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iAnomaly: A Toolkit for Generating Performance Anomaly Datasets in Edge-Cloud Integrated Computing Environments

iAnomaly: A Toolkit for Generating Performance Anomaly Datas...

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ieee international conference on Utility and Cloud Computing (UCC)

作者： Duneesha Fernando Maria A. Rodriguez Rajkumar Buyya Cloud Computing and Distributed Systems (CLOUDS) Laboratory School of Computing and Information Systems The University of Melbourne Australia

ISBN: (数字)9798350367201

ISBN: (纸本)9798350367218

Microservice architectures are increasingly used to modularize IoT applications and deploy them in distributed and heterogeneous edge computing environments. Over time, these microservice-based IoT applications are susceptible to performance anomalies caused by resource hogging (e.g., CPU or memory), resource contention, etc., which can negatively impact their Quality of Service and violate their Service Level Agreements. Existing research on performance anomaly detection in edge computing environments is limited primarily due to the absence of publicly available edge performance anomaly datasets or due to the lack of accessibility of real edge setups to generate necessary data. To address this gap, we propose iAnomaly: a full-system emulator equipped with open-source tools and fully automated dataset generation capabilities to generate labeled normal and anomaly data based on user-defined configurations. We also release a performance anomaly dataset generated using iAnomaly, which captures performance data for several microservice-based IoT applications with heterogeneous QoS and resource requirements while introducing a variety of anomalies. This dataset effectively represents the characteristics found in real edge environments, and the anomalous data in the dataset adheres to the required standards of a high-quality performance anomaly dataset.

关键词： Cloud computing image edge detection Microservice architectures Quality of service Computer architecture internet of Things Anomaly detection Standards Edge computing Service level agreements

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Morphological Segmentation with Modified Otsu’s Method and Multi-Scale Morphological Processing for Shape Recognition

Morphological Segmentation with Modified Otsu’s Method and ...

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Innovations in High Speed Communication and signal Processing (IHCSP), international conference on

作者： Manish Nagpal N.T. Velusudha Deepak Minhas Supriya Rai Ashwini Ranjit Nawadkar D. Bhanu Centre of Research Impact and Outcome Chitkara University Punjab India Department of ECE Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Mangement UG ManagementJAIN (Deemed to be University) Bangalore Karnataka India AI & Ds Vishwakarma Institute of Technology Pune India Department of Information Technology Karpagam Institute of Technology Coimbatore India

ISBN: (数字)9798350368949

ISBN: (纸本)9798350368956

Motological segmentation is essential in the domains of medical imaging, object recognition, and remote sensing. Classical approaches, such as Otsu's thresholding, fail miserably in the presence of noise, light, and complex backgrounds. These concerns are addressed by creating Modified Otsu's Method (MOM). Slow and precise segmentation, adaptive thresholding, and morphological processes are two new areas that MOM aims to tackle. The proposed MOM makes both local and global adjustments taking into account the image and text in order to mitigate the impact of variations in light intensity and noise level. Accurate segmentation and less noise artefacts are achieved by the use of dilation and erosion. On datasets including medical, nature, and remote sensing images, the suggested MOM algorithm achieves better results than previous top-tier segmentation approaches as well as Otsu's approach to generic thresholding based on experimental quantities. This study investigates the optimal execution time of the method for image processing in real time in terms of computing cost. Automated safety devices and medical imaging analysis are two examples of applications where MOM stands out for its exceptional performance in picture segmentation. Therefore, in order to make MOM more versatile and effective in a wide range of imaging contexts, future studies will use machine learning methods.

关键词： image segmentation Accuracy Thresholding (Imaging) Noise Real-time systems Object recognition Method of moments Remote sensing Biomedical imaging Noise level

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IoT based Soil Nutrition and Plant Disease Detection System for Smart Agriculture 10

IoT based Soil Nutrition and Plant Disease Detection System ...

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10th ieee international conference on Communication systems and Network Technologies, CSNT 2021

作者： Suhag, Sashant Jadaun, Sanskriti Shukla, Ayush Singh, Nidhi Johri, Prashant Parashar, Nidhi Department of Computer Science and Engineering Galgotias University Uttar Pradesh 201310 India Department of Computer Science and Engineering Meerut Institute of Technology Uttar Pradesh 250103 India

ISBN: (纸本)9780738105239

In the coming years, farmers will face challenges to feed the increasing number of populations. They need to ensure food security and reduce the dependency on imports. The effective use of new technologies to increase the efficiency of farming will help the farmers to meet the need of increased population AI and IOT related automation to be designed to improve the way a farmer operates for various tasks. We propose a framework for IoT based Soil Nutrition and Plant Disease detection which uses various sensors to collect the plant-related data in form of images at different time intervals using MY THINGS smart sensor and Soil sensors such as proximal soil sensor (PSS) to test the soil fertility which helps to analyze the condition of soil new cultivation, ploughing, water or the land for harvesting. Temperature sensors are also used. Water quality sensors are used that will keep monitoring the quality of the water. All the data will we be sent to the farmer with the help of the IoT. For image classification, Local binary thresholding is used. At harvesting time robot performs image recognition and classification. The farmer will enter the required data to use the robotic arm to automatically harvest the crop. The arm is proposed to have four degrees of freedom and will be driven by the motors. Robotic arms will identify the crop using image recognition and will put that batch in the appropriate basket to be considered by the farmer for analysis. With regular monitoring, this proposed framework can greatly aid the farmers in maintaining crop health as well as quality. © 2021 ieee.

关键词： internet of things

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SVD on a Robust Medical image Watermarking based on SURF and DCT

SVD on a Robust Medical Image Watermarking based on SURF and...

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2021 ieee international conference on Industry 4.0, Artificial Intelligence, and Communications technology, IAICT 2021

作者： Utami, Nabila Setya Novamizanti, Ledya Saidah, Sofia Nyoman Apraz Ramatryana, I. School of Electrical Engineering Telkom University Bandung Indonesia Kumoh National Institute of Technology Dept. of IT Convergence Engineering Gumi Korea Republic of

ISBN: (纸本)9781665444941

Communication technology, multimedia, copyright protection, content data have gained attention in recent years. In addition, privacy and confidentiality are also major challenges in handling. A robust hybrid based on speeded-up robust features (SURF), discrete cosine transform (DCT), singular value decomposition or SVD, and chaotic (Arnold's Cat Map) scheme is proposed in this paper. The use of chaotic maps is for watermarking medical images, which can provide protection and security on medical images. In the watermark image, a method is applied that will increase the security of the watermark image, namely Arnold's Cat Maps. SVD method is used to decompose input data into three submatrices. To produce a watermarked image by combining the watermark image and the host image with the SURF-DCT-SVD method, the embedding stage is carried out. At the extraction stage, it will produce a watermark image from the watermarked image. Furthermore, various attacks were carried out against the proposed method. Experimental results show SVD can increase the robustness of DCT and SURF-based watermarking schemes. The proposed watermarking technique is resistant to JPEG compression attacks, noise addition, signal processing, and geometry attacks. In addition, the other state-of-the-art techniques are compared to the performance of the proposed method. Thus, the proposed watermarking scheme can protect ownership and medical records of medical images. © 2021 ieee.

关键词： Singular value decomposition

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Taxes are All You Need: Integration Of Taxonomical Hierarchy Relationships Into the Contrastive Loss

Taxes are All You Need: Integration Of Taxonomical Hierarchy...

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ieee international conference on image Processing

作者： Kiran Kokilepersaud Yavuz Yarici Mohit Prabhushankar Ghassan AlRegib OLIVES at the Center for Signal and Information Processing CSIP School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

In this work, we propose a novel supervised contrastive loss that enables the integration of taxonomic hierarchy information during the representation learning process. A supervised contrastive loss operates by enforcing that images with the same class label (positive samples) project closer to each other than images with differing class labels (negative samples). The advantage of this approach is that it directly penalizes the structure of the representation space itself. This enables greater flexibility with respect to encoding semantic concepts. However, the standard supervised contrastive loss only enforces semantic structure based on the downstream task (i.e. the class label). In reality, the class label is only one level of a hierarchy of different semantic relationships known as a taxonomy. For example, the class label is oftentimes the species of an animal, but between different classes there are higher order relationships such as all animals with wings being “birds”. We show that by explicitly accounting for these relationships with a weighting penalty in the contrastive loss we can out-perform the supervised contrastive loss. Additionally, we demonstrate the adaptability of the notion of a taxonomy by integrating our loss into medical and noise-based settings that show performance improvements by as much as 7%.

关键词： Representation learning image processing Semantics Taxonomy Finance Contrastive learning Birds

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Learning Hybrid Representations of Semantics and Distortion for Blind image Quality Assessment

Learning Hybrid Representations of Semantics and Distortion ...

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international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Xiaoqi Wang Jian Xiong Bo Li Jinli Suo Hao Gao School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China School of Computer and Software Engineering Xihua University Chengdu China Department of Automation Tsinghua University Beijing China

Recently, some studies have shown that semantic and distortion representations both benefit the evaluation of image quality. However, the images of existing synthetic distortion databases are annotated with subjective quality scores and distortion types, lacking labels with semantic objects. Therefore, it is virtually infeasible to learn the representations of image semantics and distortion by co-guiding with semantic and distortion labels. To address this issue, we propose a dual-perception network (DPNet) via an end-to-end multi-task learning method, where knowledge distillation is lever-aged as a semantic label-free strategy. Specifically, semantic representation derived from pre-trained ResNet152 is applied to supervise the output of DPNet, while the output is utilized to construct a distortion recognition task. In this way, image semantics and distortion can be hybridly represented in an identical feature map. Finally, image quality is regressed based on the hybrid representations. Experimental results conducted on five benchmark databases validate that the proposed method can achieve state-of-the-art performance.

关键词： image quality Learning systems Knowledge engineering Acoustic distortion image recognition Databases Semantics

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Empirical Performance Analysis and Channel Modeling of UAV-Assisted LoRa Networks 30

Empirical Performance Analysis and Channel Modeling of UAV-A...

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30th international conference on Electrical Engineering, ICEE 2022

作者： Aghajari, Hossein Ahmadinabi, Sajad Babadegani, Hamed Bakhtiari Soorki, Mehdi Naderi Engineering Faculty Ahvaz Iran

ISBN: (纸本)9781665480871

Long range (LoRa) technology has been widely proposed to empower cost-efficient and scalable communication backbone for the battery-constrained internet of thing (IoT) device. However, the LoRa-based IoT network suffers from a limitation in coverage caused by high signal attenuation due to the terrestrial blockages especially in the urban and suburban environments. To overcome this issue, the use of unmanned aerial vehicles (UAVs) as a flying LoRa gateway to transfer messages from ground LoRa nodes to the cellular base station is proposed. Thus, it is of great interest to accurately model the propagation channel and performance analysis of UAV-Assisted LoRa network based on real measurements. In this paper, a UAV-Assisted LoRa Network is empirically implemented and analyzed. First, LoRa node and gateway are designed and practically implemented using LoRa Ra-02 module, Arduino Uno board, and SIM800l GSM module. Then, the LoRa gateway is mounted over DJI Phantom 4 Pro drone to have a flying LoRa gateway. In this UAV-assisted LoRa Network, the LoRa node sends data to the LoRa gateway over LoRa links, and then LoRa gateway sends data over cellular link to the server. The UAV-Assisted LoRa Network is set up over the campus of Shahid Chamran University of Ahvaz. For this network, different experiment scenarios including line-of-sight (LoS) or none-LoS (NLoS) links and ground or flying LoRa gateway are considered. Following the real-world measurement in these scenarios, the channel model parameters of LoRa links between flying or ground gateway and node are empirically estimated. Our results show that the path loss exponent of LoS LoRa link is 2.57 for ground LoRa gateway, while the LoS path loss exponent of LoRa link decreases to 1.65 for 80m-height flying LoRa gateway. Moreover, our practical analysis shows that the useful coverage area of network rapidly increases when the flying LoRa gateway is used instead of ground LoRa one. © 2022 ieee.

关键词： internet of things

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Integrated Design of OFDM-LFM Lidar Communication in IoV Environment

Integrated Design of OFDM-LFM Lidar Communication in IoV Env...

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international conference on Information, Communication and Networks (ICICN)

作者： Genxue Zhou Minghua Cao Qing Yang Yue Zhang Shengchun Han Huiqin Wang Lanzhou University of Technology School of Computer and Communication Lanzhou China

ISBN: (数字)9798350355802

ISBN: (纸本)9798350355819

To address the challenges associated with traditional communication-sensing integrated systems in the internet of Vehicle (IoV) environment, particularly in terms of spectrum demand and hardware implementation costs, a lidar communication-sensing integrated system is proposed. This system combines asymmetric limiting optical orthogonal frequency division multiplexing (ACO-OFDM) and linear frequency modulation (LFM) technologies to seamlessly integrate optical communication and lidar ranging. Simulation results demonstrate that the system's bit error rate (BER) performance improves by 4.2 dB under Gamma-Gamma weak and medium turbulence channel conditions compared to a single LFM signal. Additionally, the overall ambiguity function of the integrated system exhibits a distinctive ‘peg’ shape, indicating superior distance and speed resolution capabilities. A laboratory prototype successfully demonstrates the system's capability to transmit data at 10 Mbps while maintaining an impressive ranging accuracy of less than 0.14 cm.

关键词： Laser radar Shape OFDM Simulation Bit error rate Prototypes Hardware Distance measurement Proposals signal resolution

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Low-Complexity Transmission for STAR-RIS-Assisted Symbiotic Radio Using OOK

Low-Complexity Transmission for STAR-RIS-Assisted Symbiotic ...

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international conference on Communication technology (ICCT)

作者： Mingjiang Wu Xianfu Lei Ibrahim Al-Nahhal Octavia A. Dobre Luyao Sun School of Information Science and Technology Southwest Jiaotong University Chengdu China Faculty of Engineering and Applied Science Memorial University St. Johns Canada China Railway Eryuan Engineering Group Co. Ltd Chengdu China

ISBN: (数字)9798350363760

ISBN: (纸本)9798350363777

This paper proposes a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted symbiotic radio (SR) system, in which the transmission functionality of STAR-RIS is used to transmit extra internet of Things (IoT) data and the reflection functionality of STAR-RIS is adopted to enhance the downlink transmission. STAR-RIS utilizes ON-OFF keying for IoT data modulation, which allows the IoT receiver to decode data using a low-complexity energy detector. The transmit beamforming at the base station and the transmission and reflection beamforming at the STAR-RIS are jointly optimized to maximize the weighted sum-rate (WSR) of downlink users, subject to the received power constraint of IoT transmission. Considering the practical coupled phase shift constraint of STAR-RIS, an efficient penalty dual decomposition-based algorithm is proposed to solve the formulated highly non-convex problem. based on the obtained solution, the optimal IoT receiver and the theoretical bit error rate are further derived. Simulation results verify the effectiveness of the proposed STAR-RIS-assisted SR system.

关键词： Symbiosis Array signal processing Simulation Modulation Receivers Reconfigurable intelligent surfaces Downlink Reflection internet of Things Optimization

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Embedded System Design and Development for Data Acquisition and IoT-based Control and Monitoring using Event-Driven Techniques

Embedded System Design and Development for Data Acquisition ...

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ieee international conference on Electrical, Computer, and Energy Technologies (ICECET)

作者： Jitaree, Raweenipha Nuratch, Santi King Mongkuts Univ Technol Thonburi Dept Control Syst & Instrumentat Engn KMUTT Bangkok Thailand

ISBN: (纸本)9781665442312

This research presents the Embedded System Design and Development for Data Acquisition and IoT-based Control and Monitoring using Event-Driven Techniques. The proposed system is designed and developed based on industrial-based applications. It consists of two subsystems, the event-driven data acquisition system, and a real-time IoT-based control and monitoring system. The data acquisition is implemented based on three different algorithms used for different signal event detections. All algorithms make the data acquisition acquire and store data only when desired events (conditions) are detected. It means that the requirement for storage space is extraordinarily low. This implementation technique also significantly reduces bandwidth when it is implemented in sensor nodes and real-time monitoring systems. All desired signal events are logged (or sent to the IoT application) with a high-precision timestamp. These techniques make engineers precisely perform system diagnostics. The proposed system also includes IoT-based real-time control and monitoring capability. It can be used to monitor sensing parameters and control actuators through a web application in a real-time fashion. We design and perform experiments to cover all possible normal use cases. The system can operate correctly as expected. We also evaluate the proposed algorithms to find out more practical information in terms of their performance and limitations by using generative signals with additive noises. The experimental results show that the system gives good results, and it can be used in real-world industrial, laboratory, and internet-of-Thing applications.

关键词： event-driven data acquisition firmware real-time operating system embedded systems internet-of-Things

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