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检索条件"任意字段=Proceedings of the 15th International Conference on Distributed Computing Systems"

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DOSP: distributed computing-Based Operating systems Labs Platform 15

DOSP: Distributed Computing-Based Operating Systems Labs Pla...

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15th international conference on Computer Research and Development, ICCRD 2023

作者： Huang, Haoming Song, Lihua North China University of Technology Department of Computer Science Beijing China

ISBN: (纸本)9781665487504

Operating systems (OS), as a core course in Computer Science, is given much attention by all universities all over the world. Labs are the most important part of the course, and universities apply different solutions for it. Mainstream OS labs can be divided into two categories: Algorithm simulation-based labs are not beneficial for students to understand the actual mechanism of OS systematically;Kernel development-based labs have a higher barrier to entry and require more hardware resource, which is difficult for low-level universities to carry out. To solve the drawbacks of current labs solutions, this paper proposes a distributed computing-based OS labs platform, DOSP. In DOSP, students can perform labs in the virtualization-based pre-built environment, and get real-Time feedback from the judging system;Teachers can check students' score overview and real-Time teaching progress via the scoring system. the judging system can utilize idle resources in the PC room to perform distributed judging efficiently, to reduce the consumption of computing resources on the central server. Evaluation results show that our solution outperforms others in load capacity and scalability. As the result, it can solve many pain points in current OS lab teaching, which has good application prospects. © 2023 IEEE.

关键词： Students

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Fernet Encryption: A Secure Approach for Edge Data Protection 15

Fernet Encryption: A Secure Approach for Edge Data Protectio...

引用

15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Kulkarni, Jayashree Sidnal, Nandini Dandagi, Vidya Department of Computer Science & Engg. Graphic Era Deemed to be University Dehradun India Torrens Univeristy MIT Sydney Australia Department of Computer Science & Engg. Jain College of Engineering Belgavi India

ISBN: (纸本)9798350370249

the advent of edge computing has revolutionized data processing by bringing it closer to its origin, thereby minimizing latency, conserving bandwidth, and empowering real-time decision-making capabilities. However, the decentralized nature of edge computing presents distinct challenges, particularly in ensuring data security during transmission. this paper directs on the imperative task of identifying and implementing robust security algorithms for edge servers to fortify the network against unauthorized and malicious entities. the paper explores the utilization of the Fernet encryption algorithm for ensuring secure data transmission within edge computing environments. the findings of this study significantly contribute to the understanding and adoption of secure data transmission methodologies within edge computing ecosystems. Notably, the results highlight the categorization of vehicles interfacing with the edge server, thereby facilitating the differentiation between authenticated and unauthenticated and sharing of safety information exclusively with authenticated vehicles. ©2024 IEEE.

关键词： Data Security Decentralized systems Edge computing Fernet Encryption Algorithm Secure Data Transmission Symmetric Encryption

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Enhancing Decision-Making in Healthcare with Fog computing for Low-Latency Data Processing 15

Enhancing Decision-Making in Healthcare with Fog Computing f...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Mahale, Ameya Geetha, G. Srm Institute of Science and Technology Dept. of Networking and Communication Chennai India

ISBN: (纸本)9798350370249

the research aims to improve cloud computing efficiency using fog computing by optimising parameters such as response time and network utilisation. It also focuses on integrating Latency-Aware Modules into healthcare fog-cloud networks in order to reduce latency and to improve data security, for critical applications and improve patient outcomes.. We created a latency-aware framework that uses fog computing, deep learning algorithms, and edge tools to create a better healthcare system that better meets the needs of patients while also making healthcare more efficient, effective, and scalable.A cluster-based Fog computing system capable of autonomously collecting and analyzing discrete data from distributed IoT devices before transmitting it to the cloud to minimize connection latency and network congestion. Moreover, our system endeavors to enhance the processing speed of encrypted data without compromising accuracy or privacy. By prioritizing secure and efficient data transmission and analysis within the ecosystem, we aim to establish a robust framework for IoT operations. Additionally, efforts will be made to minimize data duplication, thereby optimizing network bandwidth and storage utilization. We have compared fog computing, cloud computing, and their combination in three areas: latency, data security, and resource management. Fog computing provides superior latency performance, cloud computing provides improved data security, and the mixed approach balances latency, security, and resource management in a better way. © 2024 IEEE.

关键词： and data security cloud computing fog computing IoT latency

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Last Night in Sweden: A Vision for Resource-Intelligent Stream Reasoning 18

Last Night in Sweden: A Vision for Resource-Intelligent Stre...

引用

18th international conference on distributed and Event-Based systems (DEBS)

作者： de Leng, Daniel Bonte, Pieter Linkoping Univ Dept Comp & Informat Sci Linkoping Sweden Katholieke Univ Leuven Dept Comp Sci Campus Kulak Kortrijk Belgium

ISBN: (纸本)9798400704437

Even though data is continually being produced by a wide range of services, harnessing this data in an effective manner at different levels of abstraction is challenging. In this vision paper, we consider how data streams representing real-world observations produced by geographically-distributed Internet of things (IoT) devices can be used to adaptively fulfill a user's information needs. To solve this information need in a generic fashion, it is up to the underlying system to configure itself, split up processing across available resources, discover data sources, integrate available data, deal with uncertainty, integrate domain knowledge, etc. this is an interdisciplinary problem, and while many fields have considered the subproblems involved, this challenge requires a novel and integrated approach when these subproblems are put together. We propose Resource-Intelligent Stream Reasoning as an overarching solution to tackle this interdisciplinary problem. We define a novel set of challenges that capture the need for an integrated approach, show the limitations in the the current state-of-the-art and define the future directions in order to realize Resource-Intelligent Stream Reasoning.

关键词： Stream Reasoning. distributed computing Stream Processing Internet of things Edge computing

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ICMLC 2023 - proceedings of the 2023 15th international conference on Machine Learning and computing

ICMLC 2023 - Proceedings of the 2023 15th International Conf...

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15th international conference on Machine Learning and computing, ICMLC 2023

ISBN: (纸本)9781450398411

the proceedings contain 96 papers. the topics discussed include: simulation analysis of binary antenna radiation field mathematical model of instrument landing system;quantum algorithm for regularized spectral clustering;parallel simulation of lid-driven flow with internal square obstacle;multi-missile path planning algorithm based on reinforcement learning;maximizing network reliability in large scale infrastructure networks: a heat conduction model perspective;a pipeline and a graph-based model for paragraph extraction: take the insurance document as an example;an improved bare bone multi-objective particle swarm optimization algorithm for solving stochastic wind-solar-small hydro power dispatch problems;distant supervision relation extraction of combination bag with hierarchical attention;multi-factor quantitative investment tactic design based on support vector machine;unexpectedly useful: convergence bounds and real-world distributed learning;stochastic compositional kernel estimation for Gaussian process models;and ensemble two stage machine learning for network abnormal detection.

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Reinforcement Learning-Based Autonomous Landing of AirSim Simulated Quadcopter in Unreal Engine 15

Reinforcement Learning-Based Autonomous Landing of AirSim Si...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Paladugula, Pruthvi Don, S. Vemulapalli, Nehith Sai Prabhat, Guggilam Sai Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India Dept. of Computer Science and Applications Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798350370249

this paper presents a novel approach for landing an autonomous quadcopter using reinforcement learning (RL) in the AirSim simulation environment running on Unreal Engine. the complicated dynamics and unpredictability of quadcopter landing procedures make them difficult to execute and frequently reduce the efficacy of conventional control techniques. In order to overcome these difficulties, the suggested RL model interacts with an incredibly lifelike simulation to learn the best landing techniques, which faithfully replicates physical principles. Impressing with notable improvements in landing precision and resilience in many scenarios, this model holds potential to improve unmanned aerial vehicle operations. By utilizing reinforcement learning within a practical simulation setting, this study advances the creation of more effective and flexible autonomous landing systems for unmanned aerial vehicles (UAVs), potentially leading to benefits in practical uses. ©2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Towards Reliable distributed Quantum computing on Quantum Interconnects 23

Towards Reliable Distributed Quantum Computing on Quantum In...

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7th international conference on the Art, Science, and Engineering of Programming (Programming)

作者： Wakizaka, Ryo Kyoto Univ Kyoto Japan

ISBN: (纸本)9798400707551

Quantum interconnects (QuICs), which connect multiple quantum devices to build distributed quantum systems, are essential for large-scale quantum information processing. While various software tools have been developed to analyze quantum programs running on QuICs, there are very few frameworks for formal reasoning about them on actual quantum devices. the lack of such tools may make distributed systems unreliable because of the complicated behavior of concurrent quantum processes and the physical constraints of quantum devices. this paper discusses the need for an infrastructure, including a distributed quantum programming language, to realize reliable distributed quantum computing.

关键词： quantum interconnects quantum internet distributed quantum computing quantum programming language formal verification

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An Algebraic Solution for Moving Target Localization in distributed MIMO Radar systems with Clock Synchronization Errors 15

An Algebraic Solution for Moving Target Localization in Dist...

引用

15th international conference on Signal Processing systems, ICSPS 2023

作者： Song, Haibo Yuan, Fu Wang, Jie Wu, Guofu College of Aerospace Science and Engineering National University of Defense Technology Changsha China

ISBN: (纸本)9781510675056

Due to the limitations of clock synchronization technology and non-ideal clocks of the sensors, it is not feasible to achieve precise clock synchronization for distributed multiple-input multiple-output (MIMO) radar systems. In this paper, a closed-form solution for locating moving target in distributed MIMO radar systems with clock synchronization errors by using the time delay and Doppler shift measurements is proposed. Specifically, a transmitter is utilized as the reference and the clock synchronization errors are introduced to establish estimation formulations about the target position and velocity, and the formulations are solved by best linear unbiased estimator firstly. then, the estimates of the target position and velocity are refined based on the relation between the reference parameters and unknowns. the proposed solution is demonstrated to be approximately unbiased and able to reach the Cramer-Rao lower bound under weak noise conditions through the theoretical derivation and numerical simulations. Furthermore, the simulations show that the proposed solution enjoys better target localization accuracy than the state-of-the-art algorithms. © 2024 SPIE.

关键词： Time delay

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An Improvised Genetic Algorithm Technique on Task Scheduling in Edge and Cloud computing systems 15

An Improvised Genetic Algorithm Technique on Task Scheduling...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Pitty, Nagarjuna Hemalatha, N. Venkata Ramana, K. Sajitha, L.P. Ramesh Babu, P. Babu, M.Dinesh Indian Institute of Science Karnataka Bengaluru India Tamilnadu Chennai India QIS College of Engineering and Technology Department of CSE Andrapradesh Ongole India R.M.K Engineering College Department of Computer Science and Business System Tamilnadu Kavaraipettai India Wollega University College of Engineering and Technology Department of Computer Science Oromia Region Nekemte Ethiopia Rajalakshmi Institute of Technology Department of Mechanical Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350370249

In current years, part cloud computing systems have received huge adoption because of their capability to provide low latency and high bandwidth offerings to users. however, one of the primary challenges in these structures is green undertaking scheduling in the presence of dynamic and heterogeneous sources. To deal with this trouble, genetic set of rules (GA) optimization strategies were proposed as a potential solution. this approach utilizes genetic operators, which include mutation and crossover, to conform a populace of potential solutions and choose the best one. by way of considering various constraints and objectives, consisting of strength consumption and make span, the GA-primarily based project scheduling technique can efficaciously optimize useful resource allocation in area cloud computing structures, at the end improving their performance and resource utilization. © 2024 IEEE.

关键词： Scheduling algorithms

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Leveraging a Custom Multi Modal OCR System for Marksheet Data Extraction 15

Leveraging a Custom Multi Modal OCR System for Marksheet Dat...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Kalra, Bhavvuk D. Suresh, Sreedath Sanjay Adithya, M. Shanmuga Priya, S. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350370249

In the current educational landscape, the transition towards digitalization has become crucial. However, the manual entry of data from traditional physical marksheets into digital systems remains a significant bottleneck in the process. Educators often spend significant amount of time and effort entering data into electronic systems, which could be better utilized for more productive *** this paper, we offer a solution to this problem. We propose an automated system that leverages Optical Character Recognition (OCR) Technology to streamline the extraction of essential information from marksheets. We discuss about the Dataset, preprocessing on the input image, Multi Modal OCR system Structure and other implementation details. We conclude the paper by a comparative study of our Multi Modal OCR system with other Commercially available OCRs like EasyOCR, PaddleOCR and PyTesseract. © 2024 IEEE.

关键词： Character Isolation CNN Data Extraction Digits Handwritten Letters Marksheets Multi Modal Neural Network Optical Character Recognition (OCR) Preprocessing Region of Interest Template Image Text Recognition

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