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Balador, Ali
Publications (10 of 14) Show all publications
Balador, A., Bai, C. & Sedighi, F. (2019). A Comparison of Decentralized Congestion Control Algorithms for Multiplatooning Communications. In: 2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019: . Paper presented at 2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019, 11 March 2019 through 15 March 2019 (pp. 674-680). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>A Comparison of Decentralized Congestion Control Algorithms for Multiplatooning Communications
2019 (English)In: 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, Published 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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2019
Keywords
Intelligent systems, Intelligent vehicle highway systems, Safety engineering, Ubiquitous computing, Vehicles, Dangerous situations, European telecommunications standards institutes, Evaluation metrics, Intelligent transportation systems, ITS applications, Safety messages, Threshold levels, Vehicle density, Traffic congestion
National Category
Health Sciences
Identifiers
urn:nbn:se:mdh:diva-44874 (URN)10.1109/PERCOMW.2019.8730578 (DOI)000476951900141 ()2-s2.0-85067951673 (Scopus ID)9781538691519 (ISBN)
Conference
2019 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019, 11 March 2019 through 15 March 2019
Available from: 2019-07-11 Created: 2019-07-11 Last updated: 2019-08-15Bibliographically approved
Bakhshi Valojerdi, Z. & Balador, A. (2019). An Overview on Security and Privacy Challenges and TheirSolutions in Fog-Based Vehicular Application. In: An Overview on Security and Privacy Challenges and Their Solutions in Fog-Based Vehicular Application: . Paper presented at IEEE International Symposium on Personal, Indoor and Mobile Radio Communications. Istanbul
Open this publication in new window or tab >>An Overview on Security and Privacy Challenges and TheirSolutions in Fog-Based Vehicular Application
2019 (English)In: An Overview on Security and Privacy Challenges and Their Solutions in Fog-Based Vehicular Application, Istanbul, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Fog computing is an emerging computing paradigm that extends cloud services to the edge of the network by moving computation tasks from cloud to network edges to reduce response latency in a wireless network. Fog computing inherits the principle of peer-to-peer networking, decentralization, and geographical distribution from clouds. Hence, fog computing becomes an ideal platform for readily supporting vehicular applications due to its dynamic support for mobility of client-devices and low latent heterogeneous communication capabilities. Despite many advantages, a multitude of security and privacy issues affects the platforms and renders it as a target for unknown adversaries. This has significant implication in the development of safety critical applications, such as vehicular cloud and intelligent transportation system. This paper presents, an overview of existing security and privacy vulnerabilities in fog computing, particularly in vehicular networks. Moreover, state-of-the-art security and privacy solutions for fog based vehicular networks are analyzed. In conclusion, open challenges and future research directions are discussed.

Place, publisher, year, edition, pages
Istanbul: , 2019
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-45903 (URN)2-s2.0-85074947721 (Scopus ID)
Conference
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications
Available from: 2019-11-02 Created: 2019-11-02 Last updated: 2019-11-21
Eziama, E., Jaimes, L. M., James, A., Nwizege, K. S., Balador, A. & Tepe, K. (2019). Machine learning-based recommendation trust model for machine-to-machine communication. In: 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018: . Paper presented at 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018, 6 December 2018 through 8 December 2018. Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Machine learning-based recommendation trust model for machine-to-machine communication
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2019 (English)In: 2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018, Institute of Electrical and Electronics Engineers Inc. , 2019Conference paper, Published 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.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2019
Keywords
Internet of Things(IoTs), Internet of Vehicles(IoVs), Machine Type Communication Devices, Machine-to-Machine(M2M), Supervisory Control and Data Supervisory Acquisition(SCADA), Decision trees, Internet protocols, Learning algorithms, Machine learning, Nearest neighbor search, Network security, Signal processing, Support vector machines, Vehicle to vehicle communications, Comparative analysis, Internet of thing (IoTs), K nearest neighbor (KNN), Machine learning approaches, Machine type communications, Machine-to-machine (M2M), Receiver operating characteristics, Supervisory control, Machine-to-machine communication
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-43502 (URN)10.1109/ISSPIT.2018.8705147 (DOI)2-s2.0-85065641118 (Scopus ID)9781538675687 (ISBN)
Conference
2018 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2018, 6 December 2018 through 8 December 2018
Available from: 2019-05-28 Created: 2019-05-28 Last updated: 2019-06-11Bibliographically approved
Vo, V. N., Tran, H. V., Uhlemann, E., Truong, Q. X., So-In, C. & Balador, A. (2019). Reliable Communication Performance for Energy Harvesting Wireless Sensor Networks. In: 2019 IEEE 89TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2019-SPRING): . Paper presented at 89th IEEE Vehicular Technology Conference (VTC Spring), APR 28-MAY 01, 2019, Kuala Lumpur, MALAYSIA. IEEE
Open this publication in new window or tab >>Reliable Communication Performance for Energy Harvesting Wireless Sensor Networks
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2019 (English)In: 2019 IEEE 89TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2019-SPRING), IEEE , 2019Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we study the problem of how to provide reliable communications for energy harvesting (EH) wireless sensor network (WSN). Using the example of an autonomous quarry, where self-driving trucks autonomously collect and transport goods, there is a need for multiple wireless sensors collecting data about where and when goods can be collected, while guaranteeing reliable operation of the quarry. The vehicles transfer energy to the wireless sensors within range, forming a cluster. The sensors use this energy to transmit data to the vehicles. Finally, the vehicles relay information to an access point (AP). The AP processes the collected information and synchronize the operation of all vehicles. We propose an interference channel selection policy for the sensors-to-vehicles links and vehicles-to-AP links to improve the reliability of the communications, while enhancing the energy utilization. Accordingly, closed-form expression on how to achieve reliable communication within the considered system is derived and numerical results show that the proposed channel selection strategy not only improves the probability of achieving sufficiently reliable communication but also enhances the energy utilization.

Place, publisher, year, edition, pages
IEEE, 2019
Series
IEEE Vehicular Technology Conference Proceedings, ISSN 1550-2252
Keywords
Energy Harvesting, Wireless Sensor Networks, Interference Level, Reliable Communication Probability
National Category
Communication Systems
Identifiers
urn:nbn:se:mdh:diva-45266 (URN)000482655600031 ()978-1-7281-1217-6 (ISBN)
Conference
89th IEEE Vehicular Technology Conference (VTC Spring), APR 28-MAY 01, 2019, Kuala Lumpur, MALAYSIA
Available from: 2019-09-19 Created: 2019-09-19 Last updated: 2019-09-19Bibliographically approved
Pau, G., Bazzi, A., Campista, M. E. & Balador, A. (2019). Towards 5G and beyond for the internet of UAVs, vehicles, smartphones, Sensors and Smart Objects. Journal of Network and Computer Applications, 135, 108-109
Open this publication in new window or tab >>Towards 5G and beyond for the internet of UAVs, vehicles, smartphones, Sensors and Smart Objects
2019 (English)In: Journal of Network and Computer Applications, ISSN 1084-8045, E-ISSN 1095-8592, Vol. 135, p. 108-109Article in journal, Editorial material (Other academic) Published
Place, publisher, year, edition, pages
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2019
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-43451 (URN)10.1016/j.jnca.2019.03.003 (DOI)000466258100010 ()2-s2.0-85063469156 (Scopus ID)
Available from: 2019-05-16 Created: 2019-05-16 Last updated: 2019-06-11Bibliographically approved
Pau, G., Bazzi, A., Campista, M. E. & Balador, A. (2019). Towards 5G and beyond for the internet of UAVs, vehicles, smartphones, Sensors and Smart Objects. Journal of Network and Computer Applications, 135, 108-109
Open this publication in new window or tab >>Towards 5G and beyond for the internet of UAVs, vehicles, smartphones, Sensors and Smart Objects
2019 (English)In: Journal of Network and Computer Applications, ISSN 1084-8045, E-ISSN 1095-8592, Vol. 135, p. 108-109Article in journal, Editorial material (Refereed) Published
Place, publisher, year, edition, pages
Academic Press, 2019
National Category
Computer Vision and Robotics (Autonomous Systems) Vehicle Engineering Media Engineering Embedded Systems
Identifiers
urn:nbn:se:mdh:diva-43067 (URN)10.1016/j.jnca.2019.03.003 (DOI)2-s2.0-85063469156 (Scopus ID)
Available from: 2019-12-10 Created: 2019-12-10 Last updated: 2019-12-10Bibliographically approved
Hasan, S., Balador, A., Girs, S. & Uhlemann, E. (2019). Towards emergency braking as a fail-safe state in platooning: A simulative approach. In: IEEE Vehicular Technology Conference: . Paper presented at 90th IEEE Vehicular Technology Conference, VTC 2019 Fall, 22 September 2019 through 25 September 2019. Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Towards emergency braking as a fail-safe state in platooning: A simulative approach
2019 (English)In: IEEE Vehicular Technology Conference, Institute of Electrical and Electronics Engineers Inc. , 2019Conference paper, Published paper (Refereed)
Abstract [en]

Platooning is anticipated to facilitate automated driving even with semi-automated vehicles, by forming road trains using breadcrumb tracing and Cooperative Adaptive Cruise Control (CACC). With CACC, the vehicles coordinate and adapt their speed based on wireless communications. To keep the platoon fuel-efficient, the inter-vehicle distances need to be quite short, which requires automated emergency braking capabilities. In this paper, we propose synchronized braking, which can be used together with existing CACC controllers. In synchronized braking, the leading vehicle in the platoon does not brake immediately, but instead communicates its intentions and then, slightly later, the whole platoon brakes simultaneously. We show that synchronized braking can avoid rear-end collisions even at a very high deceleration rate and with short inter- vehicle distances. Also, the extra distance travelled during the delay before braking can be compensated by enabling a higher deceleration, through coordinated synchronized braking.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2019
Keywords
Adaptive cruise control, Automation, Brakes, Synchronization, Vehicles, Automated driving, Automated vehicles, Cooperative adaptive cruise control, Deceleration rate, Leading vehicle, Rear-end collisions, Road trains, Wireless communications, Braking
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-46215 (URN)10.1109/VTCFall.2019.8891254 (DOI)2-s2.0-85075231034 (Scopus ID)9781728112206 (ISBN)
Conference
90th IEEE Vehicular Technology Conference, VTC 2019 Fall, 22 September 2019 through 25 September 2019
Available from: 2019-12-02 Created: 2019-12-02 Last updated: 2019-12-02Bibliographically approved
Balador, A., Ericsson, N. & Bakhshi, Z. (2018). Communication Middleware Technologies for Industrial Distributed Control Systems: A Literature Review. In: International Conference on Emerging Technologies And Factory Automation ETFA'17: . Paper presented at International Conference on Emerging Technologies And Factory Automation ETFA'17, 12 Aug 2017, Limassol, Cyprus.
Open this publication in new window or tab >>Communication Middleware Technologies for Industrial Distributed Control Systems: A Literature Review
2018 (English)In: International Conference on Emerging Technologies And Factory Automation ETFA'17, 2018Conference paper, Published 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.

National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-37426 (URN)10.1109/ETFA.2017.8247730 (DOI)2-s2.0-85044467676 (Scopus ID)9781509065059 (ISBN)
Conference
International Conference on Emerging Technologies And Factory Automation ETFA'17, 12 Aug 2017, Limassol, Cyprus
Projects
SafeCOP - Safe Cooperating Cyber-Physical Systems using Wireless Communication
Funder
EU, Horizon 2020, 692529 Vinnova
Available from: 2017-12-20 Created: 2017-12-20 Last updated: 2019-04-18Bibliographically approved
Bakhshi, Z., Balador, A. & Mustafa, J. (2018). Industrial IoT Security Threats and Concerns by Considering CISCO and Microsoft IoT reference Models. In: IEEE WCNCW 2018 IEEE WCNCW 2018: 2018 IEEE Wireless Communications and Networking Conference Workshops. Paper presented at IEEE WCNCW 2018 IEEE WCNCW 2018, 15 Apr 2018, Barcelona, Spain (pp. 173-178).
Open this publication in new window or tab >>Industrial IoT Security Threats and Concerns by Considering CISCO and Microsoft IoT reference Models
2018 (English)In: IEEE WCNCW 2018 IEEE WCNCW 2018: 2018 IEEE Wireless Communications and Networking Conference Workshops, 2018, p. 173-178Conference paper, Published 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.

Keywords
Industrial IoT, Industry 4.0, Security, Fog, Cloud, Threats, CISCO reference Model, Microsoft IoT.
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-39254 (URN)10.1109/WCNCW.2018.8368997 (DOI)000442393300031 ()2-s2.0-85048866181 (Scopus ID)9781538611548 (ISBN)
Conference
IEEE WCNCW 2018 IEEE WCNCW 2018, 15 Apr 2018, Barcelona, Spain
Projects
SafeCOP - Safe Cooperating Cyber-Physical Systems using Wireless CommunicationELECTRA - Evaluation of different communication technologies for heavy duty vehicle platooning
Funder
EU, Horizon 2020, 692529 Vinnova
Available from: 2018-05-23 Created: 2018-05-23 Last updated: 2019-04-17Bibliographically approved
Eziama, E., Tepe, K., Balador, A., Nwizege, K. S. & Jaimes, L. M. S. (2018). Malicious Node Detection in Vehicular Ad-Hoc Network Using Machine Learning and Deep Learning. In: 2018 IEEE GLOBECOM WORKSHOPS (GC WKSHPS): . Paper presented at IEEE Global Telecommunications Conference (GC Wkshps), DEC 09-13, 2018, Abu Dhabi, U ARAB EMIRATES. IEEE
Open this publication in new window or tab >>Malicious Node Detection in Vehicular Ad-Hoc Network Using Machine Learning and Deep Learning
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2018 (English)In: 2018 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), IEEE , 2018Conference paper, Published 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.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE Globecom Workshops, ISSN 2166-0069
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-43148 (URN)10.1109/GLOCOMW.2018.8644127 (DOI)000462817000040 ()2-s2.0-85063434879 (Scopus ID)978-1-5386-4920-6 (ISBN)
Conference
IEEE Global Telecommunications Conference (GC Wkshps), DEC 09-13, 2018, Abu Dhabi, U ARAB EMIRATES
Available from: 2019-04-18 Created: 2019-04-18 Last updated: 2019-10-15Bibliographically approved
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