Papers Cloud Computing
“Cloud Computing” 태그가 달린 논문 581편 · 필터 해제
Demonstration of effective UCB-based routing in skill-based queues on real-world data
This paper is about optimally controlling skill-based queueing systems such as data centers, cloud computing networks, and service systems. By means of a case study using a real-world data set, we investigate the practic…
Cloud ComputingFairnessMAIZX: A Carbon-Aware Framework for Optimizing Cloud Computing Emissions
Cloud computing drives innovation but also poses significant environmental challenges due to its high-energy consumption and carbon emissions. Data centers account for 2-4% of global energy usage, and the ICT sector's sh…
Cloud ComputingEdge-computingOptimization of bi-directional gated loop cell based on multi-head attention mechanism for SSD health state classification model
Aiming at the critical role of SSD health state prediction in data reliability assurance, this study proposes a hybrid BiGRU-MHA model that incorporates a multi-head attention mechanism to enhance the accuracy and stabil…
Binary ClassificationCloud ComputingSecure Data Access in Cloud Environments Using Quantum Cryptography
Cloud computing has made storing and accessing data easier but keeping it secure is a big challenge nowadays. Traditional methods of ensuring data may not be strong enough in the future when powerful quantum computers be…
Cloud ComputingRethinking Dynamic Networks and Heterogeneous Computing with Automatic Parallelization
Hybrid parallelism techniques are essential for efficiently training large language models (LLMs). Nevertheless, current automatic parallel planning frameworks often overlook the simultaneous consideration of node hetero…
Cloud ComputingOptimal Auction Design for Dynamic Stochastic Environments: Myerson Meets Naor
Allocation of goods and services often involves both stochastic supply and stochastic demand. Motivated by applications such as cloud computing, gig platforms, and blockchain auctions, we study the design of optimal sell…
Cloud ComputingFog Intelligence for Network Anomaly Detection
Anomalies are common in network system monitoring. When manifested as network threats to be mitigated, service outages to be prevented, and security risks to be ameliorated, detecting such anomalous network behaviors bec…
Anomaly DetectionCloud ComputingManagementPrivacy PreservingAssessing wildfire susceptibility in Iran: Leveraging machine learning for geospatial analysis of climatic and anthropogenic factors
This study investigates the multifaceted factors influencing wildfire risk in Iran, focusing on the interplay between climatic conditions and human activities. Utilizing advanced remote sensing, geospatial information sy…
Cloud ComputingCross-Cloud Data Privacy Protection: Optimizing Collaborative Mechanisms of AI Systems by Integrating Federated Learning and LLMs
In the age of cloud computing, data privacy protection has become a major challenge, especially when sharing sensitive data across cloud environments. However, how to optimize collaboration across cloud environments rema…
Cloud ComputingFederated LearningGATES: Cost-aware Dynamic Workflow Scheduling via Graph Attention Networks and Evolution Strategy
Cost-aware Dynamic Workflow Scheduling (CADWS) is a key challenge in cloud computing, focusing on devising an effective scheduling policy to efficiently schedule dynamically arriving workflow tasks, represented as Direct…
Cloud ComputingDeep Reinforcement LearningGraph AttentionSchedulingCloud-Based AI Systems: Leveraging Large Language Models for Intelligent Fault Detection and Autonomous Self-Healing
With the rapid development of cloud computing systems and the increasing complexity of their infrastructure, intelligent mechanisms to detect and mitigate failures in real time are becoming increasingly important. Tradit…
Anomaly DetectionCloud ComputingFault DetectionNatural Language UnderstandingLearning Virtual Machine Scheduling in Cloud Computing through Language Agents
In cloud services, virtual machine (VM) scheduling is a typical Online Dynamic Multidimensional Bin Packing (ODMBP) problem, characterized by large-scale complexity and fluctuating demands. Traditional optimization metho…
Cloud ComputingLarge Language ModelSchedulingSustainable Smart Farm Networks: Enhancing Resilience and Efficiency with Decision Theory-Guided Deep Reinforcement Learning
Solar sensor-based monitoring systems have become a crucial agricultural innovation, advancing farm management and animal welfare through integrating sensor technology, Internet-of-Things, and edge and cloud computing. H…
Cloud ComputingDeep Reinforcement LearningTransfer LearningAI-Driven Security in Cloud Computing: Enhancing Threat Detection, Automated Response, and Cyber Resilience
Cloud security concerns have been greatly realized in recent years due to the increase of complicated threats in the computing world. Many traditional solutions do not work well in real-time to detect or prevent more com…
Cloud ComputingEnhanced Outsourced and Secure Inference for Tall Sparse Decision Trees
A decision tree is an easy-to-understand tool that has been widely used for classification tasks. On the one hand, due to privacy concerns, there has been an urgent need to create privacy-preserving classifiers that conc…
Cloud ComputingPrivacy PreservingOn the Design of Resilient Distributed Single Time-Scale Estimators: A Graph-Theoretic Approach
Distributed estimation in interconnected systems has gained increasing attention due to its relevance in diverse applications such as sensor networks, autonomous vehicles, and cloud computing. In real practice, the senso…
Autonomous VehiclesCloud ComputingOptimized Cloud Resource Allocation Using Genetic Algorithms for Energy Efficiency and QoS Assurance
Cloud computing environments demand dynamic and efficient resource management to ensure optimal performance, reduced energy consumption, and adherence to Service Level Agreements (SLAs). This paper presents a Genetic Alg…
Cloud ComputingManagementSymmetry-Preserving Architecture for Multi-NUMA Environments (SPANE): A Deep Reinforcement Learning Approach for Dynamic VM Scheduling
As cloud computing continues to evolve, the adoption of multi-NUMA (Non-Uniform Memory Access) architecture by cloud service providers has introduced new challenges in virtual machine (VM) scheduling. To address these ch…
Cloud ComputingDeep Reinforcement LearningSchedulingTransformer-Based Model for Cold Start Mitigation in FaaS Architecture
Serverless architectures, particularly the Function as a Service (FaaS) model, have become a cornerstone of modern cloud computing due to their ability to simplify resource management and enhance application deployment a…
Cloud ComputingManagementDynamic Operating System Scheduling Using Double DQN: A Reinforcement Learning Approach to Task Optimization
In this paper, an operating system scheduling algorithm based on Double DQN (Double Deep Q network) is proposed, and its performance under different task types and system loads is verified by experiments. Compared with t…
Cloud ComputingScheduling