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  • 1.
    Aghaeinezhadfirouzja, S.
    et al.
    Department of Electronics Engineering, Shanghai Jiao Tong University, Shanghai, China.
    Liu, H.
    Department of Electronics Engineering, Shanghai Jiao Tong University, Shanghai, China.
    Balador, Ali
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. RISE SICS Västerås, Sweden.
    Practical 3-D beam pattern based channel modeling for multi-polarized massive MIMO systems2018In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 4, article id 1186Article in journal (Refereed)
    Abstract [en]

    In this paper, a practical non-stationary three-dimensional (3-D) channel models for massive multiple-input multiple-output (MIMO) systems, considering beam patterns for different antenna elements, is proposed. The beam patterns using dipole antenna elements with different phase excitation toward the different direction of travels (DoTs) contributes various correlation weights for rays related towards/from the cluster, thus providing different elevation angle of arrivals (EAoAs) and elevation angle of departures (EAoDs) for each antenna element. These include the movements of the user that makes our channel to be a non-stationary model of clusters at the receiver (RX) on both the time and array axes. In addition, their impacts on 3-D massive MIMO channels are investigated via statistical properties including received spatial correlation. Additionally, the impact of elevation/azimuth angles of arrival on received spatial correlation is discussed. Furthermore, experimental validation of the proposed 3-D channel models on azimuth and elevation angles of the polarized antenna are specifically evaluated and compared through simulations. The proposed 3-D generic models are verified using relevant measurement data.

  • 2.
    Bakhshi, Zeynab
    et al.
    RighTel, Iran.
    Balador, Ali
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. RISE SICS, Västerås, Sweden.
    Mustafa, Jawad
    RISE SICS, Västerås, Sweden.
    Industrial IoT Security Threats and Concerns by Considering CISCO and Microsoft IoT reference Models2018In: IEEE WCNCW 2018 IEEE WCNCW 2018: 2018 IEEE Wireless Communications and Networking Conference Workshops, 2018, p. 173-178Conference paper (Refereed)
    Abstract [en]

    This paper investigates security concerns and issues for Industrial Internet of Things (IIoT). The IIoT is an emerging transformation, bringing great values to every industry. Although this rapid alter in industries create values, but there are concerns about security issues, most of which would be still unknown due to the novelty of this platform. In order to provide a guideline for those who want to investigate IoT security and contribute to its improvement, this paper attempts to provide a list of security threats and issues on the cloud-side layer of IoT, which consists of data accumulation and abstraction levels. For this reason, we choose Cisco and Microsoft Azure IoT Architecture as reference models. Then, two layers of Cisco reference architecture model have been chosen to be investigated for their security issues. Finally, consideration of security issues has been briefly explained.

  • 3.
    Balador, Ali
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. RISE SICS, Vadies, Sweden.
    Bai, C.
    KTH Royal Institute of Technology, Stockholm, Sweden.
    Sedighi, F.
    Niroo Research Institute, Iran.
    A Comparison of Decentralized Congestion Control Algorithms for Multiplatooning Communications2019In: 2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019, Institute of Electrical and Electronics Engineers Inc. , 2019, p. 674-680Conference paper (Refereed)
    Abstract [en]

    To improve traffic safety, many Cooperative Intelligent Transportation Systems (C-ITS) applications rely on exchange of periodic safety messages between vehicles. However, as the number of connected vehicles increases, control of channel congestion becomes a bottleneck for achieving high throughput. Without a suitable congestion control method, safety critical messages such as Cooperative Awareness Messages (CAMs) may not be delivered on time in high vehicle density scenarios that can lead to dangerous situations which can threaten people's health or even life. The Decentralized Congestion Control (DCC) algorithm defined by European Telecommunications Standards Institute (ETSI), becomes a vital component of C-ITS applications to keep channel load under control and below a predefined threshold level. In this paper, we aim to analyze and evaluate the performance of a number of DCC protocols including ETSI DCC by providing a comparison between them for the multiplatooning application by using several widely-used evaluation metrics.

  • 4.
    Balador, Ali
    et al.
    RISE SICS Västerås, Sweden.
    Ericsson, Niclas
    RISE SICS Västerås, Sweden.
    Bakhshi, Zeynab
    RighTel, Iran.
    Communication Middleware Technologies for Industrial Distributed Control Systems: A Literature Review2018In: International Conference on Emerging Technologies And Factory Automation ETFA'17, 2018Conference paper (Refereed)
    Abstract [en]

    Industry 4.0 is the German vision for the future of manufacturing, where smart factories use information and communication technologies to digitise their processes to achieve improved quality, lower costs, and increased efficiency. It is likely to bring a massive change to the way control systems function today. Future distributed control systems are expected to have an increased connectivity to the Internet, in order to capitalize on new offers and research findings related to digitalization, such as cloud, big data, and machine learning. A key technology in the realization of distributed control systems is middleware, which is usually described as a reusable software layer between operating system and distributed applications. Various middleware technologies have been proposed to facilitate communication in industrial control systems and hide the heterogeneity amongst the subsystems, such as OPC UA, DDS, and RT-CORBA. These technologies can significantly simplify the system design and integration of devices despite their heterogeneity. However, each of these technologies has its own characteristics that may work better for particular applications. Selection of the best middleware for a specific application is a critical issue for system designers. In this paper, we conduct a survey on available standard middleware technologies, including OPC UA, DDS, and RT-CORBA, and show new trends for different industrial domains.

  • 5.
    Balador, Ali
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kouba, A.
    Polytechnic Institute of Porto, Porto 4249-015, Portugal.
    Cassioli, D.
    University of L'Aquila, L'Aquila, 67100, Italy.
    Foukalas, F.
    Technical University of Denmark, Kongens Lyngby, 2800, Denmark.
    Severino, R.
    Polytechnic Institute of Porto, Porto 4249-015, Portugal.
    Stepanova, D.
    Finnish Meteorological Institute, 99600 Sodankylä, Finland.
    Agosta, G.
    Politecnico di Milano ,Via G. Ponzio 32, Milano, I-20133, Italy.
    Xie, J.
    Group Technology & Research, DNV GL, Veritasveien 1, Norway.
    Pomante, L.
    University of L'Aquila, L'Aquila, 67100, Italy.
    Mongelli, M.
    CNR-IEIIT ,via De Marini 6, Genova, 16149, Italy.
    Pierini, P.
    Intecs S.p.A., Pisa, 56121, Italy.
    Petersen, S.
    SINTEF ICT, Trondheim, 7465, Norway.
    Sukuvaara, T.
    Finnish Meteorological Institute, 99600 Sodankylä, Finland.
    Wireless Communication Technologies for Safe Cooperative Cyber Physical Systems2018In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 11, article id 4075Article in journal (Refereed)
    Abstract [en]

    Cooperative Cyber-Physical Systems (Co-CPSs) can be enabled using wireless communication technologies, which in principle should address reliability and safety challenges. Safety for Co-CPS enabled by wireless communication technologies is a crucial aspect and requires new dedicated design approaches. In this paper, we provide an overview of five Co-CPS use cases, as introduced in our SafeCOP EU project, and analyze their safety design requirements. Next, we provide a comprehensive analysis of the main existing wireless communication technologies giving details about the protocols developed within particular standardization bodies. We also investigate to what extent they address the non-functional requirements in terms of safety, security and real time, in the different application domains of each use case. Finally, we discuss general recommendations about the use of different wireless communication technologies showing their potentials in the selected real-world use cases. The discussion is provided under consideration in the 5G standardization process within 3GPP, whose current efforts are inline to current gaps in wireless communications protocols for Co-CPSs including many future use cases.

  • 6.
    Balador, Ali
    et al.
    Universitat Pompeu Fabra, Barcelona, Spain.
    Movaghar, Ali
    Sharif University of Technology, Tehran, Iran.
    Jabbehdari, Sam
    North Tehran Branch, Islamic Azad University, Tehran, Iran.
    Kanellopoulos, Dimitris
    University of Patras, Greece.
    A novel contention window control scheme for IEEE 802.11 WLANs2012In: IETE Technical Review, ISSN 0256-4602, E-ISSN 0974-5971, Vol. 30, no 4, p. 202-212Article in journal (Refereed)
    Abstract [en]

    In the IEEE 802.11 standard, network nodes experiencing collisions on the shared medium need a mechanism that can prevent collisions and improve the throughput. Furthermore, a backoff mechanism is used that uniformly selects a random period of time from the contention window (cw) that is dynamically controlled by the Binary Exponential Backoff (BEB) algorithm. Prior research has proved that the BEB scheme suffers from a fairness problem and low throughput, especially under high traffic load. In this paper, we present a new backoff control mechanism that is used with the IEEE 802.11 distributed coordination function (DCF). In particular, we propose a dynamic, deterministic contention window control (DDCWC) scheme, in which the backoff range is divided into several small backoff sub-ranges. In the proposed scheme, several network levels are introduced, based on an introduced channel state vector that keeps network history. After successful transmissions and collisions, network nodes change their cw based on their network levels. Our extensive simulation studies show that the DDCWC scheme outperforms four other well-known schemes: Multiplicative Increase and Linear Decrease, Double Increment Double Decrement, Exponential Increase Exponential Decrease, and Linear/Multiplicative Increase and Linear Decrease. Moreover, the proposed scheme, compared with the IEEE 802.11 DCF, gives 30.77% improvement in packet delivery ratio, 31.76% in delay, and 30.81% in throughput.

  • 7.
    Balador, Ali
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Uhlemann, Elisabeth
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Calafate, C. T.
    Universitat Politècnica de València, València, Spain.
    Cano, J. -C
    Universitat Politècnica de València, València, Spain.
    Supporting beacon and event-driven messages in vehicular platoons through token-based strategies2018In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 18, no 4, article id 955Article in journal (Refereed)
    Abstract [en]

    Timely and reliable inter-vehicle communications is a critical requirement to support traffic safety applications, such as vehicle platooning. Furthermore, low-delay communications allow the platoon to react quickly to unexpected events. In this scope, having a predictable and highly effective medium access control (MAC) method is of utmost importance. However, the currently available IEEE 802.11p technology is unable to adequately address these challenges. In this paper, we propose a MAC method especially adapted to platoons, able to transmit beacons within the required time constraints, but with a higher reliability level than IEEE 802.11p, while concurrently enabling efficient dissemination of event-driven messages. The protocol circulates the token within the platoon not in a round-robin fashion, but based on beacon data age, i.e., the time that has passed since the previous collection of status information, thereby automatically offering repeated beacon transmission opportunities for increased reliability. In addition, we propose three different methods for supporting event-driven messages co-existing with beacons. Analysis and simulation results in single and multi-hop scenarios showed that, by providing non-competitive channel access and frequent retransmission opportunities, our protocol can offer beacon delivery within one beacon generation interval while fulfilling the requirements on low-delay dissemination of event-driven messages for traffic safety applications. 

  • 8.
    Eziama, E.
    et al.
    Windsor University, Canada.
    Jaimes, L. M. S.
    Universidad de Pamplona, Colombia.
    James, A.
    Federal University of Technology, Mina, Nigeria.
    Nwizege, K. S.
    Ken Saro-Wiwa Polytechnic, Bori, Nigeria.
    Balador, Ali
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tepe, K.
    Windsor University, Canada.
    Machine learning-based recommendation trust model for machine-to-machine communication2019In: 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018, Institute of Electrical and Electronics Engineers Inc. , 2019Conference paper (Refereed)
    Abstract [en]

    The Machine Type Communication Devices (MTCDs) are usually based on Internet Protocol (IP), which can cause billions of connected objects to be part of the Internet. The enormous amount of data coming from these devices are quite heterogeneous in nature, which can lead to security issues, such as injection attacks, ballot stuffing, and bad mouthing. Consequently, this work considers machine learning trust evaluation as an effective and accurate option for solving the issues associate with security threats. In this paper, a comparative analysis is carried out with five different machine learning approaches: Naive Bayes (NB), Decision Tree (DT), Linear and Radial Support Vector Machine (SVM), KNearest Neighbor (KNN), and Random Forest (RF). As a critical element of the research, the recommendations consider different Machine-to-Machine (M2M) communication nodes with regard to their ability to identify malicious and honest information. To validate the performances of these models, two trust computation measures were used: Receiver Operating Characteristics (ROCs), Precision and Recall. The malicious data was formulated in Matlab. A scenario was created where 50% of the information were modified to be malicious. The malicious nodes were varied in the ranges of 10%, 20%, 30%, 40%, and the results were carefully analyzed.

  • 9.
    Eziama, E.
    et al.
    Windsor University, Canada.
    Tepe, K.
    Windsor University, Canada.
    Balador, Ali
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Nwizege, K. S.
    Ken Saro-Wiwa Polytechnic, Bori, Nigeria.
    Jaimes, L. M. S.
    Grupo Ciencias Computacionales, Universidad de Pamplona, CA, Colombia.
    Malicious Node Detection in Vehicular Ad-Hoc Network Using Machine Learning and Deep Learning2019In: 2018 IEEE Globecom Workshops, GC Wkshps 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2019Conference paper (Refereed)
    Abstract [en]

    Vehicular Ad hoc Networks (VANETs) provide effective vehicular operation for safety as well as greener and more efficient communication of vehicles in the Dedicated Short Range Communication (DRSC). The dynamic nature of the vehicular network topology has posed many security challenges for effective communication among vehicles. Consequently, models have been applied in the literature to checkmate the security issues in the vehicular networks. Existing models lack flexibility and sufficient functionality in capturing the dynamic behaviors of malicious nodes in the highly volatile vehicular communication systems. Given that existing models have failed to meet up with the challenges involved in vehicular network topology, it has become imperative to adopt complementary measures to tackle the security issues in the system. The approach of trust model with respect to Machine/Deep Learning (ML/DL) is proposed in the paper due to the gap in the area of network security by the existing models. The proposed model is to provide a data-driven approach in solving the security challenges in dynamic networks. This model goes beyond the existing works conceptually by modeling trust as a classification process and the extraction of relevant features using a hybrid model like Bayesian Neural Network that combines deep learning with probabilistic modeling for intelligent decision and effective generalization in trust computation of honest and dishonest nodes in the network. 

  • 10.
    Eziama, Elvin
    et al.
    Windsor Univ, Windsor, ON, Canada..
    Tepe, Kemal
    Windsor Univ, Windsor, ON, Canada..
    Balador, Ali
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. RISE SICS, Vasteras, Sweden..
    Nwizege, Kenneth Sorle
    Ken Saro Wiwa Polytech, Bori, Nigeria..
    Jaimes, Luz M. S.
    Univ Pamplona, Grp Ciencias Computac, Pamplona, Spain..
    Malicious Node Detection in Vehicular Ad-Hoc Network Using Machine Learning and Deep Learning2018In: 2018 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), IEEE , 2018Conference paper (Refereed)
    Abstract [en]

    Vehicular Ad hoc Networks (VANETs) provide effective vehicular operation for safety as well as greener and more efficient communication of vehicles in the Dedicated Short Range Communication (DRSC). The dynamic nature of the vehicular network topology has posed many security challenges for effective communication among vehicles. Consequently, models have been applied in the literature to checkmate the security issues in the vehicular networks. Existing models lack flexibility and sufficient functionality in capturing the dynamic behaviors of malicious nodes in the highly volatile vehicular communication systems. Given that existing models have failed to meet up with the challenges involved in vehicular network topology, it has become imperative to adopt complementary measures to tackle the security issues in the system. The approach of trust model with respect to Machine/Deep Learning (ML/DL) is proposed in the paper due to the gap in the area of network security by the existing models. The proposed model is to provide a data-driven approach in solving the security challenges in dynamic networks. This model goes beyond the existing works conceptually by modeling trust as a classification process and the extraction of relevant features using a hybrid model like Bayesian Neural Network that combines deep learning with probabilistic modeling for intelligent decision and effective generalization in trust computation of honest and dishonest nodes in the network.

  • 11.
    Pau, Giovanni
    et al.
    Kore Univ Enna, Enna, Italy..
    Bazzi, Alessandro
    CNR, Rome, Italy..
    Campista, Miguel Elias M.
    Univ Fed Rio de Janeiro, Rio De Janeiro, Brazil..
    Balador, Ali
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Towards 5G and beyond for the internet of UAVs, vehicles, smartphones, Sensors and Smart Objects2019In: Journal of Network and Computer Applications, ISSN 1084-8045, E-ISSN 1095-8592, Vol. 135, p. 108-109Article in journal (Other academic)
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