WINSYS 2021 Abstracts

Area 1 - Ciber-Physical Systems

Short Papers

Paper Nr:	12
Title:	Towards Federated Learning-based Collaborative Adaptive Cybersecurity for Multi-microgrids
Authors:	Svetlana Boudko, Habtamu Abie, Ethiopia Nigussie and Reijo Savola
Abstract:	Multi-microgrids (MMGs) provide economic and environmental benefits to society by improving operational flexibility, stability and reliability of a smart grid. MMGs have greater complexity than conventional power networks due to the use of multiple infrastructures, communication protocols, controllers, and intelligent electronic devices. The distributed and heterogeneous connectivity technologies of the MMGs and their need to exchange information with external sources as well as the vulnerabilities in the communication networks and software-based components, make MMGs susceptible to cyberattacks. In this work, we present a conceptual framework for collaborative adaptive cybersecurity that is able to proactively detect security incidents. The framework utilizes federated learning for collaborative training of shared prediction models in a decentralized manner. The methodology used in this research is mainly analytical. This involves analysis of how the principles of a collaborative adaptive cybersecurity can be applied to the MMG environments resulting in the development of theoretical models which can then be validated in practice by prototyping and using real time simulation.
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Area 2 - e-Health Monitoring

Short Papers

Paper Nr:	5
Title:	Feasibility and Usability of Wearable Devices for Ambulatory Monitoring of the Rehabilitation Process of Older Patients after Hip Fracture Surgery
Authors:	Dieuwke van Dartel, Johannes H. Hegeman and Miriam M. R. Vollenbroek-Hutten
Abstract:	Objective: To assess the feasibility and usability of wearable devices for ambulatory monitoring of older patients during geriatric rehabilitation after hip fracture surgery. Methods: Patients (≥70 years) who were surgically treated for a hip fracture wore the Fitbit Charge 2/HR and the MOX device. Feasibility was assessed by investigating whether real world data gathering revealed sufficient high-quality data. Usability was assessed by 1) evaluating whether changes in the device parameters correlated with changes in clinimetric tests and 2) determining whether the wearable devices properly measured activity. Results: Data from 67 patients was used to assess feasibility; all patients wore the Fitbit and 33 the MOX. The mean amount of high-quality data was 88.1% for the Fitbit and 93.6% for the MOX. Data from 42 patients was used to assess usability; all patients wore the Fitbit and 14 the MOX. A positive progression in clinimetric tests was correlated with an increase in activity parameters. However, the Fitbit often miscalculated the number of steps and the MOX algorithm often misclassified slow walking as standing. Conclusions: Ambulatory monitoring using the Fitbit and MOX is feasible in older patients with a hip fracture. Concerning the usability, the Fitbit often miscalculated the number of steps. The MOX was more adequate but the activity classification algorithm often misclassified slow walking based on which it is recommended to use the raw data instead.
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Paper Nr:	13
Title:	Design of a Tag Antenna for IoT Applications in the Healthcare Field
Authors:	Amine Rghioui, Loubna Berrich, Jaime Lloret and Abdelmajid Oumnad
Abstract:	RFID Radio Frequency Identification is a method of remotely memorizing and retrieving data. The system is activated by a transfer of electromagnetic energy between a radio tag and an RFID transmitter. The radio tag, made up of an electronic chip and an antenna, receives the radio signal emitted by the reader, also equipped with RFID technology. This technology is useful in a wide variety of processes. The uses that can be attributed to it are many and varied as well as the sectors where it can be applied. In this paper we will study the use of RFID in the healthcare sector. Wireless technology is evolving more and more in the world of healthcare applications among these technologies we find the Internet of Things, sensor networks, RFID technologies. Radiofrequency identification (RFID) technology is a new technology that improves the quality of life of patients and offers several technological solutions and involves several fields application, we find the field of healthcare with the ability to track or locate equipment and people in real-time, and also provides efficient access to medical data for physicians and other medical professionals. The use of RFID technology in healthcare has become more popular due to its unique characteristics compared to other technologies. In this article, we discuss the state of the art and the relationship between RFID technology and the Internet of Things. after that, we introduce healthcare system monitoring using RFID technology. Finally, we offer our RFID body sensor tag design suggestion we present an RFID antenna used for healthcare application; we made many simulations in order to get an idea about the behaviour of the antenna with the patient.
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Paper Nr:	19
Title:	Comparative Analysis of Short-range Wireless Technologies for m-Health: Newborn Monitoring Case Study
Authors:	Fernando Crivellaro, Anselmo Costa and Pedro Vieira
Abstract:	The Healthcare and the Internet of Things (IoT) are being integrated to improve the people life quality in many aspects, as for example, through the increasing of the patients wellness and also optimizing Hospitals activities. One of the main actors in this integration is the communication link that connects the people to the systems, which is made in most of the cases through wireless devices. There are many available wireless technologies to be applied in a great diversity of healthcare scenarios, in which would stands out specific technologies advantages for each one. Therefore, among the great number of information about it, in this work it is detailed the physical layer characteristics of 9 most used technologies in short-range wireless applications for healthcare. Also, it is made a technology selection for one specific application scenario of newborn babies monitoring.
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Area 3 - Wireless and Mobile Technologies

Full Papers

Paper Nr:	6
Title:	Optimized Line-of-Sight Assessment Algorithm for 5G mmW Network Design using LiDAR Information
Authors:	Reza Soosahabi and Magdy Bayoumi
Abstract:	Utilizing mmW carrier frequency bands (aka above-6 GHz) at the network edge, is a key enabling factor to achieve near Gbps throughput in 5G-NR technology. The propagation characteristics of mmW signals in outdoor environment complicates 5G mmW network design. Previously used in backhaul networks, the service availability of mmW radio technologies significantly relies on the Line-of-Sight (LoS) signal path between the communicating radios. LiDAR is considered a popular source of high-resolution aerial survey data suitable for accurate LoS assessment. Maintaining low radio mounting height is another cost-related factor in practical 5G mmW network design. In this work we present a comprehensive LoS assessment problem incorporating radio mounting height. Then we propose a new LoS assessment algorithm using LiDAR data that is computationally optimized for the practical aspects of 5G mmW network design. Empowered by a novel method to topologically sort terrain data, it achieves constant-time, O(1), complexity to execute LoS assessment per user location, whereas the complexity of retrofitted LoS algorithms for the same task grows linearly with respect to the data dimensions. The improvements in the run-time efficiency are verified in numerical results for a real deployment scenario.
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Paper Nr:	10
Title:	Simulation-based Study of Interference Impact in ISM Bands in Smart Cities: Connected Traffic Light for Visually Impaired People Use-case
Authors:	Mohammad Rahal, Marc Ibrahim and Gerard Chalhoub
Abstract:	Wireless technologies operating in the unlicensed ISM (Industrial Scientific and Medical) bands are omnipresent. Indeed, with the expansion of the Internet of Things, plenty of applications are being developed on devices that use the 868.3 - 868.8 MHz ISM band. This expansion has an impact on existing technologies operating at the same frequencies. This paper focuses on the impact of IoT networks on a special use case deployed in smart cities which is the connected traffic light for visually impaired pedestrians. A connected traffic light is equipped with a radio receiver that operates at 868.3MHz frequency. It allows pedestrians to query the state of the traffic light using a handheld remote control. When the latter is pressed, a generated radio message will activate a sound beacon that tells the state of the traffic light. In some cases, when the traffic light is not optimally deployed or when it suffers from interference, the connection with the remote control cannot be established. In this paper, we investigate, using a detailed simulation analysis, the impact of interfering IoT devices and antenna types used on the receiver module of the traffic light on the quality of the radio links.
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Paper Nr:	21
Title:	Deep Reinforcement Learning for Dynamic Power Allocation in Cell-free mmWave Massive MIMO
Authors:	Yu Zhao, Ignas Niemegeers and Sonia Heemstra de Groot
Abstract:	Numerical optimization has been investigated for decades to solve complex problems in wireless communication systems. This has resulted in many effective methods, e.g., the weighted minimum mean square error (WMMSE) algorithm. However, these methods often incur a high computational cost, making their application to time-constrained problems difficult. Recently data-driven methods have attracted a lot of attention due to their near-optimal performance with affordable computational cost. Deep reinforcement learning (DRL) is one of the most promising optimization methods for future wireless communication systems. In this paper, we investigate the DRL method, using a deep Q-network (DQN), to allocate the downlink transmission power in cell-free (CF) mmWave massive multiple-input multiple-output (MIMO) systems. We consider the sum spectral efficiency (SE) optimization for systems with mobile user equipment (UEs). The DQN is trained by the rewards of trial-and-error interactions with the environment over time. It takes as input the long-term fading information and it outputs the downlink transmission power values. The numerical results, obtained for a particular 3GPP scenario, show that DQN outperforms WMMSE in terms of sum-SE and has a much lower computational complexity.
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Paper Nr:	22
Title:	Multi-layer Fog Computing Framework for Constrained LoRa Networks Intended for Water Quality Monitoring and Precision Agriculture Systems
Authors:	Laura García, Jose M. Jimenez, Sandra Sendra, Jaime Lloret and Pascal Lorenz
Abstract:	As the population of the world keeps increasing, it is necessary for the agriculture to adopt technologies that improve the production and optimize re-sources such as water. This has been done by introducing IoT devices, which has led to smart agriculture or precision agriculture. However, due to the remoteness of the fields, the communication of these devices needs to be per-formed with technologies such as LoRa that has limitations on the amount of data and the number of messages that can be forwarded. Furthermore, as there is no connection to the electric grid, optimizing the energy consumption is a necessity. In this paper, we present a multi-layer fog computing framework for a water quality monitoring and precision agriculture system. Data aggregation techniques are applied at the algorithms provided for the different layers to reduce the amount of data and the number of messages forwarded to the data center so as to improve the performance of the constrained LoRa network and reduce the energy consumption. Furthermore, the added decision-making provides fault-tolerance to the system if the connection to the Data Center is not available. Simulations were performed for different functioning modes. Results show a reduction of the 80% in the amount of transmitted data and a reduction of 85.33% in the number of for-warded messages for the most restrictive functioning mode.
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Short Papers

Paper Nr:	7
Title:	Opportunistic Routing towards Mobile Sink Nodes in Bluetooth Mesh Networks
Authors:	Marcelo Paulon J. V., Bruno José Olivieri de Souza and Markus Endler
Abstract:	This work evaluates sporadic data collection on a Bluetooth Mesh network, using the OMNET++ INET simulator. The data collector is a roaming sink node, which could be a smartphone or other portable device, carried by a pedestrian, a biker, an animal, or a drone. The sink node could connect to a mesh network in hard-to-reach areas that do not have internet access and collect sensor data. After implementing Bluetooth Mesh relay extensions, Low Power, and Friend features in OMNET++, we were able to propose and evaluate algorithms for mobility-aware, adaptive, routing of sensor data towards the sink node. While the long-term goal for this research is to implement the proposed algorithms on ESP32-based SoCs to monitor tree health, so far, the preliminary simulated results already reveal some interesting findings. One variation of a proposed routing algorithm achieved an 82.00% increase in unique data delivered to the sink node compared to Bluetooth Mesh’s default routing algorithm. In that case, there was a 5.45% decrease in energy consumption for the same scenario. Also, the delivery rate increased by 58.22%.
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Paper Nr:	9
Title:	On a Wireless Sensor Network Problem with Spanning Tree Backbone
Authors:	Pablo Adasme and Ali Dehghan Firoozabadi
Abstract:	Let G = (V,E) be a complete graph with set of nodes V = {1,...,n} and edge set E = {1,...,m} representing a wireless sensor network. In this paper, we consider the problem of finding a minimum cost spanning tree backbone formed with p ∈ Z+ out of n nodes where p < n in such a way that the n − p remaining nodes of G are connected to the leaf nodes of the backbone structure at minimum connectivity cost. Notice that this problem arises as a combination of two classical combinatorial optimization problems, namely the p-Median and spanning tree problems. We propose two mixed-integer linear programming (MIP) formulations for this problem as well as a local search heuristic. The proposed models and algorithm can be used as a reference source for comparison purposes when designing future network protocols. We consider complete graph instances with Euclidean and random uniform costs. Our preliminary numerical results indicate that one of the proposed models performs slightly better than the other one in terms of solution quality and CPU times obtained with the Gurobi solver. Finally, the proposed heuristic allows one to obtain near-optimal solutions in remarkably less CPU time compared to the MIP models.
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Area 4 - Mobile Software and Services

Short Papers

Paper Nr:	20
Title:	A Double Auction Mechanism for Coded Distributed Computing in Smart Vehicles
Authors:	Jer Shyuan Ng, Wei Yang Bryan Lim, Zehui Xiong, Sahil Garg, Yang Zhang, Dusit Niyato and Cyril Leung
Abstract:	The development of smart vehicles and rich cloud services have led to the emergence of vehicular edge computing. To perform the distributed computation tasks efficiently, Coded Distributed Computing (CDC) was proposed to reduce communication costs and mitigate the straggler effects through the use of coding techniques. In this paper, we propose a double auction mechanism to allocate the resources of the edge servers to the vehicles in order to complete the CDC tasks. Specifically, the vehicles use the PolyDot codes to manage the tradeoff between communication costs and recovery threshold. Given the requirements of various vehicles, the double auction mechanism matches the edge servers with the required resources to the vehicles. Besides, the double auction mechanism also determines the prices that the vehicles need to pay for the resources of the edge servers. The double auction mechanism satisfies the properties of individual rationality, incentive compatibility and budget-balance.
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