The International Journal of Ubiquitous Systems and Pervasive Networks (JUSPN) is a high-quality scientific journal devoted to fields of Ubiquitous Systems and Pervasive Networks. It aims to provide a highly readable and valuable addition to the literature which will serve as an indispensable reference tool for years to come. The coverage of the journal includes all new theoretical and experimental findings in the fields of Ubiquitous Systems and Pervasive Networks or closely related fields. The journal also encourages the submission of critical review articles covering advances in recent research of such fields as well as technical notes.
The Editor-in-Chief and the Editorial Board are very committed to build the Journal as one of the leading international journals in Ubiquitous Systems and Pervasive Networks in the next few years. With the support of the International Association for Sharing Knowledge and Sustainability (IASKS), it is expected that a heavy resource to be channeled into the Journal to establish its international reputation. The Journal’s reputation will be enhanced from arrangements with several organizers of international conferences in publishing selected best papers of the conference proceedings. The journal is planning to publish 4 issues per year.
AIMS AND SCOPE
The International Journal of Ubiquitous Systems and Pervasive Networks (JUSPN) is a refereed international journal to be of interest and use to all those concerned with research in various fields of, or closely related to Ubiquitous Systems and Pervasive Networks disciplines. The International Journal of Ubiquitous Systems and Pervasive Networks aims to provide a highly readable and valuable addition to the literature which will serve as an indispensable reference tool for years to come. The coverage of the journal includes all new theoretical and experimental findings in the fields of Ubiquitous Systems and Pervasive Networks or closely related fields. The journal also encourages the submission of critical review articles covering advances in recent research of such fields as well as technical notes.
Sensitivity Analysis on the Impact of Candidate Transit Projects on the Network Travel Time Evaluated by a Travel Demand Model
JUSPN, volume-20 , Issue 1 (2024), PP 09 - 22
Published: 23 Jan 2024
by Camille Kamga, Patricio Vicuna, Kyriacos Mouskos from University Transportation Research Center Region 2, New York City, New York, USA and Transportation System Analyst, Nicosia, Cyprus
Abstract: This research aimed to address the Transit-Network Design Problem (NDP) where the Upper Level optimizes the vehicles' Network Travel Time (NTT) subject to a Budget constraint and subjects to the Lower Level that estimates the vehicles' NTT based on a Travel Demand Model (TDM). The study objective is to explore the impact of a naïve model of the more complex Transit-NDP, where stakeholders propose a priori a group of potential transit projects, including bus lines, tramways, light rail systems, and rail networks. The experimental setup involved a sensitivity analysis of budget-demand combinations for two test networks – where the Halle and the Karlsruhe test networks have 37 and 48 candidate transit projects, respectively. A complete evaluation enumeration of each budget-demand combination was conducted when it was computationally feasible, and a sampling evaluation set of 100 for the remaining evaluation test combinations. The Halle network exhibits a 47.6% NTT reduction for the base demand and a 50.8% reduction for the 160% demand level with all transit projects activated. The Karlsruhe Network exhibits an NTT reduction ranging between a base demand, resulting in a 39.7% reduction, whereas a 160% demand results in a 52.4% reduction with all transit projects activated. In both networks, a set of candidate transit projects were members of the best solution in all test runs. The sensitivity analysis demonstrated that some candidate transit projects selected at lower budget-demand combinations were not necessarily included at the best solutions of higher budget-demand levels. Overall, 18,432 test runs were conducted for the Halle network and 26,704 test runs for the Karlsruhe network, which required a total of 222 days. This analysis demonstrated the computational feasibility of conducting such a large set of experiments. In addition, the resulting dataset of the enumeration and sampling method was utilized to develop a Random Forest Regression (RFR) model, which was then utilized within a set of metaheuristics to solve this specific Transit-NDP. read more... read less...
Keywords: Transit-NDP, Travel Demand Model, Random Forest Regression Model
Sharing Digital Solutions with the Public for a Climate-Friendly Smart City District via an Ecosystem Map: Concepts and Solutions
JUSPN, volume-20 , Issue 1 (2024), PP 01 - 08
Published: 23 Jan 2024
by Frank Elberzhager, Anna Schmitt, Sven Storck, Stefan Schweitzer from Fraunhofer IESE, Germany, Fraunhofer-Platz 1, 67663 Kaiserslautern
Abstract: Climate change and its consequences are currently a very pressing topic. This is also true for cities. Digital solutions can be helpful in this regard. They can be used, for example, to inform citizens and provide digital services aimed at fostering climate-friendly behavior. In the EnStadt:Pfaff research project, we are developing a climate-friendly smart city district. Our focus in the project is on digitalization, with the main goal being the implementation of a digital ecosystem providing apps to the people of the district, which is currently under construction. To date, we have developed several digital solutions with different technology readiness levels. One major issue we have faced, however, has been how to inform the public about these solutions and share our ideas with them. We decided to do this in various ways, e.g., via a classical project webpage, events, and videos. In order to have one main entry point for the public to explore our solutions, we have developed a so-called ecosystem map. Four digital solutions are presented in this map to show what kind of digital solutions might be part of the future digital ecosystem in the smart city district. In this paper, we report on how we created the digital map, provide the four digital solution examples shown on the map, and present feedback we received regarding our solutions. This has also led to ideas for the future development of the map. We share three basic ones in this paper. read more... read less...
Keywords: Smart City, Sustainability, Digitalization, Information Sharing, Digital Ecosystem Map
JUSPN, volume-19 , Issue 1 (2023), PP 33 - 38
Published: 06 Dec 2023
by Bill Karakostas from Independent Researcher. Manchester, UK
Abstract: The paper presents a novel approach for the detection of ship collision risks, by classifying images of ship traffic constructed from AIS data, using deep learning techniques. In this approach, the risk level of ship traffic patterns, according to maritime safety rules, is calculated, using a convolutional neural network trained on ship traffic image data. Experiments with the analysis of real ship traffic data from the English Channel are reported. read more... read less...
Keywords: AIS, COLREG, maritime safety, autonomous ships, computer vision, CNN, Deep Learning, Keras
JUSPN, volume-19 , Issue 1 (2023), PP 25 - 32
Published: 06 Dec 2023
by Badreddine Chah, Alexandre Lombard, Anis Bkakria, Reda Yaich, Abdeljalil Abbas-Turki from CIAD UMR 7533, Univ. Bourgogne-Franche-Comté, UTBM, F-90010 Belfort, France and IRT SystemX, Palaiseau 91120, France
Abstract: This paper conducts a privacy threat analysis of connected and autonomous vehicles to address the growing concerns regarding the privacy of sensitive information collected by these vehicles. By following the LINDDUN GO methodology, this paper aims to identify privacy risks in the overall connected and autonomous vehicles architecture based on formal privacy requirements. The proposed analysis focuses on a specific use case, assisting manufacturers in implementing privacy requirements and enhancing privacy protection. This research provides valuable insights into potential risks and vulnerabilities, contributing to the development of privacy-respecting connected and autonomous vehicle systems. read more... read less...
Keywords: Privacy, Security, Threat Analysis, Connected and Autonomous Vehicle, Privacy engineering framework
JUSPN, volume-19 , Issue 1 (2023), PP 15 - 23
Published: 06 Dec 2023
by Mahmud Mansour, Najia Ben Saud from Department of Network, University of Tripoli, Tripoli, Libya
Abstract: High level of availability can be expensive to maintain, but lack of availability may also increase cost as it may damage the reputation of the business. Which led to the development of techniques that reduce downtime until it became transparent to the user. First hop redundancy protocols (FHRP) are an essential tool for improving the availability of IP networks. The first hop redundancy protocols are protocols used to manage and maintain network default gateway routers by using one or more redundant routers that will take over in case of default router failure. Each protocol has its own purpose. FHRP was developed to reduce traffic loss. In this paper we present the first hop redundancy concept and the means for its realization in IPv6 network. We evaluate three FHRP protocols, namely, the Hot Standby Router Protocol (HSRPv2), Virtual Router Redundancy Protocol (VRRPv3), and Gateway Load Balancing (GLBP). The First Hop Redundancy Protocols will be implemented, tested, optimized, and compared to one another in terms of convergence time, packet loss and CPU utilization, by using GNS3 simulator and Wireshark the results of comparison will be provided and analyzed. The performances of the three FHRP protocols are analyzed, and their functionalities are compared. The comparison results highlight which protocol performed the best in each scenario and which protocol can be considered as the best among the three FHRPs. read more... read less...
Keywords: VRRP, FHRP, HSRP, GLBP
Handling Safety and Cybersecurity Interdependency in NFV Safety Architecture With the Use of An Ontology-based Solution
JUSPN, volume-19 , Issue 1 (2023), PP 01 - 13
Published: 06 Dec 2023
by Dionysia Varvarigou, David Espes, Giacomo Bersano from Université de Bretagne Occidentale, Brest, France, 29238 and Ikos consulting, Paris, France
Abstract: In case safety-critical systems face an anomaly (either intentional or not), safety and cybersecurity impact humans and environment. Thus, they affect each other and so they are considered as interdependent. An ontology-based solution for safety is needed to handle this interdependency. We propose a new safety ontology for Network Function Virtualization (NFV) framework which is able to cover reliability, availability, maintainability, and integrity-related breakdown types, since they interact and influence safety according to ENISA. Our ontology allows us to have a uniformized representation of the potential anomalies that a system and its elements can face. Based on this representation, a decision-making process takes place to avoid potential conflicts between safety and cybersecurity, in order to best handle their interdependency. The results of our implementation show that our ontology handles the safety and cybersecurity interdependency, and has little impact on decision-making time, which makes it an effective methodology for NFV framework. read more... read less...
Keywords: Safety ontology, NFV safety architecture, Safety and cybersecurity interdependency
Enhancement of the TSCH-Sim Simulator via Web Service Interface to Support Co-simulation Optimization
JUSPN, volume-18 , Issue 2 (2023), PP 69 - 76
Published: 02 Apr 2023
by Tarana Ara, Aida Vatankhah, Ramiro Liscano from Ontario Tech University, Oshawa, Canada, L1G 0C5
Abstract: Co-simulation is an important concept in the optimization of computer networks because a typical optimization scenario integrates an optimization algorithm with a network simulator. In many cases optimization algorithms are implemented in the MATLAB environment while network simulators are implemented as stand alone applications. In this paper we present enhancements to the TSCH-Sim network simulator in order to facilitate its integration with an optimization algorithm. The core enhancement is the definitions and implementation of a set of REST APIs for TSCH-Sim that allows a remote optimization algorithm to set the network configuration, routes, and 802.15.4e TSCH schedule of a sensor network. The significance of the REST API is demonstrated through the integration of a Differential Evolution based TSCH scheduling optimizer executing in MATLAB leveraging the TSCH-Sim simulator through the REST APIs in order to find a TSCH schedule that maximizes throughput. read more... read less...
Keywords: 802.15.4e TSCH, TSCH-Sim, REST-API, Co-simulation, DE Optimization, MATLAB Simulation
Combining the Internet of Things (IoT) and the Internet of Behavior (IoB) to create a robust educational environment
JUSPN, volume-18 , Issue 2 (2023), PP 61 - 68
Published: 02 Apr 2023
by Ossama H. Embarak from Higher Colleges of Technology Dept. of Computer Sciences, Fujairah, UAE
Abstract: The ongoing COVID-19 pandemic has accelerated the adoption of e-learning, remote learning, and hybrid models in education. These models have become essential in meeting the demands of smart cities and addressing the limitations of traditional distance learning. However, to truly achieve academic success, education must be adaptive and tailored to the individual needs of students. This study presents a novel concept for intelligent educational systems that integrate Explainable Artificial Intelligence (XAI) and Internet of Behavior (IoB) technologies. The integration of these technologies aims to revolutionize intelligent educational systems by providing a more personalized and effective learning experience. By collecting and analyzing student behavior data, the system can provide real-time feedback and adjust to meet the needs of each individual student. The results of this study demonstrate the significant impact of IoB technology on student performance. The integration of IoB led to a substantial increase in student response from 40% to 79%. These findings highlight the potential for IoB to enhance learner assistance and improve system modifications to better meet the expectations of students for increased performance. The proposed concept of integrating XAI and IoB technologies in intelligent educational systems can pave the way for a more personalized and effective learning experience in the future. read more... read less...
Keywords: Tailored education, Hybrid models, Smart cities, XAI (Explainable Artificial Intelligence), IoB (Internet of Behavior) Personalized education Adaptive learning
JUSPN, volume-18 , Issue 2 (2023), PP 49 - 59
Published: 02 Apr 2023
by Mohammad Moshawrab, Mehdi Adda, Abdenour Bouzouane, Hussein Ibrahim, Ali Raad from Département de Mathématiques, Informatique et Génie, Université du Québec à Rimouski, 300 Allée des Ursulines, Rimouski, G5L 3A1, Québec, Canada, Département D’informatique et de Mathématique, Université du Québec à Chicoutimi, Chicoutimi, 555 boulevard de l’Université, Chicoutimi, QC G7H 2B1, Canada, Institut Technologique de Maintenance Industrielle, 175 Rue de la Vérendrye, Sept-Îles, G4R 5B7, Québec, Canada and Dean of the Faculty of Science and Arts, Islamic University of Lebanon, Wardaniyeh, Lebanon
Abstract: Artificial Intelligence (AI) is increasingly becoming a potential answer to many of science’s most challenging problems. In this context, healthcare is using this technology and its advancement to improve the quality of services provided, including cardiac healthcare services. According to studies, Cardiovascular Diseases (CVDs) are among the most common and deadly diseases in the world. However, Artificial Intelligence and its branches such as Machine Learning (ML) and Deep Learning (DL) offer tremendous potential to improve disease diagnosis and even predict its occurrence. In this study, eight Machine Learning and Deep Learning models are created and trained with "PhsyioNet Smart Health for Assessing the Risk of Events via ECG Database" to analyze the characteristics of Heart Rate Variability and predict the occurrence of heart disease and cerebrovascular events. The results support the use of Artificial Intelligence in cardiology, with five of the proposed models outperforming previous implementations. Specifically, Support Vector Machines, TabTransformers, Deep Neural Networks, AdaBoost, and XGBoost achieved accuracy rates of 91.80%, 90.38%, 90.19%, 89.50%, and 89.10%, respectively. Further performance metrics are presented throught the article such as precision, recall and others. read more... read less...
Keywords: Artificial Intelligence, Machine Learning, Deep Learning, Cardiovascular Diseases, Heart Rate Variability
JUSPN, volume-18 , Issue 1 (2023), PP 39 - 48
Published: 22 Jan 2023
by Arshin Rezazadeh, Davood Abednezhad, Hanan Lutfiyya from Computer Science Department, Western University, London ON N6A 3K7 Canada, Information and Communications Technology, Khouzestan Oxin Steel Company, Ahvaz, Iran
Abstract: User-Equipments (UEs) capable of working with cloud computing have grown exponentially in recent years, leading to a significant increase in the amount of data production. Moreover, upcoming Internet-of-Things (IoT) applications such as virtual and augmented reality, video streaming, intelligent transportation, and healthcare will require low latency, communications, and processing. Edge computing is a revolutionary criterion in which dispersed edge nodes supply resources near end devices because of the limited resources available on UEs. Rather than transmitting massive amounts of data to the cloud, edge nodes could filter, analyze, and process the data they receive using local resources. Mobile Edge Computing (MEC), in particular, when user mobility is considered, has the potential to significantly reduce processing delays and network traffic between UEs and servers. This research demonstrated a novel technique for migration that minimizes delay and downtime by utilizing edge computing. Our proposed method syncs more frequently than the pre-copy method which is the most used migration method that synchronizes (sync) the source and destination only based on multiple rounds. When compared to established migration methodologies, our results indicate that our mechanism has less latency, downtime, migration time, and packet loss. These results allow delay-sensitive applications that require ultra-low latency to function smoothly during migration. read more... read less...
Keywords: delay (latency), mobile edge computing (MEC), downtime, hand-off (handover), live migration, fog computing
JUSPN, volume-18 , Issue 1 (2023), PP 31 - 38
Published: 17 Jan 2023
by Salam Traboulsi, Dieter Uckelmann from Stuttgart University of Applied Sciences, D-70174 Stuttgart, Germany
Abstract: The new 5G mobile network promises to enhance existing services or include new ones to address key challenges presented by smart city stakeholders (citizens, municipalities, politics, industries, architects, etc.) to improve system implementations. These challenges cover various smart city fields such as transportation, environmental monitoring, healthcare, industrial automation, smart grid, etc. Thus, the main objective of 5G functionalities is to provide solutions to the various identified needs, which are defined as constraints and requirements. Therefore, three categories of 5G-based use cases have been defined: Enhanced Mobile Broadband (eMBB), Massive Machine Type Communications (mMTC), and Ultra-reliable and Low Latency Communications (uRLLC). Each group involves a set of use cases and characterized by specific technical features that address the corresponding needs. However, accurate and real-time positioning information is a vital requirement common to all three categories, but the degree of performance varies across scenarios and descriptions. Therefore, this work presents a summary of existing positioning technologies crossed with wireless technologies and smart city use cases to highlight the potential that will add accurate and real-time positioning to 5G capabilities. 5G promises decimeter accuracy in some critical use cases. read more... read less...
Keywords: 5G, Positioning methods, Smart city
A Study of the Ambient Noise in the Public Space on Campus and the Correlation Between the Campus Crowds’ Ambient Noise and the WiFi Log
JUSPN, volume-18 , Issue 1 (2023), PP 23 - 30
Published: 16 Jan 2023
by Yun Jie Lim, Seanglidet Yean, Bu Sung Lee, Peter Edwards from School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Ave, 639798, Singapore and Manaaki Whenua – Landcare Research, Box 10345, The Terrace, 6143, Wellington, New Zealand
Abstract: Urban noise is becoming more serious and increasingly concerning environmental problems. This has led to numerous studies on traffic noise. However, not many studies have been done on noise from a human perspective as they go about their daily life. In another aspect, using of the crowd-sourcing platform is on the rise as the usage of personal devices (smartphones) and the deployment of Internet-of-thing increases. Thus, a large pool of data collected via mobile applications enables users to measure the environmental factor directly and provide immediate feedback for and community’s greater good. In this paper, we utilize the crowd-sourcing platform to collect noise data by volunteers to study the noise level in a campus environment, in open common areas which are frequented by students. We are able to map out the noise across the campus from the perspective of the students. The noise level increase through the day as the student gather around popular open spaces. Our study shows that the sound level on campus is due mainly to human and mechanical noise. By combining the noise data with WiFi log data, we were able to show a good correlation between sound level and human density in an area. read more... read less...
Keywords: sound level, ambient noise, environmental noise monitoring, environmental noise analysis, urban noise