Showing papers by "Mehran Abolhasan published in 2020"
TL;DR: This work presents “PrivySharing,” a blockchain-based innovative framework for privacy-preserving and secure IoT data sharing in a smart city environment that conforms to some of the significant requirements outlined in the European Union General Data Protection Regulation.
152 citations
TL;DR: A crescent shape resonator has been introduced that provides over 99% absorption ratio for all polarization angles, as well as 70% and 93% efficiencies for different incident angles up to θ=80, and the insensitivity for TE and TM modes can be adjusted due to the semi-symmetric structure.
Abstract: Being incident and polarization angle insensitive are crucial characteristics of metamaterial perfect absorbers due to the variety of incident signals. In the case of incident angles insensitivity, facing transverse electric (TE) and transverse magnetic (TM) waves affect the absorption ratio significantly. In this scientific report, a crescent shape resonator has been introduced that provides over 99% absorption ratio for all polarization angles, as well as 70% and 93% efficiencies for different incident angles up to [Formula: see text] for TE and TM polarized waves, respectively. Moreover, the insensitivity for TE and TM modes can be adjusted due to the semi-symmetric structure. By adjusting the structure parameters, the absorption ratio for TE and TM waves at [Formula: see text] has been increased to 83% and 97%, respectively. This structure has been designed to operate at 5 GHz spectrum to absorb undesired signals generated due to the growing adoption of Wi-Fi networks. Finally, the proposed absorber has been fabricated in a [Formula: see text] array structure on FR-4 substrate. Strong correlation between measurement and simulation results validates the design procedure.
47 citations
TL;DR: A method for optimising scintillator thickness to maximise the probability of locating the point of interaction of 511 keV photons in a monolithic scintilator within a specified error bound is proposed and evaluated.
Abstract: High-resolution arrays of discrete monocrystalline scintillators used for gamma photon coincidence detection in PET are costly and complex to fabricate, and exhibit intrinsically non-uniform sensitivity with respect to emission angle. Nanocomposites and transparent ceramics are two alternative classes of scintillator materials which can be formed into large monolithic structures, and which, when coupled to optical photodetector arrays, may offer a pathway to low cost, high-sensitivity, high-resolution PET. However, due to their high optical attenuation and scattering relative to monocrystalline scintillators, these materials exhibit an inherent trade-off between detection sensitivity and the number of scintillation photons which reach the optical photodetectors. In this work, a method for optimising scintillator thickness to maximise the probability of locating the point of interaction of 511 keV photons in a monolithic scintillator within a specified error bound is proposed and evaluated for five nanocomposite materials (LaBr3:Ce-polystyrene, Gd2O3-polyvinyl toluene, LaF3:Ce-polystyrene, LaF3:Ce-oleic acid and YAG:Ce-polystyrene) and four ceramics (GAGG:Ce, GLuGAG:Ce, GYGAG:Ce and LuAG:Pr). LaF3:Ce-polystyrene and GLuGAG:Ce were the best-performing nanocomposite and ceramic materials, respectively, with maximum sensitivities of 48.8% and 67.8% for 5 mm localisation accuracy with scintillator thicknesses of 42.6 mm and 27.5 mm, respectively.
39 citations
TL;DR: A travel pattern method is proposed that employs train stations as points of data offloading so that trains can deliver data as well as passengers at stations and a data transmission unit that employs appropriate communication methods to transmit data to railway control centers is proposed.
Abstract: This paper introduces a new framework into future data-driven railway condition monitoring systems (RCM). For this purpose, we have proposed an edge processing unit that includes two main parts: a data classification model that classifies Internet of Things (IoT) data into maintenance-critical data (MCD) and maintenance-non-critical data (MNCD) and a data transmission unit that, based on the class of data, employs appropriate communication methods to transmit data to railway control centers. For the transmission of MNCD, we propose a travel pattern method that employs train stations as points of data offloading so that trains can deliver data as well as passengers at stations. The performance of our proposed solution is successfully validated via three various data sets under different operating conditions.
25 citations
TL;DR: This article focuses on active protection methods because of their potential for real-time deployment during frost events and for integrated frost prediction and active protection systems, prediction method, sensor types, and integration architecture are assessed.
Abstract: Frost damage in broadacre cropping and horticulture (including viticulture) results in substantial economic losses to producers and may also disrupt associated product value chains. Frost risk windows are changing in timing, frequency, and duration. Faced with the increasing cost of mitigation infrastructure and competition for resources (e.g., water and energy), multiperil insurance, and the need for supply chain certainty, producers are under pressure to innovate in order to manage and mitigate risk. Frost protection systems are cyber–physical systems (CPSs) consisting of sensors (event detection), intelligence (prediction), and actuators (active protection methods). The Internet-of-Things communication protocols joining the CPS components are also evaluated. In this context, this article introduces and reviews existing methods of frost management. This article focuses on active protection methods because of their potential for real-time deployment during frost events. For integrated frost prediction and active protection systems, prediction method, sensor types, and integration architecture are assessed, research gaps are identified and future research directions proposed.
17 citations
TL;DR: In this article, a polarization-insensitive multilayer metamaterial absorber is introduced to measure the variation in the available RF energy levels for crowd estimation purposes, which is designed to absorb and transfer the maximum of the available Wi-Fi energy to a lumped element to enable proper and accurate measurements.
Abstract: Noninvasive crowd estimation has remained a challenging issue among researchers. Methods such as image analysis and Wi-Fi/Bluetooth probing can always be used to identify and track people. Lately, authors have introduced a noninvasive method for crowd estimation based on ambient RF energy measurements. In this article, a polarization-insensitive multilayer metamaterial absorber is introduced to measure the variation in the available RF energy levels for crowd estimation purposes. The proposed dual-band absorber is designed to absorb and transfer the maximum of the available Wi-Fi energy to a lumped element to enable proper and accurate measurements. To evaluate the design, the proposed structure is fabricated as an array, and its performance is tested, proving perfect absorption at the desired frequencies, 2.4 and 5 GHz.
15 citations
02 May 2020
TL;DR: Initial experimentation shows that Pledge is economical with low computations and communications complexity and low latency in transaction confirmation.
Abstract: Exhibition of malicious behavior during blockchain consensus, threats against reputation systems, and high TX latency are significant issues for blockchain-based IoT systems. Hence, to mitigate such challenges we propose "Pledge", a unique Proof-of-Honesty based consensus protocol. Initial experimentation shows that Pledge is economical with low computations and communications complexity and low latency in transaction confirmation.
12 citations
TL;DR: Two solution methods, namely the concave–convex fractional programming and the Semidefinite Programming (SDP) formulations of the problem have been provided and the proposed solution methods have been compared over different topologies and branches of an arbitrary network, where the SDP based approach has shown to be less restricted and more suitable for a wider range of topologies.
10 citations
15 Mar 2020
TL;DR: In this paper, a low profile polarization angle selective metamaterial absorber has been designed to absorb signals in the frequency range of 21.79 GHz to 53.23 GHz with more than 90% efficiency.
Abstract: Implementing 5G technology contributes to improve communication quality and facilitate several interesting applications in daily life such as Internet of things. Despite outstanding features of 5G, the amount of ambient electromagnetic waves will be increased significantly in the environment, which may be undesired. Ultra-wideband metamaterial perfect absorber is a promising solution to collect these undesired signals. Using lumped elements in absorber structure to increase the absorption bandwidth leads to design and fabrication process complexity. In this paper, a low profile polarization angle selective metamaterial absorber has been designed to absorb signals in the frequency range of 21.79 GHz to 53.23 GHz with more than 90% efficiency. The relative absorption bandwidth of the final structure is 83.81%. Moreover, the final structure is reasonably insensitive facing different incident angle up to 40 degree.
6 citations
TL;DR: A novel method for non-intrusive crowd density estimation that monitors variation in EM radiation within an environment that allows for the determination of the number of people within a room.
Abstract: Current crowd density estimation technologies that leverage IR depth perception, video and image processing or WiFi/BLE-based sniffing and probing have privacy and deployment issues. This paper presents a novel method for non-intrusive crowd density estimation that monitors variation in EM radiation within an environment. The human body's electrical and magnetic characteristics can be correlated with variations in available EM energy. This allows for the determination of the number of people within a room. Simulations conducted using Comsol to analyse and measure electromagnetic energy levels inside a room containing human bodies. Experimental analysis provides validation of the simulation results by showing $\text{0.8}\;\text{dBm}$ drop on the average level of EM energy per person.
6 citations
16 Nov 2020
TL;DR: In this paper, the maximum number of retransmissions under a given latency-reliability constraint is learned statistically by the devices from the history of their previous transmissions and shared with the base station.
Abstract: Mission-critical machine type communication (MC-MTC) systems in which machines communicate to perform various tasks such as coordination, sensing, and actuation, require stringent requirements of ultra-reliable and low latency communications (URLLC). Edge computing being an integral part of future wireless networks, provides services that support URLLC applications. In this paper, we use the edge computing approach and present a statistical learning-based dynamic retransmission mechanism. The proposed approach meets the desired latency-reliability criterion in MC-MTC networks employing framed ALOHA. The maximum number of retransmissions Nr under a given latency-reliability constraint is learned statistically by the devices from the history of their previous transmissions and shared with the base station. Simulations are performed in MATLAB to evaluate a framed-ALOHA system’s performance in which an active device can have only one successful transmission in one round composed of (Nr + 1) frames, and the performance is compared with the diversity transmission-based framed-ALOHA.
TL;DR: The proposed algorithms for placement of access points (APs) for the purpose of data transportation via train-to-wayside (T2W) communications along a rail network can improve the efficiency of the system at least 21% and up to 165% within 10 different scenarios.
Abstract: In this paper, we propose three algorithms for placement of access points (APs) for the purpose of data transportation via train-to-wayside (T2W) communications along a rail network. The first algorithm is proposed to find the minimum number of APs so that the path-loss (PL) does not exceed a desired threshold. Through the second algorithm, the most optimal places for a desired number of APs are determined so that the average PL is minimum. The goal of the third algorithm is to determine the required number and optimal places of APs in a rail network. Furthermore, we propose a model to consider the effects of changes of communication characteristics on the efficiency of the network in different environments. Through such model, the algorithms proposed for placement of APs can be used in different railway scenarios. The proposed algorithms are validated through extensive simulations in Sydney Trains of Australia. The simulation results show that the proposed approach can improve the efficiency of the system at least 21% and up to 165% within 10 different scenarios. We also show that we can approximately transmit over 250 Gigabit data through T2W communications over common WiFi networks.
16 Nov 2020
TL;DR: Pledge as mentioned in this paper is a unique Proof-of-Honesty based consensus protocol to reduce the possibility of malicious behavior during blockchain consensus and also introduces the Internet of Things centric transaction validation rules.
Abstract: The existing lottery-based consensus algorithms, such as Proof-of-Work, and Proof-of-Stake, are mostly used for blockchain-based financial technology applications. Similarly, the Byzantine Fault Tolerance algorithms do provide consensus finality, yet they are either communications intensive, vulnerable to Denial-of-Service attacks, poorly scalable, or have a low faulty node tolerance level. Moreover, these algorithms are not designed for the Internet of Things systems that require near-real-time transaction confirmation, maximum fault tolerance, and appropriate transaction validation rules. Hence, we propose "Pledge," a unique Proof-of-Honesty based consensus protocol to reduce the possibility of malicious behavior during blockchain consensus. Pledge also introduces the Internet of Things centric transaction validation rules. Initial experimentation shows that Pledge is economical and secure with low communications complexity and low latency in transaction confirmation.
25 Nov 2020
TL;DR: In this article, a traffic rerouting mechanism is proposed to address congestion in Software-Defined networks, which employs backtracking and constraint propagation techniques to find alternate paths to reroute multiple active flows simultaneously.
Abstract: In this paper, we propose a traffic rerouting mechanism to address congestion in Software-Defined networks. We employ back-tracking and constraint propagation techniques to find alternate paths to reroute multiple active flows simultaneously. Cost function is based on standard deviation of link-loads. We then compare traffic distribution and link utilisation with and without rerouting active flows. We measure and compare network performance using parameters such as total rate of transfer, jitter, and packet loss with that of Shortest Path First with no rerouting. Our proposed solution produces lower jitter, packet drops, and higher transfer rate. We finally conclude the paper by making observations and discussing the scope of the future work.
TL;DR: The proposed mobility model will provide a guidance trajectory for trains to have an energy-optimized operation and an algorithm is developed that can determine the specifications of contacts between trains based on the traffic traces obtained from the mobility model.
Abstract: In this paper, we propose a novel mobility model providing train traffic traces essential for train-to-train communication models. As the proposed mobility model works only based on trip timetables and train timetables are currently available in real-time, the produced mobility traces will be also in real-time. Additionally, as no GPS module is used in this method, our proposed model can provide a practical solution when signal from GPS or Assisted GPS is poor or unavailable such as in urban area or inside tunnels. Furthermore, as we used an energy optimization function, the proposed mobility model will provide a guidance trajectory for trains to have an energy-optimized operation. We also develop an algorithm that can determine the specifications of contacts between trains based on the traffic traces obtained from the mobility model. Such specifications includes duration, rate and location of train contacts used for estimation of data exchange capacity between trains through train-to-train communications. We validate our proposed model using data collected from Sydney Trains of Australia. The results obtained from our proposed model show over 98 percent accuracy in comparison with the real data collected via a GPS module from Sydney Trains.