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  • 1.
    Ahmad, Waqas
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    Ghafoor, Mubeen
    COMSATS University Islamabad, Pakistan.
    Tariq, Syed Ali
    COMSATS University Islamabad, Pakistan.
    Hassan, Ali
    COMSATS University Islamabad, Pakistan.
    Sjöström, Mårten
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    Olsson, Roger
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    Computationally Efficient Light Field Image Compression Using a Multiview HEVC Framework2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 143002-143014, article id 8853251Article in journal (Refereed)
    Abstract [en]

    The acquisition of the spatial and angular information of a scene using light eld (LF) technologies supplement a wide range of post-processing applications, such as scene reconstruction, refocusing, virtual view synthesis, and so forth. The additional angular information possessed by LF data increases the size of the overall data captured while offering the same spatial resolution. The main contributor to the size of captured data (i.e., angular information) contains a high correlation that is exploited by state-of-the-art video encoders by treating the LF as a pseudo video sequence (PVS). The interpretation of LF as a single PVS restricts the encoding scheme to only utilize a single-dimensional angular correlation present in the LF data. In this paper, we present an LF compression framework that efciently exploits the spatial and angular correlation using a multiview extension of high-efciency video coding (MV-HEVC). The input LF views are converted into multiple PVSs and are organized hierarchically. The rate-allocation scheme takes into account the assigned organization of frames and distributes quality/bits among them accordingly. Subsequently, the reference picture selection scheme prioritizes the reference frames based on the assigned quality. The proposed compression scheme is evaluated by following the common test conditions set by JPEG Pleno. The proposed scheme performs 0.75 dB better compared to state-of-the-art compression schemes and 2.5 dB better compared to the x265-based JPEG Pleno anchor scheme. Moreover, an optimized motionsearch scheme is proposed in the framework that reduces the computational complexity (in terms of the sum of absolute difference [SAD] computations) of motion estimation by up to 87% with a negligible loss in visual quality (approximately 0.05 dB).

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  • 2.
    Ansari, Rafay Iqbal
    et al.
    Frederick University, Nicosia, Cyprus.
    Pervaiz, Haris
    Lancaster University, UK.
    Chrysostomou, Chrysostomos
    Frederick University, Nicosia, Cyprus.
    Hassan, Syed Ali
    National University of Sciences and Technology (NUST), Pakistan.
    Mahmood, Aamir
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    Control-Data Separation Architecture for Dual-Band mmWave Networks: A New Dimension to Spectrum Management2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 34925-34937, article id 8663278Article in journal (Refereed)
    Abstract [en]

    The exponential growth in global mobile data traffic, especially with regards to the massive deployment of devices envisioned for the fifth generation (5G) mobile networks, has given impetus to exploring new spectrum opportunities to support the new traffic demands. The millimeter wave (mmWave) frequency band is considered as a potential candidate for alleviating the spectrum scarcity. Moreover, the concept of multi-tier networks has gained popularity, especially for dense network environments. In this article, we deviate from the conventional multi-tier networks and employ the concept of control-data separation architecture (CDSA), which comprises of a control base station (CBS) overlaying the data base station (DBS). We assume that the CBS operates on the sub-6 GHz single band, while the DBS possesses a dual-band mmWave capability, i.e., 26 GHz unlicensed band and 60 GHz licensed band. We formulate a multi-objective optimization (MOO) problem, which jointly optimizes conflicting objectives: the spectral efficiency (SE) and the energy efficiency (EE). The unique aspect of this work includes the analysis of a joint radio resource allocation algorithm based on Lagrangian Dual Decomposition (LDD) and we compare the proposed algorithm with the maximal-rate (maxRx), dynamic sub-carrier allocation (DSA) and joint power and rate adaptation (JPRA) algorithms to show the performance gains achieved by the proposed algorithm.

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  • 3.
    Aurangzeb, Khursheed
    et al.
    King Saud Univ, Riyadh, Saudi Arabia; COMSATS Inst Informat Technol, Attack, Pakistan.
    Alhussein, Musaed
    King Saud Univ, Riyadh, Saudi Arabia.
    O'Nils, Mattias
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Analysis of Binary Image Coding Methods for Outdoor Applications of Wireless Vision sensor Networks2018In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 16932-16941Article in journal (Refereed)
    Abstract [en]

    The processing of images at the vision sensor nodes (VSN) requires a high computation power and their transmission requires a large communication bandwidth. The energy budget is limited in outdoor applications of wireless vision sensor networks (WVSN). This means that both the processing of images at the VSN and the communication to server must be energy efficient. The wireless communication of uncompressed data consumes huge amounts of energy. Data compression methods are efficient in reducing data in images and can be used for the reduction in transmission energy. We have evaluated seven binary image coding techniques. Our evaluation is based on the processing complexity and energy consumption of the compression methods on the embedded platforms. The focus is to come up with a binary image coding method, which has good compression efficiency and short processing time. An image coding method with such attributes will result in reduced total energy requirement of the node. We have used both statistically generated images and real captured images, in our experiments. Based on our results, we conclude that International Telegraph and Telephone Consultative Committee Group 4, gzip_pack and JPEG-LS are suitable coding methods for the outdoor applications of WVSNs.

  • 4.
    Aurangzeb, Khursheed
    et al.
    Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.
    Alhussein, Musaed
    Computer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia.
    O'Nils, Mattias
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Data Reduction Using Change Coding for Remote Applications of wireless Visual Sensor Networks2018In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 37738-37747Article in journal (Refereed)
    Abstract [en]

    The data reduction capability of image compression schemes is limited by the underlying compression technique. For applications with minor changes between consecutive frames, change coding can be used to further reduce the data. We explored the efficiency of change coding for data reduction in a wireless visual sensor network (WVSN). This paper presents an analysis of the compression efficiency of change coding for a variety of changes, such as different shapes, sizes, and locations of white objects in adjacent sets of frames. Compressing change frame provides a better performance compared with compressing the original frames for up to 95% changes in the number of objects in adjacent frames. Due to illumination noise, the size of the objects increases at its boundaries, which negatively affects the performance of change coding. We experimentally proved that the negative impact of illumination noise could be reduced by applying morphology on the change frame. Communication energy consumption of the VSN is dependent on the data that are transmitted to the server. Our results show that the communication energy consumption of the VSN can be reduced by 27%, 29%, and 46% by applying change coding in combination with JBIG2, Group4, and Gzip_pack, respectively. The findings presented in this paper will aid researchers in enhancing the compression potential of image coding schemes in the energy-constrained applications of WVSNs.

  • 5.
    Bakar, Muhammad Abu
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Alam, Farhan Muhammad
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Bertilsson, Kent
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Modeling and Characterization of Series Connected Hybrid Transformers for Low-Profile Power Converters2020In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 53293-53306Article in journal (Refereed)
    Abstract [en]

    Compact and low profile power converters are the main business of today's power industry. A significant volume of a power converter is occupied by the power transformer. This article proposes a unique solution that would make the power converters low profile. Instead of designing a power converter by using a single bulky transformer, the solution proposed is to split the main bulky transformer into a number of low profile transformers. This not only reduces the total weight and volume of the converter but also the total transformer losses. The use of more than one transformer in series reduces the applied voltage on the transformers, which minimizes the required turns ratio and decreases the stress on the secondary rectifiers and filter elements. Moreover, the decrease in the applied voltage reduces the proportional loss per transformer and makes it possible to design a hybrid transformer by combining Litz wire and traces of a printed circuit board. The reduced copper loss and lower heat dissipation per transformer simplify thermal management. An analytical comparison is made between the utilization of a single transformer or a number of transformers. The procedure of splitting a volume of a single transformer into a number of small transformers has been comprehensively discussed. The idea is investigated both experimentally and in computer simulation for an example application of a phase shifted full bridge dc-dc converter. The converter is characterized up to a load power of 2.2 kW at Vin = 400 Vdc and Vout = 48 Vdc. To make the approach more practical, the transformers are modeled using the traditional analytical method. The design of the example application using the split transformer approach reduces the total transformer weight by 45%, compared to the traditional approachwith a single transformer. The converter also shows good performance with a maximum efficiency of 96%.

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  • 6.
    Grimaldi, Simone
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    Mahmood, Aamir
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    Real-time Interference Identification via Supervised Learning: Embedding Coexistence Awareness in IoT Devices2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 835-850Article in journal (Refereed)
    Abstract [en]

    Energy sampling-based interference detection and identification (IDI) methods collide with the limitations of commercial off-the-shelf (COTS) IoT hardware. Moreover, long sensing times, complexity and inability to track concurrent interference strongly inhibit their applicability in most IoT deployments. Motivated by the increasing need for on-device IDI for wireless coexistence, we develop a lightweight and efficient method targeting interference identification already at the level of single interference bursts. Our method exploits real-time extraction of envelope and model-aided spectral features, specifically designed considering the physical properties of signals captured with COTS hardware. We adopt manifold supervised-learning (SL) classifiers ensuring suitable performance and complexity trade-off for IoT platforms with different computational capabilities. The proposed IDI method is capable of real-time identification of IEEE 802.11b/g/n, 802.15.4, 802.15.1 and Bluetooth Low Energy wireless standards, enabling isolation and extraction of standard-specific traffic statistics even in the case of heavy concurrent interference. We perform an experimental study in real environments with heterogeneous interference scenarios, showing 90%–97% burst identification accuracy. Meanwhile, the lightweight SL methods, running online on wireless sensor networks-COTS hardware, ensure sub-ms identification time and limited performance gap from machine-learning approaches.

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  • 7.
    Grimaldi, Simone
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    Martenvormfelde, Lukas
    Ostwestfalen-Lippe University of Applied Sciences, 326 57 Lemgo, Germany.
    Mahmood, Aamir
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    Onboard Spectral Analysis for Low-complexity IoT Devices2020In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 43027-43045Article in journal (Refereed)
    Abstract [en]

    The lack of coordinated spectrum access for IoT wireless technologies in unlicensed bands creates inefficient spectrum usage and poses growing concerns in several IoT applications. Spectrum awareness becomes then crucial, especially in the presence of strict quality-of-service (QoS) requirements and mission-critical communication. In this work, we propose a lightweight spectral analysis framework designed for strongly resource-constrained devices, which are the norm in IoT deployments. The proposed solution enables model-based reconstruction of the spectrum of single radio-bursts entirely onboard without DFT processing. The spectrum sampling exploits pattern-based frequency sweeping, which enables the spectral analysis of short radio-bursts while minimizing the sampling error induced by non-ideal sensing hardware. We carry out an analysis of the properties of such sweeping patterns, derive useful theoretical error bounds, and explain how to design optimal patterns for radio front-ends with different characteristics. The experimental campaign shows that the proposed solution enables the estimation of central frequency, bandwidth, and spectral shape of signals at runtime by using a strongly hardware-limited radio platform. Finally, we test the potential of the proposed solution in combination with a proactive blacklisting scheme, allowing a substantial improvement in real-time QoS of a radio link under interference.

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  • 8.
    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.

  • 9.
    Ma, Jian
    et al.
    Beijing Jiaotong University, Beijing, China.
    Yang, Dong
    Beijing Jiaotong University, Beijing, China.
    Wang, Hongchao
    Beijing Jiaotong University, Beijing, China.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    An Efficient Retransmission Scheme for Reliable End-to-End Wireless Communication over WSANs2018In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 49838-49849Article in journal (Refereed)
    Abstract [en]

    Wireless sensor and actuator network (WSAN) is increasingly recognized as an important technology in the realization of the future Internet of Things (IoT). The ability to cater to the demands of real-time, reliable and resource-constraint communication in industrial areas is highly dependent on efficient scheduling of communication links. Harsh industrial environments make packet retransmission inevitable, which causes the waste of link resource and deteriorates the reliability. Most of researches that focus on real-time and reliable performance underestimate the complexity of packet retransmission. Therefore, this paper proposes an efficient retransmission scheme to guarantee deterministic communication and decrease the resource utilization. We combine deterministic communication with a novel reliable method by proposing a flow-based slot scheduling with a concession timeslot assistant. The proposed concession slot works by using the CCA and the pre-signal to avoid the contention of one channel during the communication on shared links. Furthermore, we use the theory of discrete-time Markov chain to analyze another two randomly backoff-based and flow-based shared link schedules. This study demonstrates that the proposed retransmission scheme can significantly improve the reliability of end-to-end packets delivery and the efficiency of slot utilization, as well as decrease energy consumption. The proposed scheduling is applied in a real factory, where the efficiency of the slot is significantly improved, and a flow reliability of 95.3% under a 12% packet error rate is guaranteed. 

  • 10.
    Zhang, Weiting
    et al.
    Beijing Jiatong University, China.
    Yang, Dong
    Beijing Jiatong University, China.
    Wang, Hongchao
    Beijing Jiatong University, China.
    Zhang, Jun
    Beijing Jiatong University, China.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology.
    AESGRU: An Attention-based Temporal Correlation Approach for End-to-End Machine Health Perception2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 141487-141497Article in journal (Refereed)
    Abstract [en]

    Accurate and real-time perception of the operating status of rolling bearings, which constitute a key component of rotating machinery, is of vital significance. However, most existing solutions not only require substantial expertise to conduct feature engineering, but also seldom consider the temporal correlation of sensor sequences, ultimately leading to complex modeling processes. Therefore, we present a novel model, named Attention-based Equitable Segmentation Gated Recurrent Unit Networks (AESGRU), to improve diagnostic accuracy and model-building efficiency. Specifically, our proposed AESGRU consists of two modules, an equitable segmentation approach and an improved deep model. We first transform the original dataset into time-series segments with temporal correlation, so that the model enables end-to-end learning from the strongly correlated data. Then, we deploy a single-layer bidirectional GRU network, which is enhanced by attention mechanism, to capture the long-term dependency of sensor segments and focus limited attention resources on those informative sampling points. Finally, our experimental results show that the proposed approach outperforms previous approaches in terms of the accuracy.

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