In cloud computing, microservices architecture has become the preferred choice for many applications. Accordingly, several small and decoupled containerized services hosted on different servers communicate through the...
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ISBN:
(纸本)9798350360882;9798350360899
In cloud computing, microservices architecture has become the preferred choice for many applications. Accordingly, several small and decoupled containerized services hosted on different servers communicate through the network. Therefore, communication latency significantly impacts end-to-end latency. Kubernetes, the de facto standard for container orchestration, cannot reduce this overhead due to its lack of awareness of service interactions. We present LEAD, a Latency-Efficient Application Deployment framework that integrates with Kubernetes without modifying its core components. LEAD considers the inter-service relationships and resource constraints, improving service placement to reduce end-to-end latency. The idea behind LEAD is straightforward: keep the cooperating services close to each other to exploit faster in-node communication and automate this process. The proposed idea is realized by leveraging a scoring algorithm and monitoring framework to achieve dynamic improvement of service placement. Our experimental results show an average 20% improvement in the 99th percentile latency compared to Kubernetes default scheduler.
Coffee bean grading is a crucial process in the coffee industry, traditionally done manually by human experts, which is time-consuming, expensive, and prone to errors. To address these challenges, deep learning models...
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Endogenous Safety and Security (ESS) of Industrial control Systems (ICS) has gained great attention with the advent of Industry 4.0. However, with rising cyber threats, most current research has focused mainly on cybe...
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ISBN:
(纸本)9798350370058;9798350370164
Endogenous Safety and Security (ESS) of Industrial control Systems (ICS) has gained great attention with the advent of Industry 4.0. However, with rising cyber threats, most current research has focused mainly on cybersecurity aspects. Our study aims to fill this research gap by focusing on the endogenous functional safety of ICS, with a particular emphasis on key control parameters "setpoints". We propose a reinforcement adversarial framework to investigate the functional security issues arising from unexpected operations and malicious tampering against setpoints. In this framework, a deep reinforcement learning(DRL) agent interacts with a custom input rule model, which serves as both a dynamic validator and an adversary, aiming to explore previously unforeseen behaviors. Explored unexpected behaviors are continuously updated to the input rule model, enhancing system adaptability and robustness. Our study employed the Tennessee Eastman process as a case study, using the proximal policy optimization(PPO) algorithm with Beta and Gaussian distributions. Our approach exhibited significant advantages in exploration efficiency over baseline methods such as random agents and simulated annealing. These findings underscore DRL's important role in augmenting ICS functional safety, thereby enhancing system resilience and security in Industry 4.0.
This paper introduces a method for modeling residual dynamics between a high-level planner and a low-level controller, using reference trajectory tracking in a cluttered environment as a case study. We aim to mitigate...
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ISBN:
(纸本)9798350358513;9798350358520
This paper introduces a method for modeling residual dynamics between a high-level planner and a low-level controller, using reference trajectory tracking in a cluttered environment as a case study. We aim to mitigate residual dynamics resulting solely from the kinematical modeling employed in high-level planning. Our high-level planner utilizes a simplified motion model for quadrotor motion. We propose a Sparse Gaussian process Regression-based technique to model residual dynamics. In contrast, Data-Driven MPC, a recent technique, targets aggressive maneuvers without obstacle constraints. Our proposed method is compared with Data-Driven MPC in estimating residual dynamics error, including obstacle constraints. Comparative analysis indicates that our technique reduces nominal model error by an average factor of 2. Furthermore, we evaluate our complete framework against four other trajectorytracking approaches in terms of tracking reference trajectory while avoiding collisions. Our approach demonstrates superior performance, achieving shorter flight times without sacrificing computational efficiency.
This study explores an intelligent emotional computing method baed on deep convolutional neural networks (DCNNs) aimed at accurately identifying and analyzing learners' emotional states within digital learning int...
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The article examines the application of a method for processing experimental data in measurement systems by generating hypotheses about the presence of a given set of parameters and estimating their probability. The d...
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New machine concepts, such as the 3D Servo Press, make it possible to implement and study new forming processes like the flexible hole-rolling. In combination with the ongoing development of models, new control concep...
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New machine concepts, such as the 3D Servo Press, make it possible to implement and study new forming processes like the flexible hole-rolling. In combination with the ongoing development of models, new control concepts can be developed and thus increase productivity of manufacturing systems. As part of this work, a soft sensor was developed to predict the part geometry of a polygon profile during the process of hole rolling based on the process forces and the ram position. This prediction was used in an experimental investigation to set up an inline geometry control to compensate for the geometric error due to roller deflection during the process. Copyright (c) 2025 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)
Cloud computing (CC) is a famous paradigm which provides computing resources on request via internet. Despite its many benefits, such as scalability, cost savings, and flexibility, cloud computing is vulnerable to hos...
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As a special I/O channel in the control system, the eTPU (Enhanced Time processing Unit) cooperates with the host computer to complete the corresponding functions. As the most foundational and important function in th...
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In recent years, the intersection of quantum computing and bioinformatics has emerged as a captivating frontier, promising to reshape the landscape of biological sequence analysis. DNA's ability to store vast info...
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