Native Applications Research Articles

Prototype for Multi-UAV Monitoring–Control System Using WebRTC

Most unmanned aerial vehicle (UAV) ground control station (GCS) solutions today are either web-based or native applications, primarily designed to support a single UAV. In this paper, our research aims to provide an open, universal framework intended for rapid prototyping, addressing these objectives by developing a Web Real-Time Communication (WebRTC)-based multi-UAV monitoring and control system for applications such as automated power line inspection (APOLI). The APOLI project focuses on identifying damage and faults in power line insulators through real-time image processing, video streaming, and flight data monitoring. The implementation is divided into three main parts. First, we configure UAVs for hardware-accelerated streaming using the GStreamer framework on the NVIDIA Jetson Nano companion board. Second, we develop the server-side application to receive hardware-encoded video feeds from the UAVs by utilizing a WebRTC media server. Lastly, we develop a web application that facilitates communication between clients and the server, allowing users with different authorization levels to access video feeds and control the UAVs. The system supports three user types: pilot/admin, inspector, and customer. Our research aims to leverage the WebRTC media server framework to develop a web-based GCS solution capable of managing multiple UAVs with low latency. The proposed solution enables real-time video streaming and flight data collection from multiple UAVs to a server, which is displayed in a web application interface hosted on the GCS. This approach ensures efficient inspection for applications like APOLI while prioritizing UAV safety during critical scenarios. Another advantage of the solution is its integration compatibility with platforms such as cloud services and native applications, as well as the modularity of the plugin-based architecture offered by the Janus WebRTC server for future development.

Validity and Reliability of a Commercially Available Inertial Sensor for Measuring Barbell Mechanics during Weightlifting

This study aimed to assess the validity and reliability of a commercially available inertial measurement unit (Enode) for measuring barbell kinematics and kinetics during a snatch. In order to assess validity and within- and between-session reliability, thirteen competitive weightlifters conducted two snatches on two separate occasions at 85% of their one-repetition maximum. The Enode sensor was attached to the barbell, with each lift recorded via the device’s native application concurrently with an 11-camera motion capture system. Passing–Bablok regression indicated fixed and proportional bias in some horizontal measures of barbell mechanics but showed no bias in all but one vertical variable. Collectively, this suggests that the Enode is a valid tool in the measurement of vertically derived, but not horizontally derived, variables from barbell kinematics. Within- and between-session reliability showed moderate to excellent ICCs, with trivial to small differences between repetitions and between sessions. However, between-session reliability showed lower levels of variability and, thus, may help coaches identify changes in technique over time (between sessions) with good accuracy. Overall the Enode offers a practical and affordable option for coaches seeking to monitor weightlifting technique in training environments.

Efficient Resource Allocation in Kubernetes Using Machine Learning

Kubernetes is a distinguished open-source container orchestration system in cloud computing and containerized applications. Google developed it, and the Cloud Native Computing Foundation now maintains it. Kubernetes offers a robust framework for automating application deployment scaling and management, revolutionizing how organizations use their containerized workloads and providing huge flexibility and feasibility. The current paper explores the application of machine learning algorithms to optimize resource allocation in Kubernetes environments. As the complexity of cloud-native applications increases because of various engagements, it is vital to maintain performance and cost- effectiveness. This study also evaluates various machine learning models and techniques and their relevancy in areas such as anomaly detection and enhancing overall cluster utilization. Our findings include machine learning-driven methodologies that will significantly improve performance utilizing historical data. Kubernetes's decentralized nature requires a scalable structure for task scheduling to accommodate dynamic workloads conveniently. The AIMD algorithm, a celebrated method for congestion avoidance in network management, inspires our approach. Computing clusters can be challenging to deploy and manage due to their complexity. Monitoring systems collect large amounts of data, which is daunting to understand manually. Machine learning provides a viable solution to detect anomalies in a Kubernetes cluster. KAD (Kubernetes et al.) is one such algorithm that can solve the Cluster anomalies problem. Enormous Cloud native applications market is projected to reach 17.0 billion USD by 2028, which was USD 5.9 billion in 2023. On par with those numbers is the global Machine Learning (ML) market size, which was valued at $19.20 billion in 2022 and is expected to grow from $26.03 billion in 2023 to $225.91 billion by 2030 (As per Fortune Business Insights). At the conjecture, both markets will take innovation to a new level, offering more adaptive solutions for contemporary cloud infrastructures.

Spacelord : Private and Secure Smart Space Sharing

Space sharing services like vacation rentals and meeting rooms are being equipped with smart devices such as cameras, door locks and many other sensors. However, the sharing of such devices poses privacy and security problems, as there is typically no clear control transfer between owners and users. In this article, we propose Spacelord , a system to time-share smart devices contained in a shared space privately and securely while allowing users to configure them. When a user stays at a space, Spacelord ensures that the smart devices contained in it run code and configurations the user trusts while removing pre-installed code and configurations. When the user leaves the space, Spacelord reverts any changes the user has introduced to the smart devices, deletes any remaining private data and lets the owner take back control over the devices. We evaluate Spacelord for two realistic space-sharing cases—smart home and coworking meeting room—and observe smart space provisioning delays of ~82sacross three different platforms. Moreover, the average runtime overhead of our system varies from 7.8% to 11.8% across different hub hardware, running native applications.

The Implementation of PWA (Progressive Web App) Technology in Enhancing Website Performance & Mobile Accessibility

The implementation of PWA as a necessary feature aims to provide added value and enhance website performance. This is intended to address several common issues in websites, such as limitations in displaying pages offline and the cost of developing native applications across various operating system platforms, both for desktop and mobile devices. Data collection methods involve literature studies and direct measurements using various tools. Testing conducted includes installation testing, evaluation of PWA criteria, performance, size of transferred resources, and offline mode. Components used in PWA include the web app manifest, service worker, and cache storage. PWA implementation involves creating a web app manifest, service worker registration, service worker configuration, adding script tags, creating specific routes within the website using Express.js, and PWA testing. Test results indicate that the website can be installed and used effectively on various types of devices, both mobile and desktop, and can be accessed in offline mode or with unstable connections.

A software-defined connectivity service for multi-cluster cloud native applications

Containerization technologies have risen in popularity for deploying microservices applications in cloud-native environments, offering the benefits of traditional virtualization with reduced overhead. However, existing container networking solutions lack support for applications requiring isolated link-layer communications among containers in different clusters. These communications are fundamental to enable the seamless integration of cloud-native solutions in 5G and beyond networks. Accordingly, we present an SDN-enabled networking solution that supports the creation of isolated link-layer virtual networks between containers across different Kubernetes clusters by building virtual circuits that dynamically adapt to changes in the topology. In this article, we introduce our solution, highlighting its advantages over existing alternatives, and provide a comprehensive design overview. Additionally, we validate it through an experiment, offering a deeper understanding of its functionality. Our work fills an existing gap for applications with inter-cluster link-layer networking access requirements in the cloud-native ecosystem.

Exploring the impact of chaos engineering with various user loads on cloud native applications: an exploratory empirical study

One of the most popular models that provide computer resources today is cloud computing. Today’s dynamic and successful platforms are created to take advantage of various resources available from service providers. Ensuring the performance and availability of such resources and services is a crucial problem. Any software system may be subject to faults that might propagate to cause failures. Such faults with the potential of contributing to failures are critical because they impair performance and result in a delayed reaction, which is regarded as a dependability problem. To ensure that critical faults can be discovered as soon as possible, the impact of such faults on the system must be tested. The performance and dependability of cloud-native systems are examined in this empirical study using fault injection, one of the chaos engineering techniques. The study explores the impacts and results of injecting various delay times into two cloud-native applications with diverse user numbers. The performance of the applications with various numbers of users is measured in relation to these delays, which accordingly reflects measuring the dependability of those systems. Firstly, the systems’ architecture were identified, and serverless with two Lambda functions and containerised microservices applications were chosen, which depend on utilising and incorporating cloud-native services. Secondly, faults are injected in order to quantify performance attributes such as throughput and latency. The results of several controlled experiments carried out in real-world cloud environments provide exploratory empirical data, which promoted comparisons and statistical analysis that we utilised to identify the behaviour of the application while experiencing stress. Typical results from this investigation include an overall reduction in performance that is embodied in an increase in latency with injecting delays. However, a remarkable result is noticed at a particular delay in which defects and availability problems appear out of nowhere. These findings assist in highlighting the value of using chaos engineering in general and fault injection in particular to assess the dependability of cloud-native applications and to find unpredicted failures that could arise quickly from defects that aren’t supposed to spread and result in dependability issues.

Flood Risk Assessment of the Middle Reach of the Helmand River, Afghanistan

The middle reach of the Helmand River is prone to floods, and flood hazard analysis is necessary to manage the flood risk. As the study site is a less-developed basin where available geographical and hydrological data are limited, we must utilize available limited data to conduct the flood hazard analysis. A frequency analysis of the annual peak flow rate was performed using available hydrological data for making representative flood hydrographs. A land-use map is derived by classifying recent Landsat images. Digital elevation model derived by Advanced Land Observing Satellite, roughness coefficient correlated with the land-use map, and the representative flood hydrographs are fed into hydraulic model HEC-RAS 2D. Flood inundation area, depth, and velocity for different flood return periods are estimated. Based on local hazard intensity and vulnerability, risk maps for evacuation and vulnerability of crops on the floodplain are obtained. Spatial flood risk characteristics differ at the upstream and downstream reaches because of distinct floodplain topography. Flood countermeasures for each reach are proposed based on the spatial characteristics of the flood risk. To provide risk information for residents within the region, the flood hazard, risk, and damage maps derived in this study are published as a web map application and a mobile native application.

Design and Implementation of Educonnect: A Cloud Native Application for Educational Institutions

Abstract: In modern software environments, a paradigm known as the MERN stack has emerged as an important force due to its breadth of development and management capabilities. Leveraging native MERN (MongoDB, Express.js, React.js, Node.js) software development, deployment, and management techniques with Cloud services, "Educonnect" emerges as an innovative solution for educational institutions seeking efficient and cost-effective data management. This paper deals with the implementation of a cloud native web application Educonnect after a dexterous development strategy to create a cloud native web application. The main focus of this cloud native application is to provide a solution for data organization and collection along with an effective way of sending communication to the students by using cloud services

Design and Implementation of a Cloud Native Application for Collaborative Learning

Abstract: In the current landscape of education technology, the incorporation of Cloud Native Architecture has emerged as a transformative force. This paper describes the meticulous design and implementation of a groundbreaking application: a Cloud Native Platform for Collaborative Learning. Using the powerful MERN stack (MongoDB, Express.js, React.js, and Node.js), this platform represents a paradigm shift in how modern education ecosystems are built. The application offers a seamless, usercentric experience that promotes collaborative learning across multiple educational dimensions. The platform encapsulates the essence of holistic and technology-driven education, featuring interactive learning paths, an integrated coding environment, rich project repositories, academic note storage, access to past papers, and an extensive research paper database. As we delve into the key features and developmental intricacies, it becomes clear that this Cloud Native Application for Collaborative Learning is poised to transform the educational landscape. This paper provides a comprehensive overview of this cutting-edge application's innovative design principles, development methodologies, and transformative potential.

Unleashing Potential: Snowflake's Streamlit Strategy for GenAI Solutions Leveraging External Network Access and OpenAI

This whitepaper explores the synergy between Snowflake's External Network Access, OpenAI, and Streamlit, presenting a groundbreaking approach to data analysis and interaction. By seamlessly integrating these technologies, organizations can unlock new dimensions of insight and efficiency in their data workflows. We delve into the configuration of External Network Access in Snowflake, the creation of Snowpark stored procedures for interacting with external services like OpenAI, and the development of user-friendly native applications with Streamlit. This innovative solution empowers users to access, analyze, and communicate with their data stored on Snowflake with unparalleled ease and sophistication, revolutionizing data-driven decision-making processes. Keywords: Snowflake, Streamlit, Generative AI , Open AI, Snowflake External Network Access

Cloud in Developing Native Applications

Cloud in Developing Native Applications

Research and Implementation of Container Based Application Orchestration Service Technology

With the rapid development of cloud computing technology, Kubernetes(K8S), as the main orchestration tool for cloud native applications, has become the preferred choice for enterprises and developers. This article is based on container based application orchestration service technology. Through a set of templates containing cloud resource descriptions, it quickly completes functions such as application creation and configuration, application batch cloning, and application multi environment deployment. It simplifies and automates the lifecycle management capabilities required for cloud applications, such as resource planning, application design, deployment, status monitoring, and scaling. Users can more conveniently complete infrastructure management and operation and maintenance work, In order to focus more on innovation and research and development, and improve work efficiency. The actual application effect of the technology used in this article depends to a certain extent on the ability level of basic service resources, and manual template creation is required for the first use. In production use, a certain professional ability is required to create a good application layout template, adjust and optimize resources according to the production environment, in order to significantly improve the effectiveness and efficiency of practical applications.

Digital Natives and Signalling in Employment Interviews: An Inquiry into the Acceptance and Perceived Fairness of Different Interview Modes

The paper investigates the signalling behaviour of digital native applicants in employment interviews and analyses how their reactions differ in face-to-face versus video-mediated contexts. The social presence within the interview setting and the possibility of employing impression management tactics are of particular interest to understanding the subjective acceptance and perceived fairness of the two types of selection procedures. The analyses of novel primary data from a German survey with 513 valid responses reveal that digital natives, similar to older applicants, appreciate signalling to lower information asymmetries. Regardless of interview mode, social presence and impression management are strong positive drivers of acceptance and perceived fairness. While members of the generational cohort still accept face-to-face interviews more than those mediated by videoconferencing technology, they perceive the former as less fair. This result, which may be explained by the specific characteristics of digital natives, contradicts the findings of studies that have investigated preceding generations. Hence, the paper complements the literature on applicant reactions by focusing on two younger generational cohorts, namely Generation Y and Z. Furthermore, the adoption of the signalling framework in this context suggests that the beneficial effects of signalling may stand vis-à-vis feelings of unfairness, which can be interpreted as additional psychological costs that are driven by moral considerations.

Integration of processes related to the implementation of the mediGOAT platform in diabetic patient care.

Diabetes has always been viewed through the prism of the fact that any expenditure in this area is a threat to the budget of the entire health care system. Most often it is the progress of science that forces integration activities. An example may be the integration processes related to the implementation and creation of the mediGOAT platform, which are focused on its multi-functionality, i.e. the ability to connect many different measuring devices (Glucometer, CGM, SmartPen, Insulin Pump, GlucoActive) from many manufacturers. They are made up of smaller particles with their own rules and goals, such as engaging and evaluating activities. We meet with this, among others by implementing good practices.
 As a result, such activities give the user more choice and independence from many native applications (manufacturers), and it enables cooperation with Google Health and iHealth (Apple). This makes it possible to use additional information provided by External Applications (meals, exercise, pressure, weight, ...) in the treatment process. In addition, it allows you to collect and store your medical records (including the results of medical tests). The indicated/selected medical/health data (in the future on-line measurements) can be provided to the doctor via the Portal, ensuring security (login via Apple and Google, Backup) and ease of use.
 Additional knowledge is written at various levels of detail, scattered in different places, its origin is sometimes uncertain, which makes it unreliable. It is often oversized where it is not necessary, and various sources can contradict each other. Therefore, it is important to use trusted sources. Controlling blood glucose levels is important, as are the circumstances surrounding such a measurement, what you do and where you are. Mobile Continuous Glucose Monitoring, using CGM, enables up to 288 readings per day, giving you insight into information that fingerstick tests cannot match. CGM provides real-time glucose readings every five minutes throughout the day and night, notifying you of high and low values. The sensor continuously measures the glucose level just below the skin and transmits the data wirelessly to the display device via the transmitter. This enables an immediate reaction. A discreet sensor placed just under the skin (the automatic applicator introduces the sensor just under the skin with one press) measures the glucose level for the time specified by the manufacturer. Glucose data is sent wirelessly to the analysing and smart device via Bluetooth® or NFC technology. Such a device can be a compatible smartphone or other optional receiver that displays and archives glucose data in real time.

Impact of Secure Container Runtimes on File I/O Performance in Edge Computing

Containers enable high performance and easy deployment due to their lightweight architecture, thus facilitating resource utilization in edge computing nodes. Secure container runtimes have attracted significant attention because of the necessity for overcoming the security vulnerabilities of containers. As the runtimes adopt an additional layer such as virtual machines and user-space kernels to enforce isolation, the container performance can be degraded. Even though previous studies presented experimental results on performance evaluations of secure container runtimes, they lack a detailed analysis of the root causes that affect the performance of the runtimes. This paper explores the architecture of three secure container runtimes in detail: Kata containers, gVisor, and Firecracker. We focus on file I/O, which is one of the key aspects of container performance. In addition, we present the results of the user- and kernel-level profiling and reveal the major factors that impact the file I/O performance of the runtimes. As a result, we observe three key findings: (1) Firecracker shows the highest file I/O performance as it allows for utilizing the page cache inside VMs, and (2) Kata containers offer the lowest file I/O performance by consuming the largest amount of CPU resources. Also, we observe that gVisor scales well as the block size increases because the file I/O requests are mainly handled by the host OS similar to native applications.

An empirical study on the performance and energy costs of ads and analytics in mobile web apps

Context:As the use of mobile devices has increased immensely through the years, the presence of analytics and advertisements on web and native applications has become prevalent. However, serving ads and analytics comes with costs, as they are associated with additional code and network requests to execute properly. Subsequently, more computing resources are used, having an impact on the energy consumption and the performance of web applications. Previous work has focused only on native Android applications, has used different metrics for performance, or has focused on other aspects of web applications. Goal:This paper aims to investigate the costs of including advertisements and analytics in web applications. This is done in terms of energy consumption and performance. For energy, the consumption is measured in Joules. For performance, the following metrics are used: first contentful paint and full page load time. The results of this study could influence the decisions of web developers and web browser vendors related to ads and analytics usage, while providing the foundation for further research on this topic. Method:To collect reliable and population-representative results, the research focused on 9 popular web applications included in the Tranco list. Energy consumption and performance metrics were gathered for 3 versions of each web application — original version with ads and analytics, without ads, and without analytics. A cross-over paired comparison design is conducted. Multiple executions of each run were performed in random order to ascertain rigorous measures. The experiment is carried out on an Android tablet using two browsers, Google Chrome and Opera. Results:Ads significantly impact the energy consumption of mobile web apps for both browsers, with a large effect size; analytics have a significant impact on the energy consumption of Chrome (with a medium effect size), but not on Opera. In terms of performance, both ads and analytics do not significantly impact the first contentful paint metric on both browsers; differently, both ads and analytics significantly impact the full page load time of the mobile web apps on both browsers, but with a small effect size. Conclusions:This study provides evidence that both ads and analytics can have a significant impact on the energy consumption and performance of mobile web apps loaded either on Opera or Chrome. Depending on the requirements of the mobile web app, it is advisable to limit both ads and analytics in a mobile web app in order to reduce its energy consumption and improve its full page load time. Special attention should be paid to the presence of ads since they resulted to be the most impactful in terms of energy consumption.

Synapse: interactive support on photoemission spectroscopy measurement and analysis for non-expert users.

Photoemission spectroscopy, an experimental method based on the photoelectric effect, is now an indispensable technique used in various fields such as materials science, life science, medicine and nanotechnology. However, part of the experimental process of photoemission spectroscopy relies on experience and intuition, which is obviously a problem for novice users. In particular, photoemission spectroscopy experiments using high-brilliance synchrotron radiation as a light source are not easy for novice users because measurements must be performed quickly and accurately as scheduled within a limited experimental period. In addition, research on the application of information science methods to quantum data measurement, such as photoemission spectroscopy, is mainly aimed at the development of analysis methods, and few attempts have been made to clarify the problems faced by users who lack experience. In this study, the problems faced by novice users of photoemission spectroscopy are identified, and a native application named synapse with functions to solve these problems is implemented and evaluated qualitatively and quantitatively. This paper describes the contents of an interview survey, the functional design and the implementation of the application synapse based on the interview survey, and results and discussion of the evaluation experiment.

RShare: Alleviating long startup on the Cloud-rendering platform through de-systemization

WebGL paves the way for the great development of lightweight rendering applications (e.g., web games). However, the target audience of Cloud-rendering frameworks (e.g., Google Stadia and gRemote) mainly focuses on native applications, called traditional Cloud-rendering frameworks. Even though traditional frameworks cover all the rendering functionalities and both light- and heavy-weight applications can run on them, such frameworks face long startup latency, imposing a significant challenge on lightweight applications. To reduce the startup latency, many researchers render objects locally, but the system-level redundancy still affects the performance of lightweight rendering applications negatively (especially in the application-initialized stage).In this paper, we propose rShare, a new rendering framework dedicated to lightweight applications. To reduce the startup latency of lightweight applications, rShare desystemizes the entire user space into the transmitted protocol. To ensure the portability of the entire system, rShare establishes two vHALs (virtual Hardware Abstraction Layer) (i.e., peripheral vHAL and rendering vHAL) within the protocol. To boost the CPU running efficiency at the initialized stage, rShare establishes an optimized mechanism called flexTLB, allowing various page sizes to work together. The experiments show that rShare can improve the CPU executing efficiency by 20%∼50% and reduce 90% startup latency compared to the CARE, a traditional Cloud-rendering framework proposed by Intel.

A Web Based Coupons Recommendation System for Applicable Users in Friend Zone

Presently, every individual is using digital payment platforms like Google Pay, PhonePe, Paytm, Amazon Pay. Whenever a person does online transactions, he/she get coupons as a reward for couple of transactions. These coupons can vary from one another. Sometimes they are discounts or cashbacks or else vouchers. Every person who uses the digital payment systems will not be able to use every single coupon he/she received. So, instead of letting that coupon expire we are developing an android- based application, where the user can form groups with contacts of his/her choice in order to share their coupons. People can exchange the coupons among each other in the group. Also, when two people share their coupons that belong to same company, the application prioritizes and recommends the coupon which expires early. Also, to overcome the problem of a person entering details of coupons our app will remind the users to update the coupons in his profile. Also, to share the coupons which can't be directly shared a module is included such that a request message will be sent to the user and if the user accepts it can be gifted from native application