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检索条件"任意字段=9th International Conference on Distributed Computing Systems"

共 7450 条记录，以下是11-20 订阅

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DR-DRL: distributed Redundant Task Offloading based on Reinforcement Learning 9

DR-DRL: Distributed Redundant Task Offloading based on Reinf...

引用

9th international conference on Information Science, Computer Technology and Transportation, ISCTT 2024

作者： Lan, Shizhan Lin, Hongcai Liang, Huaqian Chen, Shan Wang, Zhenyu School of Software Engineering South China University of Technology Guangzhou China China Mobile Group Guangxi branch Co. Ltd Nanning China

ISBN: (纸本)9798350388435

Edge computing enhances task reliability by employing redundant task executions across edge nodes. Conventional decentralized task offloading strategies, based on heuristics and game theory, either focus on optimization or are based on unrealistic assumptions. Moreover, existing Deep Reinforcement Learning (DRL) task offloading approaches underperform due to discrepancies between simulated environments and real systems, and overlook task redundancy, thus failing to meet reliability requirements. this paper proposes a DRL-based approach to offload distributed redundant tasks, namely DR-DRL (Decentralized and Redundant DRL), to solve the redundancy problem of distributed task offloading under edge computing. Experimental results show that DR-DRL has about 8% higher task success rate than other benchmark methods. ©2024 IEEE.

关键词： Deep reinforcement learning

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Optimizing QoE for Virtual Reality Games on Mobile Edge Networks 9

Optimizing QoE for Virtual Reality Games on Mobile Edge Netw...

引用

9th IEEE international conference on Fog and Mobile Edge computing (FMEC)

作者： Fowler, Scott Souihi, Sami Linkoping Univ Dept Sci & Technol Commun & Transport Syst Norrkoping Sweden Univ Paris Est Creteil UPEC LISSI TincNET Vitry Sur Seine France

ISBN: (纸本)9798350366495;9798350366488

In this paper, we explore delivering mobile edge Virtual Reality (VR) gaming services with comprehensive and satisfactory Quality of Experience (QoE) across a distributed edge network. Our goal is to meet the QoE needs of all users, addressing both latency and visual considerations. However, the unique characteristics of edge-assisted mobile VR gaming distinguish our challenge from other distributed service provisioning issues. We introduce and address the challenge of provisioning QoE-centric mobile VR gaming services within a distributed edge environment by systematically capturing the unique attributes of mobile VR games. We demonstrate that this challenge can be formulated as a Mixed-Integer Quadratically Constrained Quadratic Programming (MIQCQP) problem. While mobile edge computing holds promise for mobile VR gaming, existing studies often overlook the need to deliver satisfactory QoE to a large user base. Our paper focuses on delivering QoE-centric edge-assisted mobile VR gaming services to multiple users, comprehensively addressing visual and latency concerns.

关键词： Mobile edge computing

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Performance Analysis of distributed Database System in Cloud computing Environment 9

Performance Analysis of Distributed Database System in Cloud...

引用

9th IEEE international conference on computing, Engineering and Design, ICCED 2023

作者： Prasetio, Nicholas Ferdinand, Daniel Wijaya, Brandon Christopher Anggreainy, Maria Susan Kumiawan, Afdhal Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program School of Computer Science Jakarta11530 Indonesia

ISBN: (纸本)9798350370126

this research discusses the performance evaluation of distributed database systems in a cloud computing environment Cloud computing environments allow data and applications to be stored and deployed on infrastructure located in different parts of the world. However, the use of distributed database systems in cloud computing environments can cause performance issues, such as complex data access and factors such as network latency, security, and scalability that affect system performance. therefore, performance evaluation of distributed database systems is necessary to ensure effective data management across the infrastructure. the purpose of this research is to measure and understand the performance of distributed database systems in a cloud computing environment. this is important because proper performance evaluation is needed to ensure distributed database systems can operate effectively and efficiently in such environments. this research will analyze the features of distributed database systems, factors that affect performance, how to measure and compare system performance, and how to improve system performance. Analyzing the performance of distributed database systems in a cloud computing environment can help users choose the most appropriate and efficient cloud computing platform for their business needs and improve operational efficiency. © 2023 IEEE.

关键词： distributed database systems

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Research on Wide-Area-Cloud-Platform Operations Framework for Edge-Cloud System 9

Research on Wide-Area-Cloud-Platform Operations Framework fo...

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9th international conference on Cloud computing and Big Data Analytics, ICCCBDA 2024

作者： Qin, Yuqin Liu, Jiali Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing China

ISBN: (纸本)9798350373554

With the rapid increase of data, the scale of cloud is gradually expanding, forming a wide-area cloud platform consisting of multiple data centers distributed across different locations. For industry professionals, maintaining the normal operation of such a large platform relies on reasonable system architecture and operational methods. this article provides an in-depth analysis of the operational requirements for wide-area cloud platforms, investigates relevant anomaly detection methods, and proposes suitable anomaly detection methods for high-frequency local operational status data in data center operations systems and global operational status data in central operations systems respectively. In addition, based on edge-cloud architecture, an operational framework tailored to wide-area cloud platforms is proposed to provide reference means for improving the efficiency of operations personnel. the feasibility of the framework has been verified through actual project testing. © 2024 IEEE.

关键词： Cloud computing architecture

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Energy-Efficient Scheduling of Moldable Streaming Computations for the Edge-Cloud Continuum 9

Energy-Efficient Scheduling of Moldable Streaming Computatio...

引用

9th IEEE international conference on Fog and Mobile Edge computing (FMEC)

作者： Khosravi, Sajad Kessler, Christoph Litzinger, Sebastian Keller, Joerg Linkoping Univ Linkoping Sweden Fernuniv Hagen Germany

ISBN: (纸本)9798350366495;9798350366488

We consider the problem of cost-effectively mapping a swarm of soft real-time stream processing applications with moldable-parallel tasks to multicore resources in the device-edge-cloud continuum, consisting of mobile devices, edge resources and cloud resources. We leverage flexibility from different parallelization degrees and frequency levels (DVFS) for the tasks, keeping application throughput constraints and communication bandwidth limitations while minimizing overall cost (including device/edge resource energy and cloud resource renting). We present two offline algorithmic solutions with a global view of the environment: an integer linear program (ILP) extending the crown scheduling approach for multi-layer distributed systems and a greedy heuristic algorithm. Our experimental evaluation for several real-world and synthetic scenarios shows that the time required for solving the scheduling problem to cost-optimality by the ILP is feasible for nontrivial scenarios. the heuristic achieves about 12% worse cost efficiency on average, yet operates much faster (by 1-2 orders of magnitude), allowing to scale up the problem size more than the ILP approach.

关键词： distributed stream processing Mapping Scheduling Moldable tasks Edge-Cloud continuum Energy efficiency DVFS

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Multi-Factor Trust Management in distributed Storage Networks based on Capacity and Behavior 9

Multi-Factor Trust Management in Distributed Storage Network...

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9th IEEE international conference on Fog and Mobile Edge computing (FMEC)

作者： Van thillo, Ibe Hameed, Zeeshan Pahl, Claus Univ Antwerp Dept Appl Engn Elect ICT Antwerp Belgium Free Univ Bozen Bolzano Fac Engn Bolzano Italy

ISBN: (纸本)9798350366495;9798350366488

Decentralized storage has gained popularity due to its superior fault tolerance, scalability, privacy, and security compared to traditional cloud storage solutions. However, the untrusted and potentially unreliable nature of storage nodes in Internet of things (IoT) and edge cloud settings necessitates careful selection of nodes for file storage in open and heterogeneous distributed solutions. We introduce a new trust management system for distributed storage networks that evaluates the performance of nodes in serving files to improve file placement decisions. We consider capacity and reliability as the most important parameters influencing a node's trustworthiness. Capacity refers to the available resources, while reliability is assessed based on node performance in responding to file requests and maintaining file integrity. We present a methodology to combine these two parameters into a joint trust score for node selection. Our experiments show that this trust model can enhance file placement decisions in distributed storage networks by providing more accurate estimations of the nodes' trustworthiness than the existing file placement algorithms.

关键词： Edge Cloud distributed Storage Network Trust Management Capacity Behaviour Internet of things

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IoTinuum: the IoT computing Continuum 20

IoTinuum: The IoT Computing Continuum

引用

20th Annual international conference on distributed computing in Smart Sensor systems and the Internet of things (DCOSS-IoT)

作者： Kamienski, Carlos Zyrianoff, Ivan Bittencourt, Luiz Fernando Di Felice, Marco Fed Univ ABC Santo Andre SP Brazil Univ Bologna Bologna Italy Univ Estadual Campinas Campinas SP Brazil

ISBN: (纸本)9798350369458;9798350369441

IoT smart applications must deal with the inherently distributed nature of IoT infrastructures that may vary among different deployments. For example, in urban environments, some deployments may require distributed edge nodes to support the sensors and actuators, while others may skip this processing stage and go directly to the cloud. We propose the concept of an IoT computing Continuum, or IoTinuum, with multiple computing stages spread over the distributed IoT infrastructure. We present the modeling and implementation of two urban use cases for a 6-stage IoTinuum: smart drone delivery and smart structural monitoring. In our experience, the IoTinuum improves the understanding of function placement in application development and reveals important performance tradeoffs.

关键词： edge computing fog computing IoT smart applications

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Algorithm and Hardware Co-Design for Efficient PMCMC Acceleration on FPGA

Algorithm and Hardware Co-Design for Efficient PMCMC Acceler...

引用

9th international conference on Signal and Image Processing (ICSIP)

作者： Wang, Fulong Peng, Shiyu Gong, Yuanhao Li, Minghan Liu, Shuanglong Hunan Normal Univ Coll Hunan Prov Key Lab Low Dimens Quantum Struct & Quantum Contr Key Lab Phys & Devices Postmoore Era Changsha Peoples R China

ISBN: (纸本)9798350350920

the particle Markov-chain Monte Carlo (PMCMC) method is a stochastic algorithm that combines Particle Filters (PFs) and Markov-chain Monte Carlo (MCMC) techniques. this approach is widely used in Bayesian inference for high-dimensional state spaces and nonlinear, non-Gaussian dynamic systems. However, current PMCMC accelerators face significant challenges due to their intensive computational complexity and the intricate particle routing, limiting their application in real-time scenarios. To address these challenges, we propose a novel distributed PMCMC method that leverages parallel computing to enhance hardware execution speed. Additionally, our method introduces a particle exchange scheme that not only resolves the accuracy issues caused by particle routing in distributed PMCMC but also achieves faster computing speed. Our design is implemented on a Xilinx Kintex-7 xc7k480t FPGA device. Experimental results demonstrate that our accelerator is nearly 65x faster than CPU performance, and provides speedups up to 5x compared to existing FPGA-based accelerators.

关键词： Particle Markov-chain Monte Carlo (PMCMC) Particle Filter (PF) Field Programmable Gate Arrays (FPGAs) distributed PMCMC Hardware Acceleration

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A Survey on Advanced Security and Ensured User Privacy for distributed systems 9

A Survey on Advanced Security and Ensured User Privacy for D...

引用

9th international conference on Smart and Sustainable Technologies (SpliTech)

作者： Luntovskyy, Andriy BA Dresden Univ Coop Educ Saxon Acad Hans Grundig Str 25 D-01307 Dresden Germany

ISBN: (纸本)9798350390797;9789532901351

this work is devoted to an actual survey on advanced security and ensured user privacy for (Highly-) distributed systems. the last term belongs to thin and thick apps, robot and mobile apps, (micro-)service-oriented applications, and IoT applications. the most dangerous vulnerabilities, intrusion analysis techniques and models, and countermeasures to increase the safety of the cyber-systems are discussed. AI-based methods are favored nowadays. However, generative models provide some new risks and vulnerabilities. EU legal regulations are considered. Several case studies (among others, for telemedicine and e-health) are examined.

关键词： Phishing Malware AI LLM HP FW IDS IPS Diamond Model SIEM OWASP MITRE ATT&CK

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Designing Fault-tolerant Modern Data Engineering Solutions with Reliability theory as the Driving Force 24

Designing Fault-tolerant Modern Data Engineering Solutions w...

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9th international conference on Machine Learning Technologies (ICMLT)

作者： Virmani, Ankit Kuppam, Manoj Inst Elect & Elect Engineers Piscataway NJ 08854 USA

ISBN: (纸本)9798400716379

this study has been undertaken to amalgamate the principles of Site Reliability Engineering and Data Engineering to effectively measure, monitor and manage the reliability of petabyte-scale data engineering process from collection at source to processing, analyzing, and distributing the data for appropriate decision making to improve business outcomes and system performance. Modern data architectures increasingly leverage cloud platforms, low-code systems, and serverless technologies to enable scalable data engineering. However, these innovations also introduce new complexities regarding reliability assurance. As these failure-prone yet business-critical data infrastructures continue rapid adoption, it is vital to elucidate architectural paradigms, quantified benchmarks, and procedural methodologies tailored to safeguarding dependability across heterogeneous, distributed data ecosystems. this paper will equip end users with a reusable framework ingrained with best practices to develop a blueprint for data reliability across business units of an organization.

关键词： Big Data Engineering Site Reliability Engineering Data Operations Platform Management Cloud computing

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