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Towards Trust-Centric networking: A General Model for Trust Evaluation

Towards Trust-Centric Networking: A General Model for Trust ...

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IEEE international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Andrés F. Murillo Ayoub Messous Andikan Otung Motoyoshi Sekiya Fujitsu Research of Europe Slough UK Fujitsu Laboratories Kawasaki Japan

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Advances in networking and computing are moving society towards a cyber space, in which more aspects of our daily lives are being conducted over the Internet. This movement generates concerns regarding trust between the parties involved in these aspects. Nevertheless, trust is a broad topic and thus it is challenging to define a unified mechanism for evaluating trust in communication networks. This article focuses on presenting a general model of trust in communication networks that is flexible enough to be implemented by a wide range of use cases. The model is based on the concept of trust functions, a type of relationship used to evaluate trust. Trust functions are evaluated between two subjects, based on the action that is about to take place and the objects being affected by that action. We use this model to describe a use case of Trust Enhanced networking and present a discussion regarding trust in communication networks and future challenges.

关键词： Privacy Computational modeling Network security Internet Communication networks

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Optimizing Yinyang K-Means Algorithm on ARMv8 Many-Core CPUs 22nd

Optimizing Yinyang K-Means Algorithm on ARMv8 Many-Core CPU...

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22nd international conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2022

作者： Zhou, Tianyang Wang, Qinglin Yin, Shangfei Hao, Ruochen Liu, Jie Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China School of Computer Science National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783031226762

K-Means algorithm is one of the most common clustering algorithms widely applied in various data analysis applications. Yinyang K-Means algorithm is a popular enhanced K-Means algorithm that avoids most unnecessary calculations using triangle inequality. However, Yinyang K-Means algorithm is time-consuming when the problem size is large. Due to the influence of performance and energy-efficiency, ARM CPUs have appeared in high performance computing. Therefore, it is very interesting to accelerate Yinyang K-Means algorithm on ARM CPUs. In this paper, we propose an efficient parallel implementation of Yinyang K-Means algorithm on ARMv8 many-core CPUs by means of vectorization, NUMA affinity memory optimization and data layout optimization. The experiment on two ARMv8 many-core CPUs has shown that our implementation can achieve up to 5.6 times faster than the open-source multi-threaded one of Yinyang K-Means algorithm. To the best of our knowledge, this is the first work that studies the optimization of Yinyang K-Means algorithms on ARMv8 CPUs. © 2023, Springer Nature Switzerland AG.

关键词： K-means clustering

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Message from conference Chairs

Proceedings - 22nd IEEE/ACIS International Conference on Sof...

引用

proceedings - 22nd IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, networking and Parallel/distributed computing, SNPD 2021-Fall 2021年 VIII页

作者： Stenzel, Roland Yau, Her-Terng University of Applied Sciences Dresden Germany National Chin-Yi University of Technology Taiwan

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Towards Implementation of Privacy-Preserving Federated Learning Aggregation Using Multi-key Homomorphic Encryption 25th

Towards Implementation of Privacy-Preserving Federated Lear...

引用

25th international conference on Internet computing and IoT, ICOMP 2024, and 22nd international conference on Embedded Systems, Cyber-physical Systems, and Applications, ESCS 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied computing, CSCE 2024

作者： Boudko, Svetlana Norwegian Computing Center Oslo Norway

ISBN: (纸本)9783031859229

Federated Learning is a machine learning approach where a model is trained across multiple decentralized edge devices. Since the data are not uploaded to a server, this approach is particularly useful for data protection and efficient computation. Further, it can be combined with privacy-preserving technologies, e.g., homomorphic encryption for enhanced data protection. Considering all these elements, a practical solution will require an efficient multikey homomorphic encryption as well as an effective integration of federated model aggregation and multikey generation processes. The paper studies the related work for homomorphic encryption in the context of federated learning and outlines the rationale behind practical design of secure federated learning. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： distributed computer systems

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Accelerating GPU-Based Out-of-Core Stencil Computation with On-the-Fly Compression 22nd

Accelerating GPU-Based Out-of-Core Stencil Computation with ...

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22nd international conference on Parallel and distributed computing, Applications and Technologies (PDCAT 2021)

作者： Shen, Jingcheng Wu, Yifan Okita, Masao Ino, Fumihiko Osaka Univ Osaka 5650871 Japan

ISBN: (纸本)9783030967727;9783030967710

Stencil computation is an important class of scientific applications that can be efficiently executed by graphics processing units (GPUs). Out-of-core approaches help run large scale stencil codes that process data with sizes larger than the limited capacity of GPU memory. Nevertheless, performance of out-of-core approaches is always limited by the data transfer between the CPU and GPU. Many optimizations have been explored to reduce such data transfer, however, published results on the use of on-the-fly compression are insufficient. In this study, we propose a method that accelerates GPU-based out-of-core stencil computation with on-the-fly compression, introducing a novel data compression scheme that solves the data dependency between contiguous decomposed data blocks. We also modify a widely used GPU-based compression library to support pipelining that overlaps data transfer with computation. Experimental results show that the proposed method achieved a speedup of 1.2x compared with a method that involves no compression. Moreover, although precision loss caused by compression increased with the number of time steps, it was trivial up to 4,320 time steps, demonstrating the usefulness of the proposed method.

关键词： High performance computing On-the-fly compression Stencil computation Simulation GPGPU

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Research on distributed Database Stability Testing Platform based on Chaos Engineering

Research on Distributed Database Stability Testing Platform ...

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IEEE international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Chaolun Wang Jiaxing Yang Xiaolu Han Jianrui Ma Siyuan Liu Pengwei Ma China Academy of Information and Communications Technology Beijing China

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

With the fast development of information technology, the databases used as the fundamental storage and computing component of information system have to deal with much more complicated scenarios with high frequency and concurrency. distributed databases are becoming more and more common in data-intensive industries such as banking and telecommunications. The selection of distributed database products requires comprehensively consider the function, performance, security, ease of use and stability of the product. The stability of distributed database is known to be difficult in testing and product selection. The method widely used in database testing is TPC-DS (transaction processing performance council-decision support) benchmark, which is only suitable for functional and performance testing. To deal with this drawback, a distributed database stability testing platform based on chaos engineering methodology is developed. Through the perturbation injection by using the stability testing platform, the performance fluctuation of the database under pressure condition can be observed, and the stability of the database can then be evaluated.

关键词： Chaos Industries Urban areas distributed databases Transportation Software Telecommunications

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Current Advances on Cloud-Based distributed computing for Forest Monitoring 22nd

Current Advances on Cloud-Based Distributed Computing for Fo...

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22nd international Scientific and Practical conference Information and Communication Technologies and Sustainable Development, ICT and SD 2022

作者： Shelestov, Andrii Salii, Yevhenii Hordiiko, Nataliia Yailymova, Hanna National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute" Beresteiskyi Ave. 37 Kyiv03056 Ukraine Space Research Institute National Academy of Sciences of Ukraine and State Space Agency of Ukraine Glushkov Ave. 40 Kyiv03187 Ukraine

ISBN: (纸本)9783031468797

One of the most important tasks related to environmental protection is forests monitoring. Meanwhile, specialists deal with the problem of big data and the need to utilize powerful computing resources that are not always available. Cloud solutions (CREODIAS, Google Earth Engine, etc.) provide instant satellite data access and the ability to quickly and conveniently process geospatial data in the cloud and use it to search for information products. Forest monitoring is supported by the European Commission (EU project SWIFTT), the World Wildlife Fund and others. This work analyzes Sentinel-2 satellite spectral channels, which distribution of pixel values was constructed for diseased and healthy forests, and the possibility of separating these two classes was analyzed based on the Bhattacharya distance. The informativeness of time series application of the normalized difference vegetation index (ndVI) was analyzed. The assumption that the average value of ndVI decreases and the standard deviation increases when the forest changes is confirmed. Getting results for large areas will lead to a big data problem. Therefore, the structure of the pilot information system is proposed as the basis for a further cloud solution with the development of a machine (deep) learning model for forest monitoring in any territory (including Ukraine). This system allows monitoring forests dynamics based on time series of satellite data at the country level and worldwide. This will be an important step for Ukraine as a potential member of the EU in the field of providing information services and monitoring the most sensitive natural resources. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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Latency-Optimal Pyramid-based Joint Communication and Computation Scheduling for distributed Edge computing 42

Latency-Optimal Pyramid-based Joint Communication and Comput...

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42nd IEEE international conference on Computer Communications, INFOCOM 2023

作者： Chen, Quan Wang, Kaijia Guo, Song Shi, Tuo Li, Jing Cai, Zhipeng Zomaya, Albert Guangdong University of Technology School of Computers Guangzhou China Hong Kong Polytechnic University Department of Computing Hong Kong Tianjin University College of Intelligence and Computing Tianjin China Georgia State University Department of Computer Science Atlanta United States University of Sydney School of Computer Science Sydney Australia

ISBN: (纸本)9798350334142

By combing edge computing and parallel computing, distributed edge computing has emerged as a new paradigm to accelerate computation at the edge. Considering the parallelism of both computation and communication, the problem of Minimum Latency joint Communication and Computation Scheduling (MLCCS) is studied recently. However, existing works have rigid assumptions that the communication time of each device is fixed and the workload can be split arbitrarily small. Aiming at making the work more practical and general, the MLCCS problem without the above assumptions is studied in this paper. Firstly, the MLCCS problem under a general model is formulated and proved to be NP-hard. Secondly, a pyramid-based computing model is proposed to consider the parallelism of communication and computation jointly, which has an approximation ratio of 1 + δ, where δ is related to devices' communication rates. An interesting property under such computing model is identified and proved, i.e., the optimal latency can be obtained under arbitrary scheduling order when all the devices share the same communication rate. When the devices own different communication rates, the optimal scheduling order is also obtained. Additionally, when the workload cannot be split arbitrarily, an approximation algorithm with ratio of at most 2 (1 + δ) is proposed. Finally, the theoretical analysis and simulation results verify that the proposed algorithm has high performance in terms of latency. Two testbed experiments are also conducted, which show that the proposed method outperforms the existing methods, reducing the latency by up to 29.2% in real-world applications. © 2023 IEEE.

关键词： Edge computing

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3D-GRES: Generalized 3D Referring Expression Segmentation 24

3D-GRES: Generalized 3D Referring Expression Segmentation

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32nd ACM international conference on Multimedia, MM 2024

作者： Wu, Changli Liu, Yihang Ji, Jiayi Ma, Yiwei Wang, Haowei Luo, Gen Ding, Henghui Sun, Xiaoshuai Ji, Rongrong Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University Xiamen China Youtu Lab Tencent Shanghai China Institute of Big Data Fudan University Shanghai China

ISBN: (纸本)9798400706868

3D Referring Expression Segmentation (3D-RES) is dedicated to segmenting a specific instance within a 3D space based on a natural language description. However, current approaches are limited to segmenting a single target, restricting the versatility of the task. To overcome this limitation, we introduce Generalized 3D Referring Expression Segmentation (3D-GRES), which extends the capability to segment any number of instances based on natural language instructions. In addressing this broader task, we propose the Multi-Query Decoupled Interaction Network (MDIN), designed to break down multi-object segmentation tasks into simpler, individual segmentations. MDIN comprises two fundamental components: Text-driven Sparse Queries (TSQ) and Multi-object Decoupling Optimization (MDO). TSQ generates sparse point cloud features distributed over key targets as the initialization for queries. Meanwhile, MDO is tasked with assigning each target in multi-object scenarios to different queries while maintaining their semantic consistency. To adapt to this new task, we build a new dataset, namely Multi3DRes. Our comprehensive evaluations on this dataset demonstrate substantial enhancements over existing models, thus charting a new path for intricate multi-object 3D scene comprehension. The benchmark and code are available at https://***/sosppxo/MDIN. © 2024 ACM.

关键词： Semantics

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Identifying and Architecting Microservices for Edge computing

Identifying and Architecting Microservices for Edge Computin...

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IEEE international conference on Software Architecture Workshops (ICSAW)

作者： Urjaswala Vora College of Information Sciences and Technology Pennsylvania State University State College Unites States

ISBN: (数字)9798331533366

ISBN: (纸本)9798331533373

Microservices architecture (MSA) paradigm extends Service Oriented Architecture (SOA) to focus on specific aspects such as design of small lightweight services as independent cohesive components, development and service management using agile and DevOps methodologies and service delivery based on distributed data management and decentralized service governance and more. MSA thus has become a widely used architectural style for designing modern applications due to advantages like granular scalability and maintainability, especially in today's world of ‘system of systems’. Edge computing facilitates segregation of computing responsibilities between edge devices and cloud infrastructure to process and analyze data acquired by edge devices. The number of IoT devices is increasing at such a high rate that the need for Edge AI is expected to reach the value of investment to USD 72.6 billion by 2030. The edge analytics bring correlated research challenges from the areas of cyber and physical security, data privacy, maintenance support, access, latency, reliability, power consumption and remoteness into the scope and require innovation at architecture level as does the improvement in all systems' quality related attributes. In this tutorial we discuss how microservices paradigm can be used effectively for edge computing-based systems resulting in a sustainable architecture with lower dependency on the data-center / cloud architecture.

关键词： Cloud computing Technological innovation Power demand Software architecture Scalability Microservice architectures Computer architecture Tutorials Quality of service Security

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