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检索条件"任意字段=IEEE International Conference on Distributed Computing Systems"

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Bottom-Up Resource Orchestration in Edge computing: An Agent-Based Modeling Approach 12

Bottom-Up Resource Orchestration in Edge Computing: An Agent...

引用

12th ieee international conference on Intelligent systems, IS 2024

作者： Ghasemi, Abdorasoul Schranz, Melanie Lakeside- Labs Klagenfurt Austria

ISBN: (纸本)9798350350982

Edge computing addresses delay-sensitive microservices near applications, supplementing cloud computing. The dynamic nature of resources and workloads in edge clusters challenges traditional machine learning tools for resource prediction and allocation for each request (pod in the Kubernetes context). This paper models edge infrastructure as a multi-agent system with a master, a worker, and two types of arriving pods: rigid and elastic. Rigid pods have an estimate of their CPU/RAM demands, and strict execution times, and may only utilize some assigned resources, leading to slack. Elastic pods have more flexible execution times and aim to utilize these slack resources. We propose a scalable bottom-up algorithm that maintains the coarse-grained footprint of deployed rigid pods in a few buckets. The algorithm selects an appropriate bucket based on the demand of the new arriving elastic pod and chooses the host rigid pod randomly and with uniform probability from that bucket. We evaluate the system performance in terms of CPU/RAM utilization and the satisfaction rate of pods, comparing the results with random and non-scalable best strategies. Our findings show that the bottom-up swarm intelligence-inspired mechanism can complement the inefficiency in estimating the exact demand needs in a dynamic edge environment. © 2024 ieee.

关键词： Swarm intelligence

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VANETGuard: A Secure Hybrid Trust Management System for VANETs 16

VANETGuard: A Secure Hybrid Trust Management System for VANE...

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16th international conference on Ambient systems, Networks and Technologies Networks, ANT 2025 / 8th international conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Almaziad, Reem Kurdi, Heba Department of Computer Science King Saud University Riyadh Saudi Arabia

This study introduces a secure and scalable hybrid trust management system for Vehicular Ad Hoc Networks (VANETs), designed to detect and mitigate diverse malicious activities, including Sybil attacks, Denial of Service (DoS), and data forgery. Integrating entropy-based anomaly detection, Bayesian reputation updating, and the IOTA Tangle as a distributed ledger, the system ensures robust, real-time trust evaluation in dynamic vehicular environments. Rigorous testing against adversarial scenarios demonstrated high detection accuracy, low latency, and resilience under varied attack conditions. Key contributions include enhanced scalability through edge computing, secure reputation storage using distributed Ledger Technology (DLT), and real-time anomaly detection. © 2025 Elsevier B.V.. All rights reserved.

关键词： Edge computing

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Development of Personalized Mobile Information Service Platform of University Library Based on Multi-Core Processor and Cloud computing Platform 2

Development of Personalized Mobile Information Service Platf...

引用

2nd ieee international conference on distributed computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Mishra, Saket Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350347456

The library can quickly create and manage its own data center. University library will allow to maintain greater control over applications and data storage that contain sensitive private information about students. Using multi-core processors are considered the design of future product microprocessors. Not only is it a solution for Central Processing Unit (CPU) speeds, also reduces consumption because many cores at lower frequencies collectively produce less to the cores with their total computing. Existing methods are K-Nearest Neighbor (KNN) and Principle Component Analysis (PCA) is an information resources have gradually shifted from digital analog analysis the Digital libraries are beginning to enter the computing increased the cost and time. Cloud computing Digital Information Resources Integration Library is suitable for architecture model applications, to provide a new solution for digital library, construction intensity and digital resource sharing. To overcome the issue in this work proposed Sequence Recurrent Neural Network (SRNN) using mobile library services, some of which can be used by various university libraries and other services already find help libraries that gather their information in a fast and time-limited way without external and time restrictions. The value of this is Help of University libraries can identify and adapt mobile processors. With these mobile initiatives, libraries can offer a wide range of mobile services to interested users. It has been shown by test results that adding processor cores to the data center increases system performance, reduces consumption, and has other benefits. © 2023 ieee.

关键词： Program processors

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Utilizing AWS Cloud-Enhanced VPN and VPC Integration to Improve Data Security and Access Control in Library Management systems 2

Utilizing AWS Cloud-Enhanced VPN and VPC Integration to Impr...

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2nd international conference on Intelligent Cyber Physical systems and Internet of Things (ICoICI)

作者： Sahoo, Sasmita Swain, Adyasha Mohapatra, Sunil Kumar Pattanaik, Swarupa Senapati, Arpita Centurion Univ Technol & Management Dept Comp Sci & Engn Bhubaneswar India

ISBN: (纸本)9798331540661;9798331540678

Digital information exchange has become commonplace due to the growth of the internet and information technology breakthroughs. Academic institutions are placing a greater emphasis on developing digital campuses, of which digital libraries are an essential part. Though cloud computing is a well-known idea, what matters more are the security precautions performed within the cloud environment. Numerous technologies have been developed in recent years to offer cloud network security. This paper investigates the integration of Virtual Private Networks (VPNs) for improving data security and access control in library management systems, which enables logical separation between public and private clouds, to facilitate remote access to digital library resources securely and effectively. There are undoubtedly many risks to the public cloud because resources within it are accessible to everybody. With the aid of the Amazon Virtual Private Cloud (VPC), these potential risks are effectively avoided. We have presented VPC principles and examples in this article, along with an explanation of the benefits and necessity of VPC. The implementation involves creating a VPC, setting up gateways, configuring route tables, and establishing both private and public subnets. Secure Shell (SSH) keys and EC2 instances are utilized to deploy OpenVPN, followed by RDP connections. This setup provides a secure, encrypted tunnel specifically for the library management website, allowing authorized users to access resources from anywhere.

关键词： Virtual Private Network Virtual Priavte Cloud Cloud computing Digitization OpenVPN Amazon Web Service Cloud Service Cyber Security Library Management System

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High-Resolution Time-Frequency Analysis of EEG Signals for Affective computing 46

High-Resolution Time-Frequency Analysis of EEG Signals for A...

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46th Annual international conference of the ieee Engineering in Medicine and Biology Society, EMBC 2024

作者： Veeranki, Yedukondala Rao Posada-Quintero, Hugo F. University of Connecticut Storrs United States

ISBN: (纸本)9798350371499

Affective computing is a critical aspect of human-computer interaction. Electroencephalographic (EEG) signals, which reflect electrical brain activity, are widely used for the understanding of human emotional states. However, these signals are nonlinear and nonstationary, making traditional analysis methods insufficient. To address these challenges, recent studies have focused on time-frequency analysis. In this paper, we propose a variable frequency complex demodulation (VFCDM) approach to obtain high-resolution time-frequency spectra (TFS) from EEG signals. First, we compute the TFS using the time-varying optimal parameter search technique to capture the spectral information. Then we generate VFCDM sub-bands and extract statistical features from each of the sub-bands. These features are then used with the Random Forest algorithm to classify arousal and valence dimensions. Our results demonstrate the robustness of this approach and its ability to accurately discriminate complex affective dimensions. The δ-VFCDM and γ-VFCDM bands produced the highest F1 scores of 71.80% for Arousal and 69.55% for Valence differentiation. This work significantly advances EEG-based affective computing and opens avenues for more emotionally attuned human-computer interaction systems. © 2024 ieee.

关键词： Decision trees

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Protecting Data from DDOS Attack in a Cloud Based Intrusion Detection System Security through Enhanced RSA Algorithm 2

Protecting Data from DDOS Attack in a Cloud Based Intrusion ...

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2nd ieee international conference on Communication, Security and Artificial Intelligence, ICCSAI 2023

作者： Naik, Pramod Kumar Divya, S. Mohan, M. Velusamy, Jayaraj Radhakrishnan, P. Rajasekaran, Arun Sekar Dayananda Sagar University Bengaluru Department of Cse India Biomedical Engineering Dr. N.G.P. Institute of Technology India Kpr Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore India Nehru Institute of Engineering and Technology Department of Electronics and Communication Engineering Tamilnadu India School of Cs and Ai Sr University Telangana Warangal India Sr University Department of Ece Telangana Warangal India

ISBN: (纸本)9798350369960

Since cloud computing platforms have become an essential component in a range of different industries, it is still challenging to ensure that user data and system resources will remain secure inside these settings. This paper proposes a methodology to identify and mitigate unwanted traffic and packets, specifically duplicate packets, in cloud computing envi- ronments. The procedure requires the creation of an IntrusionFinder and Detector (IF-AD) system that allots secondary storage and keeps user information in a secure manner. This technique does a comparison between the sizes of downloaded files and the sizes of the original files, searching for any variations between the two that would suggest a probable distributed denial of service assault (DDoS). The RSA cryptography procedure is employed in order to further strengthen the degree of security that is provided by any future file transfers that may take place. The problem that has been identified and a potential solution for has been proposed with the intention of enhancing the safety of cloud-based systems by identifying and preventing unauthorised access to files as well as modifications to them. © 2023 ieee.

关键词： Cloud computing decryption duplicate packets encryption Intrusion-Finder and Detector RSA

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Proceedings - 2023 ieee international conference on Web Services, ICWS 2023

Proceedings - 2023 IEEE International Conference on Web Serv...

引用

2023 ieee international conference on Web Services, ICWS 2023

ISBN: (纸本)9798350304855

The proceedings contain 94 papers. The topics discussed include: MVGCL: multi-view graph contrastive learning for service recommendation;a knowledge service framework for fault diagnosis of low-earth orbit satellite constellation;secure cross-domain medical data sharing based on distributed cloud and blockchain services;a bidirectional representation recommendation based on relevance information enhancement to solve user interest drift;on the suitability of ai for service-based adaptive supply chains in smart manufacturing;a multiple-path learning neural network model for code completion;ExpoEv: enhancing social recommendation service with social exposure and feature evolution;a novel logic-based adaptive monitoring for composite edge services;a two-stage preference learning method based on graph neural networks for preference service;and FedWM: federated crowdsourcing workforce management service for productive laziness.

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Early Forest Fire Prediction System Using Wireless Sensor Network 2

Early Forest Fire Prediction System Using Wireless Sensor Ne...

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2nd ieee international conference on Device Intelligence, computing and Communication Technologies, DICCT 2024

作者： Thangam, S. Sri Sai Samhitha, J. Adarsh Sagar, K. Yaswanth, Julakanti Sai Haritha, Kundula Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering India

ISBN: (纸本)9798350372847

Wireless sensor network (WSN), is a collection of sensors that is used for monitoring the activities in a given environment. They are used in the forests for fire detection wherea large number of sensor nodes are placed to detect the fire inits early stages. Forest fires are the main reason which affect the wildlife and many living creatures. The project performs a comparative analysis between the traditional system and the new system developed used to predict forest fires early using the Wireless sensor network for detecting forest fires with the goal of monitoring the scale and intensity of the wildfire ignited at forests. The solution involves deploying the fire sensing sensors across the forest area, calculating Fire Whether Index (FWI) of the regions, establishing data communications between the sensors using the protocol to create dynamic routing paths across the Wireless Sensor Network [7]. These paths are developed based on several factors such as fire, energy, weather index and security. Tracing the multi dynamic route is established using star topology where the red alert zones send the alert message to all the nearby base stations. Using Net Logo simulator this project analyses the performance of the traditional systems and new systems based on network power, fire detection efficacy and the overall power consumed by the fires alerting systems. © 2024 ieee.

关键词： Fires

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Decentralised Biomedical Signal Classification using Early Exits 21

Decentralised Biomedical Signal Classification using Early E...

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21st ieee Interregional NEWCAS conference (NEWCAS)

作者： Li Xiaolin Vandierendonck, Hans Nikolopoulos, Dimitrios S. Ji, Bo Cardiff, Barry John, Deepu Univ Coll Dublin Dublin Ireland Queens Univ Belfast Belfast Antrim North Ireland Virginia Tech Blacksburg VA USA

ISBN: (纸本)9798350300246

This paper presents a decentralised signal classification approach for data acquired using Internet of Things (IoT) wearable sensors. Traditionally, data from IoT sensors are processed in a centralised fashion, and in a single node. This approach has several limitations, such as high energy consumption on the edge sensor, longer response times, etc. We present a distributed processing approach for convolutional neural network (CNN) based classifiers where a single CNN model can be split into multiple sub-networks using early exits. To reduce the transfer of large feature maps between sub-networks, we introduced an encoder-decoder pair at the exit points. Processing of inputs that can be classified with high confidence at an exit point will be terminated early, without needing to traverse the entire network. The initial sub-networks can be deployed on the edge to reduce sensor energy consumption and overall complexity. We also experimented with multiple exit point locations and show that the point of exit can be adjusted for trade-offs between complexity and performance. The proposed system can achieve a sensitivity of 98.45% and an accuracy of 97.55% for electrocardiogram (ECG) classification and save 60% of the data transmitted wirelessly while reducing 38.45% of the complexity.

关键词： ECG classification Arrhythmia Decentralised Inferencing distributed Network Deep Learning

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distributed Finite-Time Consensus Control of Multi-Agent systems with Communication Topology Switching 6

Distributed Finite-Time Consensus Control of Multi-Agent Sys...

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6th international conference on Industrial Artificial Intelligence, IAI 2024

作者： Guoliang, Wang Yaqiang, Lyu School of Information and Control Engineering Liaoning Petrochemical University Fushun China

ISBN: (纸本)9798350356618

In this paper, in the context of distributed control of heterogeneous battery energy storage systems in a droop control microgrid, based on the consensus theory of multi-agent systems, this paper proposes a distributed finite-time control strategy. Each agent in this strategy only needs to obtain its own information and neighbor information through a sparse communication network, and the topology of the communication network between the agents is time-varying, and its switching process satisfies the Markov process, which enables the multi-intelligent agent system to reach an average consensus in finite time under the condition of the limitation of the number of controllers. The theoretical analysis clearly reveals the consistency and convergence of the proposed control strategy. In addition, the proposed control strategy improves the synchronization performance over the traditional one. The effectiveness and superiority of the proposed strategy is also verified through simulation. © 2024 ieee.

关键词： Battery storage

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