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

共 149810 条记录，以下是381-390 订阅

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Innovations in Cloud and Edge computing Security Safeguarding Privacy in distributed systems

Innovations in Cloud and Edge Computing Security Safeguardin...

引用

2024 international conference on Sustainable computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Jayanthi, Muthuswamy Suneel, Sajja Gupta, Manish Kansal, Vipashi Mallikarjuna Raju, K. Albawi, Ali Department of Electronics and Communication Engineering New Horizon College of Engineering Bangalore India Institute of Aeronautical Engineering Dundigal Hyderabad500043 India Lovely Professional University Phagwara India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of CSBS GRIET Bachupally Telangana Hyderabad India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq

ISBN: (纸本)9798350355338

This work advances cloud and edge computing security, especially in distrib-uted systems. The suggested response has been extensively tested and shown to improve authentication, access control, hazard detection, and data integri-ty verification. Using ablation research, this report examines how the rec-ommended strategy works together. Machine learning-based threat identification and privacy protection appear crucial to system performance. The study provides minor security tips for dispersed populations. I like how the offered method balances data encryption and decryption speed with secure multi-party computing. This balance ensures the response is achievable and adapts to evolving computing settings. After comparison, the recommended distributed system security solution is standard. Its consistently above-average performance suggests it can establish industry norms. The study im-proves cloud and edge security and opens the door to greater research and cooperation, which will improve security approaches. This study improves distributed systems and highlights how vital privacy is in cloud and edge computing. © 2024 ieee.

关键词： Cloud security

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Scheduling Delay-Sensitive Bag-of-Task Jobs with Imprecise Computations on distributed Resources

Scheduling Delay-Sensitive Bag-of-Task Jobs with Imprecise C...

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2023 ieee international conference on Computer, Information, and Telecommunication systems, CITS 2023

作者： Karatza, Helen D. Aristotle University of Thessaloniki Department of Informatics Thessaloniki Greece

ISBN: (纸本)9798350336092

The evolution of the distributed computing paradigm had as a result new computing models such as grid and cloud computing. Furthermore, in these environments it is common to run complex parallel applications thus making the employment of appropriate scheduling strategies of paramount importance. This research examines the scheduling of multiple-task applications of bag-of-tasks type that have different characteristics, utilizing imprecise computations. Two scheduling schemes are utilized in a distributed system. Their performance is evaluated and compared using simulation. The experimental results demonstrate that the proposed scheduling technique that considers the delay sensitivity of the applications and allows partial task executions, can provide significant performance improvement at the expense of a low decrease in the results precision. © 2023 ieee.

关键词： distributed computer systems

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Governing Resource Failures through Reinforcement Learning Scheduling in Fog/Edge computing: A Review

Governing Resource Failures through Reinforcement Learning S...

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ieee international conference on Automatic Control and Intelligent systems (I2CACIS)

作者： Muhamad, Aliyu Hussin, Masnida Univ Putra Malaysia UPM Fac Comp Sci & Informat Technol Serdang 43400 Selangor Darul Malaysia

ISBN: (纸本)9798350372113;9798350372106

The exponential growth of IoT applications due to user demands necessitates the emergence of reliable fog/edge computing systems. Because of the wide-open area of these systems, the tendency for failure in communication channels and computing nodes (resources) is unpredictable, especially in real-time IoT applications. Several studies have aimed at tackling fault and failure issues by employing a variety of resource management strategies. Most studies use heuristics or conventional scheduling approaches that leverage the use of reinforcement learning. The element of reinforcement learning aims to support better governance when resource faults and failures occur. This paper provides an analysis of the implementation of reinforcement learning (RL) into fault-tolerant scheduling in fog/edge computing systems. The efficacy of fault-tolerant scheduling is claimed to be improved through RL with regard to system performance. We grouped the discussion based on three themes: resource failures, reinforcement learning (RL) in general, and RL scheduling for fault tolerance. The discussion could further derive solutions for overcoming the challenges of resource failures in fog/edge systems.

关键词： Fog/edge computing fault tolerance reinforcement learning scheduling review study

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Designing Social Good Semantic computing Architectures for the Long Tail: Case Studies, Evaluation, and Challenges 18

Designing Social Good Semantic Computing Architectures for t...

引用

18th ieee international conference on Semantic computing (ICSC)

作者： Kejriwal, Mayank Univ Southern Calif Informat Sci Inst Los Angeles CA 90089 USA

ISBN: (纸本)9798350385359

Many real-world systems, especially systems characterized by high social activity (such as the Web), tend to obey power law distributions and thereby have a significant 'long tail'. We argue that researching, developing and designing semantic computing systems for the long tail, especially dependent on inductive AI, constitutes an important class of problems, not least because the long tail is challenging both technically and socially. By its very nature, the long tail is irregular, testing the generalization capabilities of the state-of-the-art, especially in architectures and interfaces that are built on some form of machine learning or statistical inference (including large language models). As machine learning and generative AI continues to be integrated into more front facing systems, the issue of the long tail cannot be ignored by either the systems engineering or the AI communities. We present two case studies with important social consequences (fighting human trafficking online, and managing information effectively and in real-time during humanitarian crises) where semantic computing and AI platforms specifically designed to handle long-tail challenges find critical application, and sometimes with drastically different design choices compared to designing only for the short tail (with the main goal of maximizing average accuracy).

关键词： Long tail social good crisis response human trafficking

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Construction of a Load-testing Environment for distributed systems Including Idle Computers 25

Construction of a Load-testing Environment for Distributed S...

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25th ieee international conferences on High Performance computing and Communications, 9th international conference on Data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Nagashima, Yuya Higashino, Masayuki Kawamura, Takao Tottori University Tottori Japan

ISBN: (纸本)9798350330014

In recent years, many educational institutions have adopted information systems such as e-Learning platforms and groupware. However, these existing information systems often have significant installation, operation, and maintenance costs. Moreover, on-premise systems require expensive servers and cloud computing systems can accumulate high maintenance expenses. To address this issue, we have proposed that utilizes idle resources (idle computers) in an organization's information system. One of the characteristics of idle computers is that communication lines can be connected or disconnected at arbitrary times according to the operations of the original users. In general, the distributed system uses an idle computer as an unstable resource. However, our proposed system requires tolerating them as normal behaviors, and it requires a test environment for this problem. In this paper, we propose a load-testing environment to use idle computers having unstable behaviors in a distributed system. We also implemented and applied the proposed environment to a distributed e-Learning system. The result shows efficiency in showing behavior of unstable behaviors of idle computers to developers. © 2023 ieee.

关键词： Information systems

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Scalable computation of fuzzy joins over large collections of JSON data

Scalable computation of fuzzy joins over large collections o...

引用

ieee international conference on Fuzzy systems (FUZZ-ieee)

作者： Uhartegaray, Remi D'Orazio, Laurent Damigos, Matthew Kalogeros, Eleftherios Univ Rennes ENSSAT Lannion France Univ Rennes CNRS IRISA Lannion France Ionian Univ Dept Arch Lib Sci & Museol Corfu Greece

ISBN: (纸本)9798350332285

Fuzzy joins are widely used in a variety of data analysis applications such as data integration, data mining, and master data management. In the context of Big Data, computing fuzzy joins is challenging due to the high computational cost required and the communication cost. While on one hand big fuzzy joins on relational data and on the other hand joins on tree-structured data have been investigated in the literature, to the best of our knowledge, combining the two is still an open problem. In this context, we study methods for leveraging distributed environments in order to compute fuzzy joins over large collections of JSON documents. Our algorithms take into account both the text-similarity of the joining data, as well as its structural similarity.

关键词： fuzzy join similarity trees JSON distributed computation

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Research on Concurrent Destruction of Embedded High-Availability distributed computing Platform 24

Research on Concurrent Destruction of Embedded High-Availabi...

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24th ieee/ACIS international conference on Computer and Information Science, ICIS 2024

作者： He, Qinhan Liu, Jinhui He, Lijun Zhou, Guangfei School of Artificial Intelligence Xidian University Xi'an China School of Computer Science and Technology Xidian University Xi'an China Aeronautics Computing Technique Research Institute Xi'an China

ISBN: (纸本)9798350376647

The embedded distributed computing platform runs large-scale tasks with high complexity and high computing capacity requirements, and divides the embedded tasks required by super computing capacity into multiple independent sub-tasks, which can be simultaneously allocated to multiple computing nodes for paralleled execution. This paper researches that the embedded high-availability distributed computing platform ensures the real-time and deterministic requirements of embedded system function execution through the distribution of computing resources, network communication resources and storage resources, and implements the allocation and execution of distributed tasks under static partition configuration based on the distributed computing framework of the Actor model. In the paper, the destruction technology of large-scale storage resources in embedded high-availability distributed computing platform is also studied, the concurrent destruction is proposed, which improves the efficiency of destructive power input, solves the problems of large amount of computing nodes destruction, large destructive current and long destructive duration of large-scale storage resources in embedded system, and effectively solves the leakage of key information. © 2024 ieee.

关键词： Concurrent destruction distributed computing High availability

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distributed Cyber Physical systems Software Model Checking using Timed Automata 26

Distributed Cyber Physical Systems Software Model Checking u...

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26th ieee international Symposium on Real-Time distributed computing (ISORC)

作者： Ghosh, Purboday Karsai, Gabor Vanderbilt Univ Inst Software Integrated Syst 221 Kirkland Hall Nashville TN 37235 USA

ISBN: (纸本)9798350339024

Formal validation of the design and properties of distributed software entities for Cyber Physical systems (CPS) is challenging due to the non-linear sequence of operations and multiple possible inter-leavings of events and processes. Current model-checking tools are more suited to represent independent systems or pieces of code that are self-contained and rarely consider interactions between different participants of a composite distributed software application. This paper introduces an automated model generation tool for distributed CPS software applications written in a software framework called RIAPS. The tool combines the application model, edge deployment architecture, and individual component level source code annotated with user-supplied timing parameters to produce a network of Timed Automata models compatible with the popular model checker UPPAAL. The generated model can then be verified using UPPAAL's formal verification engine. The article uses a simple distributed application example CPS to demonstrate how the tool can be used to verify and compare the design and timing of different deployment configurations.

关键词： cyber physical systems distributed systems timed automata UPPAAL model-based design verification

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Proactive Content Caching via Interplay Between Deep Learning and Stochastic Optimization 21

Proactive Content Caching via Interplay Between Deep Learnin...

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21st ieee international conference on Mobile Ad-Hoc and Smart systems (MASS)

作者： Park, Yongmoon Lee, Kyungtae Choi, Minseok Kim, Yeongjin Inha Univ Incheon South Korea Kyung Hee Univ Yongin South Korea

ISBN: (纸本)9798350363999;9798350364002

The increasing demand for video data traffic, along with the proliferation of smart devices, poses significant challenges to content and Internet service providers. In response to this challenge, content caching on mobile edge computing (MEC) servers has emerged to reduce content download latency. However, existing caching solutions often assume stationary content popularity or require real-time knowledge of popularity, which does not align with real-world scenarios. To address these limitations, we introduce ProCache, a novel content caching algorithm. ProCache takes into account spatial and temporal monetary budget sharing for caching, content sizes, and original server locations while dealing with uncertain regional content popularity. The goal of ProCache is to minimize the long-term expected content download latency overall active users, comprising two key components. First, the deep learning module includes the 1DCNN-LSTM-Dense layered deep learning model for predicting future content requests and the data mapping module which makes the model focus more on the request trend rather than the magnitude. Second, based on our predictions, the stochastic optimization module runs a dynamic content caching algorithm based on the Lyapunov optimization technique that operates in a fully distributed manner by region and ensures overall performance bounds. Trace-driven simulations using the YouTube dataset demonstrate that ProCache outperforms existing prediction models and content caching algorithms.

关键词： Content Caching Deep learning Edge computing Proactive caching Stochastic optimization

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Power Factor Improvement in ieee-33 Radial Distribution systems using Fruit Fly Algorithm Compared with Bat Algorithm by Optimizing the DG Size 3

Power Factor Improvement in IEEE-33 Radial Distribution Syst...

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3rd international conference on Automation, computing and Renewable systems, ICACRS 2024

作者： Pujar, Pavan Lavanya, M. Department of Electrical and Electronics Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai602105 India

ISBN: (纸本)9798331532420

Power factor improvement in Radial Distribution systems (RDS) is done by placing distributed Generation (DG) in the best possible location, this study compares two optimization algorithms: the innovative Fruit Fly Algorithm (FFA) and the Bat Algorithm (BA). Materials and Methods: To ascertain the ideal location and size of distributed generators (DGs) inside radial distribution power networks, the Fruit Fly Algorithm and Bat Algorithm are utilized. With a power level of 0.8, the sample size of 14 samples was determined using G*Power for two groups. Results: Based on the data, FFA performs better than BA at raising the Power Factor. The computed significance value of 0.941 (p>0.05) suggests that the difference is not statistically significant. Conclusion: The FFA-based optimization strategy outperforms the BA-based method (0.9089) in terms of Power Factor improvement (0.9132). © 2024 ieee.

关键词： DC distribution systems

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