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Leader-Follower Consensus Control of Multi-Agent systems With Disturbance by distributed Sliding Mode Control 1

Leader-Follower Consensus Control of Multi-Agent Systems Wit...

引用

1st ieee international conference on Smart and Sustainable Developments in Electrical Engineering, SSDEE 2025

作者： Kumar, Praveen Anand, Amit Guha, Dipayan Purwar, Shubhi MNNIT EE Department Allahabad India

ISBN: (纸本)9798331542108

This paper addresses the leader-follower consensus control of multi-agent systems (MASs) in the presence of external disturbance, utilizing a distributed sliding mode control (DSMC) approach. We first formulate the consensus problem, where a designated leader influences the behavior of multiple follower agents. The proposed DSMC strategy is designed to enhance robustness against disturbances and uncertainties inherent in the system. By leveraging the sliding mode control theory, we ensure that the agents maintain desired trajectories while effectively rejecting external perturbations. Theoretical analysis demonstrates the stability and convergence of the consensus protocol, supported by simulation results showcasing the efficacy of the DSMC method in practical scenarios. This work contributes to the field of multi-agent systems by providing a reliable control framework capable of achieving consensus under challenging conditions, making it applicable in various domains, including robotics and autonomous vehicles. © 2025 ieee.

关键词： Sliding mode control

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Butterfly Shaped Planar Microstrip Resonant sensor for Measuring Permittivity of Liquids 1

Butterfly Shaped Planar Microstrip Resonant Sensor for Measu...

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1st international conference on Trends in Engineering systems and Technologies, ICTEst 2024

作者： Vishnupriya, V. Laila, D. Model Engineering College Department of Electronics Kerala Thrikkakara India College of Engineering Department of Electronics Kerala Chengannur India

ISBN: (数字)9798350307795

ISBN: (纸本)9798350307795

A planar microstrip resonant sensor is proposed. Permittivity of the liquid samples can be found using this method. The proposed structure is a structure that exhibit high field confinement and have good dispersion analysis. The design is simulated in Ansys studio Suite HFSS and found that the resonant frequencies decreases when permittivity increases. sensor finds application in different areas such as detecting adulteration of oil etc. © 2024 ieee.

关键词： Permittivity

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Helping Faculty Teach Software Performance Engineering

Helping Faculty Teach Software Performance Engineering

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1st international conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： Owens, John D. Hoppe, Bruce Univ Calif Davis Dept Elect & Comp Engr Davis CA 95616 USA Connect Associates Arlington MA USA

ISBN: (纸本)9798350364613;9798350364606

Over the academic year 2022-23, we discussed the teaching of software performance engineering with more than a dozen faculty across North America and beyond. Our outreach was centered on research-focused faculty with an existing interest in this course material. These discussions revealed an enthusiasm for making software pertimmance engineering a more prominent part of a curriculum for computer scientists and engineers. Here, we discuss how MIT's longstanding efforts in this area may serve as a launching point for community development of a software performance engineering curriculum, challenges in and solutions for providing the necessary infrastructure to universities, and future directions.

关键词： Performance distributed parallel cluster computing data structures and algorithms software performance engineering

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2024 1st international conference on Trends in Engineering systems and Technologies, ICTEst 2024

2024 1st International Conference on Trends in Engineering S...

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1st international conference on Trends in Engineering systems and Technologies, ICTEst 2024

ISBN: (纸本)9798350307795

The proceedings contain 119 papers. The topics discussed include: machine learning and deep learning architectures for intrusion detection system (IDS): a survey;artificial steering feel in steer by wire systems: a simulation based evaluation of control strategies;review of totem-pole boost bridgeless PFC rectifier intended for on-board EV charging;revolutionizing voting: blockchain-powered e-voting with Solana;automated glaucoma detection and assessment using CNN from fundus images;ANN technique for load forecasting;energy efficient beam-forming and power distribution in cognitive radio network;comparison of deep learning classifier models for sensor array based acoustic source localization;power quality improvement in transmission system using optimal location system with integration of distributed power flow controller;and smart junctions: Yolov5, DeepSORT, and direction analysis for traffic enhancement.

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Automated Calibration of Parallel and distributed computing Simulators: A Case study

Automated Calibration of Parallel and Distributed Computing ...

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1st international conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： McDonald, Jesse Horzela, Maximilian Suter, Frederic Casanova, Henri Univ Hawaii Manoa Honolulu HI 96822 USA Karlsruhe Inst Technol Karlsruhe Germany Oak Ridge Natl Lab Oak Ridge TN USA

ISBN: (纸本)9798350364613;9798350364606

Many parallel and distributed computing research results are obtained in simulation, using simulators that mimic real-world executions on some target system. Each such simulator is configured by picking values for parameters that define the behavior of the underlying simulation models it implements. The main concern for a simulator is accuracy: simulated behaviors should be as close as possible to those observed in the real-world target system. This requires that values for each of the simulator's parameters be carefully picked, or "calibrated," based on ground truth real-world executions. Examining the current state of the art shows that simulator calibration, at least in the field of parallel and distributed computing, is often undocumented (and thus perhaps often not performed) and, when documented, is described as a labor-intensive, manual process. In this work we evaluate the benefit of automating simulation calibration using simple algorithms. Specifically, we use a real-world case study from the field of High Energy Physics and compare automated calibration to calibration performed by a domain scientist. Our main finding is that automated calibration is on par with or significantly outperforms the calibration performed by the domain scientist. Furthermore, automated calibration makes it straightforward to operate desirable trade-offs between simulation accuracy and simulation speed.

关键词： Simulation of distributed computing platforms and applications Simulation accuracy and scalability Simulation calibration

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A GMM-CGABC Based Energy Replenishment Scheme for On-Demand Wireless Rechargeable sensor Networks 1

A GMM-CGABC Based Energy Replenishment Scheme for On-Demand ...

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1st international Symposium on Parallel computing and distributed systems, PCDS 2024

作者： Mouli, S.Sudhamsu Veeraiah, T. Mahesh, K. Singh, M.P. Ecole Centrale School of Engineering Mahindra University Department of Computer Science and Engineering Hyderabad India National Institute of Technology Department of Computer Science and Engineering Patna India

ISBN: (纸本)9798350349658

Wireless sensor Networks (WSNs) are constrained by the limited energy capacity of sensor Nodes (SNs), which hinders their perpetual operation. The advent of Wireless Energy Transfer (WET) technology has emerged as a promising solution to this challenge, enabling the creation of Wireless Rechargeable sensor Networks (WRSNs). Recent research has shown growing interest in integrating Wireless Mobile Chargers (WMCs) into WRSNs to replenish the energy reserves of critical SNs through WET. A key aspect of WET involves using one or more WMCs to recharge SNs, with optimizing the charging schedule (i.e., the sequence in which SNs are charged) crucial in on-demand WRSNs. In addition, spatiotemporal constraints imposed by the requesting SNs must be considered when devising the WMC's charging schedule. To address these challenges, this work proposes the integration of a Gaussian Mixture Model with a Chaotic Gaussian Artificial Bee Colony (GMM-CGABC) to develop an efficient recharge schedule that revitalizes SNs. This model is designed to optimize SN deployment, maximize network coverage, minimize energy consumption, and extend network longevity. The proposed method determines the optimal charging path for WMCs within each cluster to minimize Average Charging Latency (ACL) while incorporating a novel strategy for fitness function evaluation. Extensive simulations demonstrate that the proposed system outperforms state-of-the-art algorithms, including First Come, First Served (FCFS), Nearest Job Next with Preemption (NJNP), and the Gravitational Search Algorithm (GSA), in terms of charging latency. © 2024 ieee.

关键词： Inductive power transmission

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Optimizing Optical Character Recognition Accuracy in Livestock Weighting systems Through distributed Intelligent Computer Vision 1

Optimizing Optical Character Recognition Accuracy in Livesto...

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1st ieee international Symposium on Consumer Technology, ISCT 2024

作者： Wafa, M. Rosyad Ahsanul Toh-Arlim, Muhaimin Sukaridhoto, Sritrusta Budiarti, Rizqi Putri Nourma Prayudi, Agus Politeknik Elektronika Negeri Surabaya Dept. of Multimedia Creative Technology Surabaya Indonesia Universitas Nahdlatul Ulama Surabaya Faculty of Economics Business and Digital Technology Surabaya Indonesia

ISBN: (纸本)9798350365191

This research develops and optimizes an optical character recognition (OCR) system for goat weighing scales using intelligent computer vision and distributed computing to enhance accuracy and efficiency in real-world operational conditions. Images of the scales are captured and processed to remove noise, then recognized using deep learning algorithms. The implementation of distributed computing frameworks like Apache Hadoop and TensorFlow enables efficient parallel processing. Results show a 20% increase in OCR accuracy and a 30% improvement in processing efficiency compared to conventional systems. This integration provides a scalable and reliable solution for applications in the livestock industry, with potential adaptation for various operational conditions and other livestock types. © 2024 ieee.

关键词： Scales (weighing instruments)

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A Comprehensive study on distributed Denial of Service Attack Detection using Deep Learning Technique 1

A Comprehensive Study on Distributed Denial of Service Attac...

引用

1st international conference on Software, systems and Information Technology, SSITCON 2024

作者： Mukku, Bhavana Mlr Institute of Technology Department of Data Science and Cyber Security Hyderabad India

ISBN: (纸本)9798350352931

distributed Denial of Service (DDoS) attacks are among the most dangerous threats in cyberspace impacting areas such as the Internet of Things (IoT), Cybersecurity, and Cloud computing, which leads to network interruptions. DDoS attacks target IoT environments by manipulating IoT networks, consuming resources and interrupting services, leading to privacy challenges and performance degradation. However, accurate detection of DDoS attacks is difficult, due to their various DDoS attack types, heterogeneity of network security and complexity of communication protocols. Advanced Deep Learning (DL) approaches have been employed for effective detection of DDoS attacks while reducing false-positive rates and improving high detection rates of the different network traffic patterns. The DL algorithms such as Convolutional Neural Networks (CNN), Bidirectional Long-Short Term Memory (Bi-LstM), Recurrent Neural Networks (RNN), and Deep Neural Networks (DNN) are used for the detection of DDoS attacks. This survey focuses on analyzing the advantages and limitations of different DL algorithms used for DDoS attack detection. The performance of the DL models is evaluated based on performance metrics such as accuracy, precision, recall, and F1-score. © 2024 ieee.

关键词： Cyber attacks

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distributed Multi-GPU Community Detection on Exascale computing Platforms

Distributed Multi-GPU Community Detection on Exascale Comput...

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1st international conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： Sattar, Naw Safrin Lu, Hao Wang, Feiyi Halappanavar, Mahantesh Oak Ridge Natl Lab Oak Ridge TN 37830 USA Pacific Northwest Natl Lab Richland WA 99352 USA

ISBN: (纸本)9798350364613;9798350364606

Community detection is a fundamental operation in graph mining, and by uncovering hidden structures and patterns within complex systems it helps solve fundamental problems pertaining to social networks, such as information diffusion, epidemics, and recommender systems. Scaling graph algorithms for massive networks becomes challenging on modern distributed-memory multi-GPU (Graphics Processing Unit) systems due to limitations such as irregular memory access patterns, load imbalances, higher communication-computation ratios, and cross-platform support. We present a novel algorithm HiPDPL-GPU (distributed Parallel Louvain) to address these challenges. We conduct experiments involving different partitioning techniques to achieve an optimized performance of HiPDPL-GPU on the two largest supercomputers: Frontier and Summit. Remarkably, HiPDPL-GPU processes a graph with 4.2 billion edges in less than 3 minutes using 1024 GPUs. Qualitatively, the performance of HiPDPL-GPU is similar or better compared to other state-of-the-art CPU- and GPU-based implementations. While prior GPU implementations have predominantly employed CUDA, our first-of-its-kind implementation for community detection is cross-platform, accommodating both AMD and NVIDIA GPUs.

关键词： multi-GPU Louvain community detection clustering hybrid HIP MPI

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System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models

System Optimizations for Enabling Training of Extreme Long S...

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1st international conference on Smart Energy systems and Artificial Intelligence (SESAI)

作者： Jacobs, Sam Ade Tanaka, Masahiro Zhang, Chengming Zhang, Minjia Aminabadi, Reza Yazdani Song, Shuaiwen Leon Rajbhandari, Samyam He, Yuxiong Microsoft Inc Redmond WA 98052 USA

ISBN: (纸本)9798350364613;9798350364606

Long sequences are ubiquitous in NLP tasks such as document summarization, machine translation, and dialogue modeling [1]-[9]. Traditional approaches to parallelism, including data parallelism [10]-[12], tensor [13] and pipeline parallelism [14]-[16] struggle to handle sequences that span thousands or even millions of tokens. © 2024 ieee.

关键词： DeepSpeed distributed Training HPC LLMs Long context LLMs Sequence Parallelism

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