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real-time Anomaly Detection Using Distributed Tracing in Microservice Cloud applications 12

Real-Time Anomaly Detection Using Distributed Tracing in Mic...

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12th international conference on Cloud Networking (CloudNet)

作者： Raeiszadeh, Mahsa Ebrahimzadeh, Amin Saleem, Ahsan Glitho, Roch H. Eker, Johan Mini, Raquel A. F. Concordia Univ CIISE Montreal PQ Canada Ericsson Res Lund Sweden Univ Western Cape Comp Sci Programme Cape Town South Africa

ISBN: (纸本)9798350313062;9798350313079

Distributed tracing plays a vital role in microservice infrastructure, and learning-based trace analysis has been utilized to detect anomalies within such systems. However, existing approaches for learning-based trace-based anomaly detection face certain limitations. Some assume that trace patterns can be learned solely from normal executions, while others depend on anomaly injection to generate labeled traces categorized as normal or anomalous. However, in practical scenarios, anomalies may also happen during the normal execution. Moreover, a wide variety of anomalies may occur in practice, which cannot be captured solely through anomaly injection. To address these issues, we propose a Trace-Driven Anomaly Detection (TDAD) approach based on a Span Causal Graph (SCG) representation, which trains a model using a Graph Neural Network (GNN) and Positive and Unlabeled (PU) learning. This technique allows the model parameters to be optimized by estimating the underlying data distribution. As a result, TDAD can be effectively trained using a small number of labeled anomalous traces along with a relatively large number of unlabeled traces. Our evaluation reveals that TDAD outperforms not only the existing unsupervised trace-based anomaly detection methods by 11.9% in terms of F-1-score but also a supervised learning-based benchmark by 12x in terms of detection time.

关键词： Anomaly Detection Distributed Tracing Microservice Positive and Unlabeled Learning

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Configuration of Parallel real-time applications on Multi-Core Processors 20

Configuration of Parallel Real-Time Applications on Multi-Co...

引用

20th ieee international conference on Industrial Informatics (INDIN)

作者： Gharajeh, Mohammad Samadi Carvalho, Tiago Pinho, Luis Miguel Polytech Inst Porto Sch Engn Porto Portugal

ISBN: (数字)9781728175683

ISBN: (纸本)9781728175683

Parallel programming models (e.g., OpenMP) are more and more used to improve the performance of real-time applications in modern processors. Nevertheless, these processors have complex architectures, being very difficult to understand their timing behavior. The main challenge with most of existing works is that they apply static timing analysis for simpler models or measurement-based analysis using traditional platforms (e.g., single core) or considering only sequential algorithms. How to provide an efficient configuration for the allocation of the parallel program in the computing units of the processor is still an open challenge. This paper studies the problem of performing timing analysis on complex multi-core platforms, pointing out a methodology to understand the applications' timing behavior, and guide the configuration of the platform. As an example, the paper uses an OpenMP-based program of the Heat benchmark on a NVIDIA Jetson AGX Xavier. The main objectives are to analyze the execution time of OpenMP tasks, specify the best configuration of OpenMP directives, identify critical tasks, and discuss the predictability of the system/application. A Linux perf based measurement tool, which has been extended by our team, is applied to measure each task across multiple executions in terms of total CPU cycles, the number of cache accesses, and the number of cache misses at different cache levels, including L1, L2 and L3. The evaluation process is performed using the measurement of the performance metrics by our tool to study the predictability of the system/application.

关键词： real-time systems multi-core processors timing analysis parallel programming OpenMP

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Crowdsourcing of Internet of Things: applications, Trends in technology and the Future

Crowdsourcing of Internet of Things: Applications, Trends in...

引用

2023 international conference on Power, Instrumentation, Control and computing, PICC 2023

作者： Anoopa, S. Salim, A. Pankaj, Dhanya S. College of Engineering Trivandrum Affiliated to Apj Abdulkalam Tecnological University Department of Computer Science and Engineering Kerala Thiruvananthapuram India Govt. Engineering College Thrissur Affiliated to Apj Abdulkalam Tecnological University Department of Computer Science and Engineering Kerala Thiruvananthapuram India

ISBN: (纸本)9798350334463

Crowdsourcing of IoT devices is giving a new dimension to the Internet of things(IoT) applications. The crowd equipped with geolocated mobile devices enhances mobile crowd-sourcing which in turn contributes to new and unexplored use cases. This paper proposes a generalized architecture for the crowd-IoT system, enlightens a comprehensive survey of different applications of crowd-IoT, points out the importance of embedded intelligence in crowd-IoT systems, and suggests appropriate Artificial Intelligence(AI) tools and supporting frameworks for next-generation IoT applications. As crowd-IoT is an emerging research area, this paper aims to provide awareness and motivation to the innovations towards Crowdsourcing of IoT devices. © 2023 ieee.

关键词： Crowdsourcing

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LuxuryLeaf: Smart Ornamental Plant Monitoring and Control System with embedded IoT 10

LuxuryLeaf: Smart Ornamental Plant Monitoring and Control Sy...

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10th ieee international conference on Smart Instrumentation, Measurement and applications, ICSIMA 2024

作者： Harun, Faezah Marzuki, Muhammad Syahmi Haziq Ikhmalalbakri, Muhammad Imanmukhriz Radzi, Muhammad Syakir Mohd Universiti Kuala Lumpur Electronic Technology Section British Malaysian Institute Gombak Malaysia Universiti Kuala Lumpur Communication Technology Section British Malaysian Institute Gombak Malaysia

ISBN: (纸本)9798350365283

Ornamental plant primarily valued for their aesthetic value, fragrance or spatial shaping. They are not only making indoor and outdoor places visually more appealing, but also contribute to improved air quality, creating a healthier atmosphere and good for mental health. Despite the numerous advantages, not everyone is well-equipped with knowledge and techniques to take care of the ornamental plants, particularly indoor varieties. Inadequate care can lead to plant deterioration due to owner negligence or overenthusiastic practices, such as overwatering or excessive exposure to heat. This paper presented the development of automated monitoring system that continuously monitor environmental parameters such as temperature, humidity and soil moisture. The system integrates a cloud-based IoT system for data collection and analysis, providing a real-time view of all parameters, to ensure ideal growth conditions. Additionally, a remote water pump access is successfully incorporated into the overall system solution with 100% control system efficiency. The monitoring system is able to provide efficient plant monitoring with clear information related to the plant's condition and behaviour. This system is also cost-effective and user-friendly;catering to both novice users and nurseries with large-scale plant operations. © 2024 ieee.

关键词： Soil moisture

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Role of IOT and its Trends in Data Driven systems Using AI 3

Role of IOT and its Trends in Data Driven Systems Using AI

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3rd international conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Singla, Neeraj Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350330724

This mainly focus on the rapid growth in the disciplines of data-driven system, concentrating on integration of Artificial Intelligence and the Internet of Thing. The chapter stars out with introducing the challenges and future scope and direction of Internet of Thing and Artificial Intelligence in data-driven system. It then examines the functions of Internet of Thing and its trends in data-driven systems with the assessment of augmented reality, diving deep into the topic by discussing on the models and architectures that combine Internet of Thing and Artificial Intelligence for data-driven systems. The chapter will also look at how Artificial Intelligence and Internet of Thing work together to create complex, real-time data-driven systems and how machine learning algorithms has a big role of Internet of Thing for data-driven systems. Furthermore, showing the new and optimized machine learning and deep learning models with comprehensible Artificial Intelligence for data-driven systems. Artificial Intelligence and Internet of Thing is big part of developing countries, also for social security and welfare. Then exploring the important role of cloud computing in Artificial Intelligence based data-driven systems, including a hybrid cloud computing environment based for large data-driven applications. Lastly, we will focus over the discussing the challenges, future scope and direction of Artificial Intelligence and cloud computing in the data-driven systems and there uses in boosting up the network efficiency. Artificial Intelligence and Internet of Thing can be operated with access to the internet and it can be used by person of any age. Overall, this chapter is a complete guide for practitioners, researchers and engineers interested in the newest developments of Internet of Thing and Artificial Intelligence applications in data-driven systems. © 2023 ieee.

关键词： Internet of things

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A Review on the Analysis of the Effectiveness of Permission Based Security Models in Android Apps 7

A Review on the Analysis of the Effectiveness of Permission ...

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7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Harikrishnan, P.R. Periyasamy, P. Department of Computer Science Tamilnadu Tirupur India Department of Computer Science and Applications Tamilnadu Tirupur India

ISBN: (数字)9798350372816

ISBN: (纸本)9798350372816

As the ubiquity of Android devices continues to grow, the importance of safeguarding user data and privacy within the Android app ecosystem becomes increasingly critical. Central to this security framework is the permission-based security model, which grants users control over the extent to which apps access sensitive device resources and personal information. This paper provides a thorough examination of the efficiency of permission-based security models in Android applications, furnishing valuable perspectives on the everchanging realm of security. At the core of Android's security framework lies the permission-based security model, a system designed to regulate an app's access to sensitive device resources such as the camera, microphone, location, contacts, and personal data. This model empowers users by granting them the authority to approve or deny these permissions when installing or using an app, ostensibly ensuring the privacy and security of their data. This review embarks on a comprehensive exploration of the effectiveness of permission-based security models in Android apps. In the context of the permission-based model, it explored potential security vulnerabilities and the real- world risks they pose to users devices and data. The performance of different malware detection systems associated with the permission based android apps and its limitations are also analyzed in this paper. By synthesizing existing research and empirical evidence, this paper provides valuable insights into the current state of permission-based security in Android apps and suggests directions for future research and development. © 2024 ieee.

关键词： Android malware

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Packet Simulator Tool for Many-Core systems

Packet Simulator Tool for Many-Core Systems

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2023 ieee international conference on systems, Man, and Cybernetics, SMC 2023

作者： Paris, Paulo Cesar Donizeti Pedrino, Emerson Carlos Federal University of São Carlos Departament of Computer Science São Carlos Brazil

ISBN: (纸本)9798350337020

With recent advances in technology, many-core systems have become increasingly common in high-performance computing applications, such as embedded systems and artificial intelligence. To fully utilize the processing power offered by this architecture, it is necessary to have good management and allocation of application tasks on Processing Elements (PEs), using Design Space Exploration (DSE) techniques. In this article, we develop an approach, called a Packet Simulator Tool for many-core systems, implemented in a simulation environment using the Matlab, for analysis and calculation of the metric related to energy efficiency based on packet traffic using a Network-on-chip (NoC) architecture for a manycore processor. The approach uses high-level abstraction, is modular, and can be integrated with statistical analysis and Directed Acyclic Graph (DAG) generation tools. The experimental results showed that, although the NoCTweak simulator obtained better results, the approach proposed in this article proved to be promising for academic studies due to its ease of use and faster learning curve. © 2023 ieee.

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The Research on Current Automated Driving ODD Regulations, Standards and applications

The Research on Current Automated Driving ODD Regulations, S...

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2022 ieee international conference on real-time computing and Robotics, RCAR 2022

作者： Chen, Chen Qidong, Zhao Tong, Zheng Yang, Zhai Xianglei, Zhu China Automotive Technology and Research Center Co. Ltd. China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

ODD, short for Operational Design Domain, is fundamental to automated driving technology RandD. A reasonable and well-defined ODD is the prerequisite for the realization of automated driving function safety. In this paper, UN regulations and international standards (including drafts) publicly released in recent years, and presentation from important organizations or companies in the industry are thoroughly reviewed to perform a prospective analysis from four aspects, namely, concept and definition of ODD, responsible subject for ODD description, ODD description methods and contents, and ODD application cases. © 2022 ieee.

关键词： Industries Service robots ISO Standards Standards organizations Companies Regulation real-time systems

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Efficient Transformers for on-robot Natural Language Understanding 21

Efficient Transformers for on-robot Natural Language Underst...

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ieee-RAS 21st international conference on Humanoid Robots (Humanoids)

作者： Greco, Antonio Roberto, Antonio Saggese, Alessia Vento, Mario Univ Salerno Dept Comp & Elect Engn & Appl Math I-84084 Fisciano Italy

ISBN: (纸本)9798350309799

The main task of a social robot is to interact with humans through spoken natural language. It implies that it must be able to understand the intent of the user and the involved entities. Recently, different solutions have been proposed to deal with the Natural Language Understanding (NLU) task. Extremely accurate results have been obtained by architectures based on transformers, but they require high computational resources to work in real-time. Unfortunately, these resources are not available on embedded systems equipped on board the robot. For these reasons, in this paper we experimentally evaluate the most promising transformers for NLU over the popular ATIS and SNIPS datasets and measured their inference time on the NVIDIA Jetson Xavier NX embedded system. The experimental analysis demonstrates that the Albert model can obtain comparable performance w.r.t. the popular BERT architecture (just a 2% drop on entity recognition), while gaining a speed-up of more than 3x. Thanks to the insights coming out from our analysis, we finally developed a real system for restaurant search running the model over a NVIDIA Jetson Xavier NX equipped on board of a social robot, obtaining a positive user feedback about its effectiveness and responsiveness.

关键词： embedded systems

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Helmet Detection System Using Yolo V2

Helmet Detection System Using Yolo V2

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2024 ieee international conference on Information Technology, Electronics and Intelligent Communication systems, ICITEICS 2024

作者： Arun, M.D.R. Jaitly, Vanita Hindustan Institute of Technology and Science Department of Computer Applications Chennai India

ISBN: (纸本)9798350382693

The risk of head injuries. The methodology The increasing concern for safety in a variety of work and leisure environments mandates the production of robust and efficient helmet detection systems. This study offers a fresh method for helmet detection, utilizing the (You Only Look Once version 2) YOLOv2 algorithm. The proposed system leverages the capabilities of YOLOv2 for real-time object detection, providing a proactive solution to enforce helmet-wearing regulations and mitigate impacts that encompass gathering of data, pre-processing, designing of the model architecture, training, and assessment. Results from experiments show the YOLO has achieved the greatest mAP success rate of 96.72%. How well the suggested approach works in precisely detecting helmets in diverse environments and scenarios. Furthermore, discussions on implementation considerations, challenges, and future research directions are provided, highlighting the potential impact of the helmet detection system on enhancing safety across industries and activities. © 2024 ieee.

关键词： Deep learning

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