameras, capable of complex image processing tasks that also communicate within one another, and the server. Based on these considerations, we evaluate in-node and node – server configurations of image processing tasks to provide an insight of how tasks partitioning affects the overall energy consumption. The two main energy components taken in consideration for their influence in the total energy consumption are processing and communication energy. The results from the people counting scenario proved that processing background modelling, subtraction and segmentation in-node while transferring the remaining tasks to the server results in the most energy efficient configuration, optimising both processing and communication energy. In addition, the inclusion of data reduction techniques such as data aggregation and compression not always resulted in lower energy consumption as generally assumed, and the final optimal partition did not include data reduction.

  • 7.
    Shallari, Irida
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Krug, Silvia
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    O'Nils, Mattias
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Communication and Computation Inter-Effects in People Counting Using Intelligence PartitioningManuscript (preprint) (Other academic)
  • 8.
    Taami, Tania
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Krug, Silvia
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    O'Nils, Mattias
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Experimental Characterization of Latency in Distributed IoT Systems with Cloud Fog Offloading2019In: IEEE International Workshop on Factory Communication Systems - Proceedings, WFCS, Institute of Electrical and Electronics Engineers (IEEE), 2019, article id 8757960Conference paper (Refereed)
    Abstract [en]

    The Internet of Things (IoT) enables users to gather and analyze data from a large number of devices. Knowledge obtained by these systems is valuable in order to understand, control, and enhance the monitored process. The mass of information to process leads however to new challenges related to required resources for both data processing and data transportation. Two critical metrics are latency and consumed energy to complete a given task. Both metrics might be exceed if all processing is done locally at the sensor device level. Cloud and Fog computing concepts can help to mitigate this effect. However, using such offloading concepts add complexity and overhead to the system. In this paper, we study the latency for processing and communication tasks in a distributed IoT systems with respect to cloud or fog offloading and derive characteristic cost functions for the studied tasks. Our results give valuable insights into the tradeoffs and constraint within our example scenario. The developed characterization methodology can however be applied to any kind of IoT system and thus allowing more general analysis. 

  • 9.
    Vilar, Cristian
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Thörnberg, Benny
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Krug, Silvia
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Evaluation of embedded camera systems for autonomous wheelchairs2019In: VEHITS 2019 - Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems, SciTePress , 2019, p. 76-85Conference paper (Refereed)
    Abstract [en]

    Autonomously driving Power Wheelchairs (PWCs) are valuable tools to enhance the life quality of their users. In order to enable truly autonomous PWCs, camera systems are essential. Image processing enables the development of applications for both autonomous driving and obstacle avoidance. This paper explores the challenges that arise when selecting a suitable embedded camera system for these applications. Our analysis is based on a comparison of two well-known camera principles, Stereo-Cameras (STCs) and Time-of-Flight (ToF) cameras, using the standard deviation of the ground plane at various lighting conditions as a key quality measure. In addition, we also consider other metrics related to both the image processing task and the embedded system constraints. We believe that this assessment is valuable when choosing between using STC or ToF cameras for PWCs.

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