Wi-Fi Networks Research Articles

On the Fairness of Internet Congestion Control over WiFi with Deep Reinforcement Learning

For over forty years, TCP has been the main protocol for transporting data on the Internet. To improve congestion control algorithms (CCAs), delay bounding algorithms such as Vegas, FAST, BBR, PCC, and Copa have been developed. However, despite being designed to ensure fairness between data flows, these CCAs can still lead to unfairness and, in some cases, even cause data flow starvation in WiFi networks under certain conditions. We propose a new CCA switching solution that works with existing TCP and WiFi standards. This solution is offline and uses Deep Reinforcement Learning (DRL) trained on features such as noncongestive delay variations to predict and prevent extreme unfairness and starvation. Our DRL-driven approach allows for dynamic and efficient CCA switching. We have tested our design preliminarily in realistic datasets, ensuring that they support both fairness and efficiency over WiFi networks, which requires further investigation and extensive evaluation before online deployment.

Development of the "Mother Give Me Exclusive Breastfeeding" e-booklet based on Android as a nutrition educational media

Undernutrition is one of the most serious and least addressed challenges worldwide. The significant relationship between this condition and children's feeding practices makes exclusive breastfeeding an early and appropriate intervention. Therefore, this study aimed to develop health promotion media in the form of an Android-based booklet titled "Mother Give Me Exclusive Breastfeeding".The development method model adopted was ADDIE (Analysis, Design, Development, Implementation, Evaluation). A total of 20 mothers of toddlers participated in product feasibility testing.The results showed that the product had an average total percentage of 80%, signifying high suitability for usage. The study subjects rated the E-Booklet very positively, showing great enthusiasm for engaging with the content presented in the "Mother Give Me Exclusive Breastfeeding" E-Booklet.In conclusion, further study was needed to maximize the role of this product in enhancing mothers' understanding of exclusive breastfeeding and ensuring access to facilities such as gadgets, technology devices, and internet or wifi networks.

Smart Home

The concept of a smart home integrates wireless electronic systems that connect household devices to a central interface, enabling remote control via smartphones or wall panels through Wi-Fi networks. This paper explores the core components of smart homes, including smart devices such as speakers, thermostats, lighting, and security systems, as well as the role of mobile applications in managing these devices. The paper discusses the various applications of smart homes, from home automation and security monitoring to energy management and health-focused initiatives. Additionally, it evaluates the pros and cons of smart home technology, highlighting benefits such as enhanced security, energy efficiency, and user convenience, while also addressing challenges related to cost, complexity, and cybersecurity risks. The paper concludes by emphasizing the transformative potential of smart homes in modern living, while recognizing the need for strategic approaches to mitigate associated challenges.

Wi-Fi QoS Management Program: Bridging the QoS Gap of Multimedia Traffic in Wi-Fi Networks

Wi-Fi QoS Management Program: Bridging the QoS Gap of Multimedia Traffic in Wi-Fi Networks

Wi-Fi Fingerprint Indoor Localization by Semi-Supervised Generative Adversarial Network.

Wi-Fi fingerprint indoor localization uses Wi-Fi signal strength measurements obtained from a number of access points. This method needs manual data collection across a positioning area and an annotation process to label locations to the measurement sets. To reduce the cost and effort, this paper proposes a Wi-Fi Semi-Supervised Generative Adversarial Network (SSGAN), which produces artificial but realistic trainable fingerprint data. The Wi-Fi SSGAN is based on a deep learning, which is extended from GAN in a semi-supervised learning manner. It is designed to create location-labeled Wi-Fi fingerprint data, which is different to unlabeled data generation by a normal GAN. Also, the proposed Wi-Fi SSGAN network includes a positioning model, so it does not need a external positioning method. When the Wi-Fi SSGAN is applied to a multi-story landmark localization, the experimental results demonstrate a 35% more accurate performance in comparison to a standard supervised deep neural network.

Hardware-software implementation of a local Wi-Fi network for the transmission of biomedical signals

The object of this study is a wireless local Wi-Fi network for broadcasting biomedical signals, its structure, and principles of construction. The task of minimizing the power consumption of a Wi-Fi transmitter has been addressed, which provides the possibility of building a wireless system for long-term monitoring of biomedical signals. As a result, a functional diagram of a wireless Holter monitoring system based on an ESP32 microcontroller was constructed, which includes a subsystem for setting up and diagnosing system units using MATLAB software packages, an ECG signal generator, and a multifunctional PCIe board from National Instruments. Evaluation criteria and methods for minimizing power consumption by an autonomous Wi-Fi transmitter have been proposed. Methods for synchronizing the working cycles of the transmitter and receiver of the Holter monitoring system were determined. A procedure for determining the optimal biosignal measurement frequency is presented, at which the distortion of ECG signals would be minimal, which means that the signal could be transmitted without losses. The concept of constructing an algorithm for implementing a program for a Wi-Fi transmitter has been developed, ensuring parallel execution of ECG signal measurement operations and their transmission over a local network. The data from semi-naturalistic tests with an experimental Holter monitoring system with a pre-setup subsystem and using external measuring devices, a computer, and the MATLAB software environment are presented. A comparative analysis of the experimental data with primary ECG signals and ECG signals at the receiver output showed a fairly stable correspondence between the input and output ECG signals. The proposed algorithms make it possible to reduce the average current consumption of the ESP32 microcontroller to 50.5 mA. The results of the study demonstrate the possibility of constructing an energy-efficient wireless system for long-term monitoring of biomedical signals based on the Wi-Fi interface

Technological And Connectivity Conditions of Undergraduate Students of Economics, Accounting and Administrative Sciences at A Peruvian Public University

The purpose of the research was to identify the ICT and connectivity conditions of university students and how they use them in their undergraduate studies at a Peruvian public university. Data was collected from 208 students of the Professional Schools of Business Administration, Tourism Administration, Accounting and Economics enrolled in the Academic Semester 2024-1, with the support of a Google Forms survey. The results show that students mainly use laptops (90%) and cell phones (95%). They use wifi networks for their studies, 35% of them do not a c c e s s a network at the University or home. The preferred mobile operators are Claro (38.3%) and Bitel (35%). The preferred online service is Canva (48.3%). The most used social network is Facebook (88.3%), followed by Tik Tok (66.7%), Instagram (60%), YouTube (43.3%) and Twitter (25%). Technological conditions are limited to promote academic learning.

KUALITAS PELAYANAN PUBLIK PADA KANTOR KEMENTERIAN AGAMA KOTA PADANG

The research method used is descriptive qualitative research that aims to describe research conducted on natural objects. The sampling technique uses purposive sampling technique. Data collection techniques used are observation, interviews and documentation. This research was conducted at the Office of the Ministry of Religion in Padang City. The focus in this study is on public service indicators including reliability, responsiveness, assurance, empathy, tangibles.Conclusion 1.) The quality of public services at the Office of the Ministry of Religion of the City of Padang is still not good, that is, there is a guarantee that the public has doubts about the officer's promise to complete the letter given. Because it was not completed on time according to the time said by the officer. then the physical evidence in terms of the completeness of the infrastructure such as laptops, printers and other assistive devices, is further upgraded and added according to the existing officers. The wifi network is not fast enough and wifi is not provided free of charge to the public. the parking facilities are quite wide but inadequate, there is no distinction between guest parking and the officers, The waiting room is quite adequate because inside there is air conditioning and the service desk has attendants, but there are still not enough seats for people who come more than ten a day while there are ten chairs. 2.) The factors of the quality of public services at the Office of the Ministry of Religion of the City of Padang are still not good, namely in terms of existing facilities such as inadequate parking because there is no difference between guest parking and officers, and also the existing parking has been filled with vehicles officers only while guests only park outside. The waiting room inside needs to change the location and add chairs so that no one is standing in line. the waiting room outside the service desk, if there are no officers working, it's better to just remove it and add chairs and need a fan / air conditioner. For wifi, a password and token must be given for free for people who come.

Optimal channel assignment on dense Wi-Fi networks using Thermodynamic Threshold Accepting

Channel assignment in Wi-Fi 6 dense networks is a challenging problem which critically impacts the performance of WLAN communications. Although there have been many proposals in the area of IEEE 802.11 channel assignment, LCCS has emerged as the de facto standard for distributed channel selection. Notwithstanding, centralized optimizers overcome the performance of distributed channel assignment algorithms, so their study is of utmost importance. One of the most successful optimization proposals in the state-of-the-art for Wi-Fi 4 is based on simulated annealing (SA). However, SA presents a significant limitation: its parameters must be adjusted manually for each scenario, otherwise yielding suboptimal solutions. In this paper, we propose a new technique for channel assignment optimization of Wi-Fi dense networks, called Thermodynamic Threshold Accepting (TTA), including modifications inspired by Threshold Accepting (TA) and Thermodynamic Simulated Annealing (TSA). With respect to SA, TTA avoids manual tuning, being able to adapt to the specific setting automatically. We evaluate TTA in a dense Wi-Fi model and, compared to SA, we show that our approach reaches optimal results without requiring any prior fine-tuning. We also show that TTA is even able to slightly overcome the performance of an accurately calibrated SA optimizer for the same number of iterations.

Smart IoT SCADA System for Hybrid Power Monitoring in Remote Natural Gas Pipeline Control Stations

A pipeline network is the most efficient and rapid way to transmit natural gas from source to destination. The smooth operation of natural gas pipeline control stations depends on electrical equipment such as data loggers, control systems, surveillance, and communication devices. Besides having a reliable and consistent power source, such control stations must also have cost-effective and intelligent monitoring and control systems. Distributed processes are monitored and controlled using supervisory control and data acquisition (SCADA) technology. This paper presents an Internet of Things (IoT)-based, open-source SCADA architecture designed to monitor a Hybrid Power System (HPS) at a remote natural gas pipeline control station, addressing the limitations of existing proprietary and non-configurable SCADA architectures. The proposed system comprises voltage and current sensors acting as Field Instrumentation Devices for required data collection, an ESP32-WROOM-32E microcontroller that functions as the Remote Terminal Unit (RTU) for processing sensor data, a Blynk IoT-based cloud server functioning as the Master Terminal Unit (MTU) for historical data storage and human–machine interactions (HMI), and a GSM SIM800L module and a local WiFi router for data communication between the RTU and MTU. Considering the remote locations of such control stations and the potential lack of 3G, 4G, or Wi-Fi networks, two configurations that use the GSM SIM800L and a local Wi-Fi router are proposed for hardware integration. The proposed system exhibited a low power consumption of 3.9 W and incurred an overall cost of 40.1 CAD, making it an extremely cost-effective solution for remote natural gas pipeline control stations.

A distributed and cooperative signature-based intrusion detection system framework for multi-channel man-in-the-middle attacks against protected Wi-Fi networks

A Multi-Channel Man-in-the-Middle (MC-MitM) attack is an advanced form of MitM attack, characterized by its ability to manipulate encrypted wireless communications between the Access Point (AP) and clients within a WiFi network. MC-MitM attacks can target any Wi-Fi client, regardless of the authentication method used with the AP. Notable examples of such attacks include Key Reinstallation Attacks and FragAttacks, which have impacted millions of WiFi systems worldwide, especially those involving Internet of Things devices. Current defense mechanisms are inadequate against these attacks due to interoperability challenges and the need for modifications to devices or protocols within the targeted Wi-Fi networks. This paper introduces a distributed and cooperative signature-based wireless intrusion detection mechanism designed for online passive monitoring to detect malicious traffic patterns during MC-MitM attacks in any environment, from apartments and houses to large areas like hotels, offices or industrial sites. We implemented the proposed framework on Raspberry Pis and evaluated it in real-world settings. Our evaluation demonstrates that this framework can effectively identify MC-MitM attacks with an average accuracy of 98% when deployed across different locations within our experimental testbed.

Undergraduates’ experiences with library portal services: perceptions of usefulness and satisfaction

PurposeThe purpose of this study is to evaluate the perceived usefulness and satisfaction levels of undergraduate students with respect to university library portal services, specifically within selected universities in South-West Nigeria.Design/methodology/approachA descriptive survey research design was used to investigate the perceived usefulness and satisfaction levels among undergraduate students regarding university library portal services. Data were collected through surveys administered to 658 undergraduate respondents across multiple universities in South-West Nigeria.FindingsThe findings indicate that undergraduate students’ top reasons for using the portal were for tasks such as locating research materials, accessing databases, requesting bibliographies and checking the library catalog. Library computers and school information and communication technology center computers were identified as the most preferred access point, followed by computer labs and campus Wi-Fi networks. Undergraduates rated the portals as highly useful, particularly for saving time locating resources, checking material status and patronizing the library. High satisfaction was reported for services such as attending workshops, events and receiving research support through the portals workshops. Moderate satisfaction levels existed for accessing policies/hours, the institutional repository and renewals of books online. A strong positive correlation (r = 0.785, p < 0.05) was found between perceived usefulness and satisfaction.Originality/valueThis study contributes to the understanding of undergraduate students’ perceptions regarding the utility and satisfaction of university library portal services in the context of South-West Nigeria. It underscores the importance of aligning portal services with students’ academic and research needs to enhance overall satisfaction levels. In addition, it provides insights into areas where improvements can be made to further enhance the effectiveness and satisfaction derived from these services.

Enhanced-SETL: A multi-variable deep reinforcement learning approach for contention window optimization in dense Wi-Fi networks

In this paper, we introduce the Enhanced Smart Exponential-Threshold-Linear (Enhanced-SETL) algorithm, a new approach that uses the multi-variable Deep Reinforcement Learning (DRL) framework to simultaneously optimize multiple settings of the Contention Window (CW) in IEEE 802.11 wireless networks. Unlike traditional DRL methods that adjust only a single CW parameter, our innovative approach simultaneously optimizes both the CW minimum (CWmin) and CW Threshold (CWThreshold), significantly improving network traffic control. We utilize a Double Deep Q-learning Network (DDQN) for dynamic updates of these CW settings, broadcasted across the dense Wi-Fi networks. This dual adjustment method, coupled with dynamic, data-driven updates, not only enhances throughput, but also reduces collision rates, and ensures fairness access across both static and dynamic wireless environments. Enhanced-SETL achieves a throughput improvement ranging from 3.55% up to 43.73% and from 3.98% up to 30.15% in static and dynamic scenarios over standard protocols and state-of-the-art DRL models, while maintaining a fairness index near 99% across diverse stations, showcasing its effectiveness and adaptability in various network conditions.

A COMPREHENSIVE REVIEW OF DIGITALIZED ATTENDANCE SYSTEMS FOR VARIOUS INSTITUTIONS

With Technological and Digital change, it has become mandatory to keep an eye on attendance in educational and workplace settings. This change brings more novel digitalized methods of attending. The reasons behind adapting this are ways that reduce the time consumed in attendance as time wasted on attendance through the traditional pen-and-paper method. Overcoming all these limitations and to give more convenience, the development of the digitalized attendance system has come into being. These technologies use RFID sensors, Bluetooth devices, Wi-fi networks, Facial recognition, and Fingerprint decentralizing sensors that make the whole process close to error-free and very much accurate attendance tracking methods. This paper reviews the recent developments which have taken place in digitalized attendance systems by applying and incorporating relevant technology for efficiency. This presentation forms the very basis for a comprehensive analytical evaluation through an indepth exploration of technology, implementable domains, and key discoveries.

Evaluation of the IEEE 802.11aa group addressed service in VHT Wi-Fi networks

Evaluation of the IEEE 802.11aa group addressed service in VHT Wi-Fi networks

MDU-CACS: A Coordinated Forecasting-Based Cloud-Assisted Dynamic Channel Assignment Mechanism for Wi-Fi Network Clusters

MDU-CACS: A Coordinated Forecasting-Based Cloud-Assisted Dynamic Channel Assignment Mechanism for Wi-Fi Network Clusters

Design and building of a room light control System based on iot arduino cloud

The development of Internet of Things (IoT) technology opens up various opportunities to improve efficiency and convenience in various aspects of life, including in the management of electrical devices in the room. One of the innovative solutions that utilizes IoT technology is the Arduino Cloud-based room light control system using the NodeMCU ESP8266 microcontroller. This system is specifically designed to improve the efficiency of using room lights in the PLC laboratory of the Electrical Engineering department. This research aims to design and develop an Arduino Cloud-based IoT room light control system that can be controlled remotely using an Android device, PC, or laptop. NodeMCU ESP8266, as the core of this system, is a microcontroller that can connect with IoT, allowing users to control room lights via WiFi network. With this system, it is expected that users can control the PLC laboratory room lights in the Electrical Engineering department more easily, practically, and efficiently. In addition, this system is also expected to help save energy usage in the room. This research uses the method of designing and making a room light control system based on IoT Arduino Cloud. The research stages include system design, hardware and software development, and system testing. The test results show that the developed room light control system is able to turn on and off four lights in the PLC laboratory room via WiFi network using an Android device. In addition, this system is also equipped with an On/Off switch that can be used in the event of internet communication disruption. Thus, the IoT Arduino Cloud-based room light control system using the NodeMCU ESP8266 microcontroller is proven to provide convenience and efficiency for users in managing lighting in the PLC laboratory of the Electrical Engineering department, while helping to save energy.

Performance Study of the PRAW Mechanism with Slots of Arbitrary Duration in Wi-Fi HaLow Networks

Performance Study of the PRAW Mechanism with Slots of Arbitrary Duration in Wi-Fi HaLow Networks

Sistem Manajemen Baterai Pada Peralatan Catu Daya Di Equipment Room Stasiun Manggarai Dengan Aplikasi Blynk Berbasis Esp8266

This research aims to develop an efficient battery monitoring system using the ESP8266 module and INA219 sensor. Monitoring the battery condition effectively is crucial in various applications, especially in portable systems or isolated systems where real-time supervision is required. The method used in this research is the utilization of the ESP8266 module as the main microcontroller connected to the INA219 sensor to monitor the battery voltage, current, and power in real-time. The data obtained by the INA219 sensor is transmitted through the WiFi network managed by ESP8266 to a server or monitoring platform accessible to users via Blynk a web-based application or mobile application. The test results show that the system is capable of providing accurate information about the battery condition, including the charge level, usage current, and potential issues such as overcharge or undercharge. The implementation of this system is expected to be applicable in various applications, including renewable energy systems, portable devices, and electric vehicles, to improve battery performance and safety. The INA219 module as a voltage and current sensor found a voltage reading error percentage with a range of 0%-0.66% and an average of 0.18%. For readings at current with an error range of 0.91%-7.57%. For internal resistance readings which are calculated based on dividing the clamp voltage value by the circuit current, an error range of 0.04% -30.36% is found.

Adapting to Online Education: A Case Study of Resilience and Innovation in Private Tutoring During the Pandemic

During the pandemic, online-based learning faced numerous challenges, such as internet connectivity issues, difficulties in comprehension, an increase in assignments, one-sided interactions, and reduced concentration. Nevertheless, private tutoring institutions emerged as invaluable resources, enabling students to revisit lesson materials, enhance their understanding, and complete assignments effectively. This study aimed to investigate the digital transformation at Prima Utama Private Tutoring Institution in Surakarta, Indonesia, focusing on the factors that support and hinder the institution's operations, and proposing solutions to overcome these obstacles during the pandemic. Utilizing a qualitative case study approach, the research involved institutional leaders, tutors, and students as key informants. Data were collected through interviews, observations, and documentation, followed by data condensation, presentation, and conclusion drawing. The findings demonstrated the institution’s resilience through the implementation of both online and offline tutoring programs, incorporating diverse learning strategies such as lectures, interactive teaching methods, and the use of various applications. Despite technical challenges like network issues and limited technological proficiency, the interaction between tutors and students remained strong. Challenges included physical distance constraints, module availability, and promotional barriers. Proposed solutions included enhancing the Wi-Fi network, providing training on learning platforms, accessing e-modules, and developing practice questions. Additionally, the study recommended using social media, parent testimonials, and discount offers to overcome promotional challenges. Ultimately, this research offers valuable insights into the adaptation of educational institutions during the pandemic and provides recommendations for improving learning quality in an all-digital private tutoring environment.