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Load-Aware Container Orchestration on Kubernetes Clusters 14

Load-Aware Container Orchestration on Kubernetes Clusters

引用

14th International Conference on Cloud Computing and Services Science, CLOSER 2024

作者： Marchese, Angelo Tomarchio, Orazio Dept. of Electrical Electronic and Computer Engineering University of Catania Catania Italy

ISBN: (纸本)9789897587016

Microservice Architecture is quickly becoming popular for building extensive applications designed for deployment in dispersed and resource-constrained cloud-to-edge computing settings. Being a cloud-native technology, the real strength of microservices lies in their loosely connected, autonomously deployable, and scalable features, facilitating distributed deployment and flexible integration across powerful cloud data centers to heterogeneous and often constrained edge nodes. Hence, there is a need to devise innovative placement algorithms that leverage these microservice features to enhance application performance. To address these issues, we propose extending Kubernetes with a load-aware orchestration strategy, enhancing its capability to deploy microservice applications within shared clusters characterized by dynamic resource usage patterns. Our approach dynamically orchestrates applications based on runtime resource usage, continuously adjusting their placement. The results, obtained by evaluating a prototype of our system in a testbed environment, show significant advantages over the vanilla Kubernetes scheduler. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Containers

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Jumpstarting and Evolving a Software Quality Management Initiative: From Pre-Web to DevOps 16

Jumpstarting and Evolving a Software Quality Management Init...

引用

16th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2024

作者： Cusick, James J. Ritsumeikan University Dept. of Electronic and Computer Engineering Shiga Kusatsu Japan

ISBN: (纸本)9798350377903

Management of technology development requires adequate measurements. This paper discusses a broad effort to define, deploy, and adopt software quality measures, especially software reliability in an industrial setting. The industrial projects described here began before the emergence of the Web and continue to the current day. The approach and results of these quality metrics support the technical management of a variety of large-scale software platforms, their operations, and the improvement of quality across numerous iterations of development. Additionally, a comparison of classical customer oriented and dynamic software metrics with those commonly applied within Agile and DevOps environments is discussed in the context of the evolution of technology management and measurements. These metrics include Software Reliability, Test Effectiveness, and Code Coverage. Management decisioning using these metrics is traced through several real-world industrial projects across differing companies. Conclusions are linked to current trends in managing Software Development such as ITIL, Agile methods, and DevOps. © 2024 IEEE.

关键词： Software testing

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Enhancing Indoor Navigation Efficiency with WiFi Signal Mapping 15

Enhancing Indoor Navigation Efficiency with WiFi Signal Mapp...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Reddy, N. Sai Pranavdhara Narayanan, Gayathri Singh, Aman Kumar Cheeramvelil, Geo Jolly Sethulekshmi, U.S. Kumar, R. Adithya Tripathi, Akshat Amrita Vishwa Vidyapeetham Dept. Of Computer Science and Engineering Amritapuri India

ISBN: (纸本)9798350370249

In the contemporary digital landscape, efficient indoor navigation has become imperative for large, intricate spaces like shopping malls, airports, hospitals, and universities. Traditional GPS-based methods often prove inadequate in these indoor settings due to poor reception and a lack of fine-grained location accuracy. To address these challenges, the work employs WiFi signals, pervasive in modern buildings, and harnesses their ubiquity and reliability for sophisticated indoor navigation. The team developed a Python package for collecting WiFi signal details, implementing robust preprocessing to filter out private networks, and storing the data in a database. The core of the system lies in a machine learning ensemble consisting of Gaussian Bayes classifier, decision tree, and K-nearest neighbors (KNN). This ensemble utilizes WiFi signal strengths to predict users' real-time positions within large indoor spaces. The system aims to enhance user experiences and simplify wayfinding in complex indoor environments. © 2024 IEEE.

关键词： Decision Tree Gaussian Bayes Classifier Indoor Navigation K-nearest Neighbors Machine Learning Ensemble WiFi Signals

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Machine Learning based Malware Detection in Android: A Practical Approach 3

Machine Learning based Malware Detection in Android: A Pract...

引用

3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024

作者： Tyagi, Toshi Gautam, Madhu Kiet Group of Institutions Dept. of Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9798350384598

Today's society heavily depends on online communities, which host a wide variety of social networks and public and private services. These demands led to the creation of Android, the world's most popular mobile operating system. The wide range of features and capabilities offered by freely installable third-party apps is largely responsible for this success. While focusing on the positive aspects of technology use, it is vital to keep in mind the potential negative consequences like privacy breaches, data theft, and malware infections that could compromise personal information and device security, especially if negligence or overuse of technology is present. This article discusses a systematic review of ML-based Android malware detection techniques. It provides a critical analysis of a number of carefully selected articles, highlighting their methods and conclusions. To support this study, we also present our own analysis and findings, for which an evaluation of diverse ML models with 123,453 applications and 5,560 malware samples from the DREBIN dataset was done to classify apps as malicious and benign. Preprocessing was done on the dataset to address missing values and perform label encoding. To cope with the issue of class imbalance, we used SMOTE an efficient ML technique that handles imbalance issues efficiently. We have applied five different ML algorithms, The results show that among all the techniques, Decision Tree (DT), Support Vector Machines (SVM) with various kernels (linear, polynomial, RBF), Sequential Neural Network (NN), K-Nearest Neighbours (KNN), and Logistic Regression (LR), the sequential neural network model outperformed other methods with 99% accuracy. Additionally, the process identifies areas for future research and improvement in ML-based Android malware detection techniques. © 2024 IEEE.

关键词： Android malware

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Direction-Selective Parallel Module Structure for Cascaded Bridge and Modular Multilevel Converters with Minimum Transistor Count 50

Direction-Selective Parallel Module Structure for Cascaded B...

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Zhang, Jinshui Goetz, Stefan M. Dept. Electrical & Computer Engineering Duke University Durham United States

ISBN: (纸本)9781665464543

Modular multilevel converters have developed into a door opener for a variety of energy applications. Enabling parallel connectivity between modules can offer several advantages to systems, including sensorless balancing, module-to-module energy exchange, reduced impedance, low-frequency operation down to dc output, and a larger effective capacitance. Existing module circuits, however, require many individual switches or offer only very limited parallel functionalities. We propose a new module topology, which we name the direction-selective parallel structure, which requires only a minimum of transistors. A combination of only four active switches and four diodes enables bidirectional equilibration, bipolar module output, and inter-module switched-capacitor features. The topology is highly attractive for existing converters working with cascaded H-bridge elements as the addition of only four diodes enables the key features of more complicated module topologies, particularly their superior balancing, such as sensorless estimator-free balancing, and module-to-module energy exchange. The diodes furthermore well match the insulated gate bipolar transistors implemented in most larger systems. We elaborate on the working principle of the direction-selective parallel module and demonstrate its operation. © 2024 IEEE.

关键词： Insulated gate bipolar transistors (IGBT)

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State of the Art and Innovations needed for Direct Radiating Arrays to place Very High Throughput Satellite Communications into Technology Reach 5

State of the Art and Innovations needed for Direct Radiating...

引用

5th IEEE International Conference on Communications, Information, Electronic and Energy systems, CIEES 2024

作者： Kaifas, Theodoros N. F. Democritus University of Thrace Dept. of Electrical and Computer Engineering Xanthi Greece

ISBN: (纸本)9798350352863

The current work provides the roadmap towards the advent of Very High Throughput Satellite Communications. The key enabler will be the envisioned and presented in detail placement of the Direct Radiating Arrays vision into the reach of the technology. Such an endeavor entails the proper choice of the multi-element electrically large array's geometry as well as the choice on the element radiator. Those choices should support and implement the overlapping concept in hardware. At the same time, they should leave room for advanced array synthesis techniques to unfold their full potential. Those issues are treated in detail, and proper emphasis is given both on the state of the art as well as to the innovations needed to increase the current relative technological readiness level. © 2024 IEEE.

关键词： Satellite communication systems

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Unraveling Patterns in Healthcare Fraud through Comprehensive Analysis 18

Unraveling Patterns in Healthcare Fraud through Comprehensiv...

引用

18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Chirchi, Khushi E. Kavya, B. Dayananda Sagar University Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9789380544519

This study addresses healthcare provider fraud in Medicare, employing advanced machine learning models on a diverse dataset to predict potential fraud. The goal is to contribute insights for effective fraud detection and mitigate its impact on overall healthcare costs. Utilizing Logistic Regression, Random Forest, and addressing class imbalance through SMOTE, we discern patterns in provider behavior. Evaluation metrics, including confusion matrices, accuracy, sensitivity, specificity, Kappa values, AUC, and F1-scores, comprehensively assess each model's performance. Findings highlight distinct behavior patterns and underscore SMOTE's effectiveness in mitigating class imbalance challenges. Comparative analysis discusses algorithm strengths and weaknesses, offering insights for real-world implementation, impacting fraud prevention strategies for insurance companies, healthcare providers, and beneficiaries. In summary, this research makes a noteworthy contribution to the detection of healthcare fraud, offering insights for effective strategies. The incorporation of SMOTE enhances model robustness, leading to improved fraud detection capabilities and, consequently, reducing the impact of fraud on healthcare costs. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： ANN AUC GNN Kappa values Logistic Regression ML NB Random Forest SMOTE SVM

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An algorithm frequently mines a set of items for big data to enhance efficiency

An algorithm frequently mines a set of items for big data to...

引用

2024 IEEE International Conference on Automation and Computation, AUTOCOM 2024

作者： Sonkar, Sanjay Kumar Singh, Balkar SunRise University Dept. of Computer Science and Engineering Rajasthan Alwar India

ISBN: (纸本)9798350382723

In the landscape of rapidly expanding data streams, deriving meaningful insights, particularly frequent itemsets, within massive datasets at a swift pace poses a significant challenge. Addressing this challenge, various methodologies for Frequent Itemset Mining have been proposed, yet they struggle with low support counts and efficiency concerns in handling large datasets. In response, our research introduces Jagged Itemset Counting (JIC) methodologies, aiming to effectively mine Frequent Itemsets from extensive data. The core objective revolves around devising a robust algorithm capable of identifying all Frequent Itemsets, irrespective of database size or the nature of the itemset. Central to this approach is the introduction of a straightforward label representation, GPLN (Geometric Progression Label Number), assigned to each frequent item. Utilizing CGPLN (Cumulative Geometric Progression Label Number), derived from the arithmetic sum of GPLNs within transaction subsets, forms the CGPLN-Label representation for each transaction subset (itemset). Comparative analysis reveals superior performance of JIC over Apriori and Eclat algorithms for small and medium-sized datasets, exhibiting efficiency even at minimal support thresholds. In the realm of Big Data, where FP-Growth and Eclat falter, the proposed technique shines with faster execution times, optimized main memory utilization, and efficient disc memory usage. © 2024 IEEE.

关键词： Data mining

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Agritech Harmony: Real-time ESP32 Automation and Cloud Computing for Socially-Informed Crop Suggestions 5

Agritech Harmony: Real-time ESP32 Automation and Cloud Compu...

引用

5th IEEE International Conference for Emerging Technology, INCET 2024

作者： Bawadkar, Vishal Verma, Aman Pawar, Aditya Phatale, Utkarsh Sadaphule, Prashant Dept. of Computer Engineering AISSMS Institute of Information Technology Pune India

ISBN: (纸本)9798350361155

Accurately predicting long-term crop yield trends remains a crucial challenge in optimizing agricultural practices and ensuring food security. This paper proposes a novel framework that merges real-time data acquired from Internet of Things (IoT) sensors with a Bi-directional LSTM model with an attention mechanism to achieve this objective. This architecture extracts insights from historical and future environmental conditions and prioritizes critical factors influencing yield through attention weighting. The framework incorporates an ESP32-managed sensor network measuring humidity, temperature, moisture, rainfall, and NPK levels, providing a continuous stream of real-time field data. Evaluation of real-world datasets demonstrates the framework's superiority over traditional methods, yielding significantly higher prediction accuracy and exposing key drivers of yield fluctuations through attention analysis. An accessible API facilitates seamless integration with farm management systems, empowering farmers with data-driven decision-making capabilities. This paper highlights the transformative potential of integrating deep learning, real-time IoT data, and APIs for revolutionizing agriculture, paving the way for a more sustainable and resilient agricultural futur. © 2024 IEEE.

关键词： Crops

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BDA: Blockchain-Based Decentralized Authentication System for Autonomous Vehicle Under Ad-Hoc Network

BDA: Blockchain-Based Decentralized Authentication System fo...

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2024 International Conference on Electronics, Information, and Communication, ICEIC 2024

作者： Bae, Ji-Sung Seo, Seung-Woo Seoul National University Dept. of Electrical and Computer Engineering Korea Republic of

ISBN: (纸本)9798350371888

Autonomous driving technology has made substantial development in various platforms and fields. However, a single mistake of an autonomous vehicle can lead to a severe accident or a life-threatening event. Protecting autonomous vehicle data must be considered and guarantee real-time data management, robust security systems, and safe communication systems between vehicle nodes. Since these features can be satisfied by blockchain-based algorithms, combining these two big main themes will make a safer and secure connected-vehicle (CV) system. In this paper we propose a decentralized authentication system in order to make a robust and safe autonomous driving environment. © 2024 IEEE.

关键词： Blockchain

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