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Social-Aware Cross-Chain Authentication Strategy in Mobile Edge computing 9

Social-Aware Cross-Chain Authentication Strategy in Mobile E...

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IEEE 9th international conference on Information, Communication and Networks (ICICN)

作者： Zhao, Jinghan Yang, Hui Beijing Univ Posts & Telecommun State Key Lab Informat Photon & Opt Commun Beijing Peoples R China

ISBN: (纸本)9780738113456

With the rapid development of mobile edge computing (MEC), the amount of mobile devices and users is growing rapidly, and the distributed management architecture based on the blockchain technology is gradually used for the demand of trust and privacy protection in MEC. While most of the works focus on how to use blockchain to provide a secure and trusted environment in MEC, the problem of excessive authentication cost caused by repeated authentication has not been solved. this paper proposes a social-aware cross-chain authentication strategy in MEC. the concept of social network is introduced into MEC, based on data collected from the users, we can derive the social connection among users and select notaries from users with high credibility to cross the chain. Simulation results show that the proposed strategy can effectively reduce the system cost of distributed management architecture in MEC.

关键词： component blockchain cross chain social network Mobile Edge computing(MEC)

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Tora: A Trusted Blockchain Oracle Based on a Decentralized TEE Network 12

Tora: A Trusted Blockchain Oracle Based on a Decentralized T...

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12th IEEE international conference on Joint Cloud computing (IEEE JCC) / 9th IEEE international conference on Mobile Cloud computing, Services, and Engineering (IEEE MobileCloud)

作者： Chen, Lili Yuan, Rui Xia, Yubin Shanghai Jiao Tong Univ Inst Parallel & Distributed Syst Shanghai 200030 Peoples R China Trustmirror inc Shanghai Peoples R China

ISBN: (纸本)9781665434799

Smart Contracts cannot get external data directly due to the closure and determinacy of blockchain itself, limiting the extensibility of blockchain applications. Oracle is proposed to serve as a data feed to offer authenticated and deterministic external data to smart contracts. However, existing centralized oracles are efficient but vulnerable to targeted attacks and suffering from a single point of failure, while existing decentralized oracles are inefficient. the paper presents a trusted blockchain oracle based on a decentralized Trusted Execution Environment (TEE) network called Tora, which embraces both efficiency and availability. the key of Tora is a hybrid consensus mechanism with the confidential available group selection based on Proof-of-Availability (PoA). We have implemented a prototype of Tora on Ethereum with Intel Software Guard eXtensions (SGX) and evaluated it with a data-fetch use case on different measurements, including gas costs, off-chain execution time, group selection results and throughput. the results show that Tora provides considerable efficiency and scalability.

关键词： blockchain oracle TEE

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By-default Security Orchestration on distributed Edge/Cloud computing Framework

By-default Security Orchestration on distributed Edge/Cloud ...

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IEEE conference on Network Softwarization (NetSoft)

作者： José Manuel Bernabé Murcia José Francisco Pérez Zarca Alejandro Molina Zarca Antonio Skármeta Dept. of Information and Communications Engineering University of Murcia Murcia Spain

Next generation networks and the strength of the distributed computing paradigm (edge/cloud) are transforming how services are provisioned, mainly when solutions focus on collaboration and aggregation of resources provided by different entities or organisations, that becomes essential to satisfy the most demanding computation and storage service requirements. However, it also entails challenges such as infrastructure and technologies heterogeneity, which directly impacts infrastructure management and especially security, that usually tends to be relegated to a second place. this paper provides a by-default security orchestrator approach to mitigate the above mentioned challenges in distributed edge/cloud computing frameworks. We use an Intent-based/policy-based orchestration paradigm for dealing with heterogeneity, allowing users to request service deployments securely without requiring knowledge about the underlying distributed infrastructure. By-default security orchestration will decide how to provide the requested services, ensuring that they are compliant with the security requirements provided by the user and the ones gathered by the system, locally and from reliable external sources 1 . We provide design and use-cases based workflows for managing by-default security orchestration in proactive and reactive ways. In the future, it is expected to perform the implementation and validation of the proposed approach inside the scope of the FLUIDOS EU project. 1 https://***/known-exploited-vulnerabilities-catalog

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IHEP TIER-2 computing CENTER: STATUS and OPERATION 9

IHEP TIER-2 COMPUTING CENTER: STATUS and OPERATION

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9th international conference "distributed computing and Grid Technologies in Science and Education", GRID 2021

作者： Kotliar, Viktor Gusev, Victor Kukhtenkov, Vladimir Institute for High Energy Physics named by A.A. Logunov National Research Center "Kurchatov Institute" Nauki Square 1 Protvino Moscow region 142281 Russia

RU-Protvino-IHEP site is one of three biggest WLCG Tier-2 centers in Russia. the computing infrastructure serves for "big four" high energy physics experiments such as Atlas, Alice, CMS, LHCb and local experiments at IHEP such as OKA, BEC, radio biology stands and others. In this work the current status of the computing capacities, networking and engineering infrastructure will be shown as well as the contribution of the grid site to the collaboration experiments. Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 international (CC BY 4.0).

关键词： High energy physics

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

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

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international conference on Fog and Mobile Edge computing (FMEC)

作者： Ibe Van thillo Zeeshan Hameed Claus Pahl Department of Applied Engineering-Electronics-ICT University of Antwerp Antwerp Belgium Faculty of Engineering Free University of Bozen-Bolzano Bolzano Italy

ISBN: (数字)9798350366488

ISBN: (纸本)9798350366495

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： Cloud computing Privacy Multi-access edge computing Scalability Reinforcement learning Peer-to-peer computing Planning Internet of things Security Trust management

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Optimization of computing Power Network Routing Strategies based on Multi-Agent Soft Actor-Critic

Optimization of Computing Power Network Routing Strategies b...

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6th international conference on Intelligent computing and Signal Processing (ICSP)

作者： Zhongyue Chen Shicong Zhang Ying Tang Mengke Xu Xiaoqing Wu Minchao Ye Zhaojuan Zhang Yaping Qi Huijuan Lu Wanli Huo China Jiliang University Hangzhou Zhejiang China National (Hangzhou) Novel Internet Exchange Hangzhou Zhejiang China Division of Ionizing Radiation Metrology Hangzhou Zhejiang China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Despite rapid developments in cloud computing, big data, and artificial intelligence, the computing Power Network, as a new type of information infrastructure supporting the digital transformation and upgrading of various industries, faces significant challenges in efficiently scheduling, and managing computing and network resources. this paper introduces an optimization method for the computingRoute algorithm based on the Multi-Agent Soft Actor-Critic algorithm, operating within a Software-Defined networking (SDN) architecture to address the efficiency issues in data transmission within the computing power network. the method leverages collaboration among multiple intelligent agents and employs deep reinforcement learning to optimize routing paths. Experimental results indicate that the MASAC algorithm, compared to traditional Actor-Critic algorithms, shows a 43.63 % improvement in stable average reward values, demonstrating better learning efficiency and performance. Furthermore, the soft policy updates, entropy regularization, and the use of target networks in the MASAC algorithm enhance its stability, improving training efficiency and performance. In performance comparisons with other computing power network routing strategies, the proposed computingRoute solution minimizes computing power requirements while reducing latency by 39.06% compared to DRL-TE and 21.42% compared to SmartPath. However, computingRoute exhibits a slightly higher packet loss rate than SmartPath.

关键词： Training Power demand Processor scheduling Signal processing algorithms Packet loss Collaboration Signal processing Routing Entropy Software defined networking

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Handwritten Word Recognition of Various Languages: A Review

Handwritten Word Recognition of Various Languages: A Review

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international conference on Smart computing & Communications (ICSCC)

作者： V. Jayanthi S. thenmalar Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur TamilNadu India

Handwriting recognition (HWR) is the ability of a computer to interpret and understand handwritten text. HWR involves gathering, storing, and processing digital pen data. HWR is used for many tasks, including writing automation, digital document archiving and retrieval, text entry automation, and document data extraction. Handwriting recognition software is used to help automate these tasks or to make them easier for the user. HWR is also used to improve accessibility for people with disabilities who cannot generate characters traditionally accurately. Recognizing the handwritten word is a complicated process because of the nature of the characters, such as similar shapes and sizes, spaces between the characters, discontinued characters, overlapped characters, complex stroke patterns, and writing styles in various languages. A deep learning approach has been mainly used in handwritten recognition recently. Deep learning can be used to process both labeled and unlabeled data. the advantage of the deep learning approach is to perform feature extraction independently. the survey focuses on the issues and challenges previous research has encountered. the study lists the types of methodologies and datasets utilized in different languages are described.

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Learning at the Edge: Mobile Edge computing and Reinforcement Learning for Enhanced Web Application Performance

Learning at the Edge: Mobile Edge Computing and Reinforcemen...

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international conference on Web Research (ICWR)

作者： Komeil Moghaddasi Shakiba Rajabi Department of IT and Computer Engineering Urmia Branch Islamic Azad University Urmia Iran

Over the recent years, the adoption of Mobile Edge computing (MEC) has increased due to its ability to bring computing resources closer to end-users, which includes storage, computing, and networking at the network's edge. this approach results in faster and more efficient data processing, reduced latency, and better overall performance for mobile device applications. Our aim in this study is to evaluate the effectiveness of using reinforcement learning algorithms, namely Deep Q-Network (DQN) and Asynchronous Advantage Actor-Critic (A3C), in optimizing the performance of web applications in MEC environments, such as latency, CPU usage, and memory utilization. We conducted experiments using a sample dataset and compared the performance of models with and without MEC. the results demonstrate that the use of MEC substantially improves the performance of web applications. Both DQN and A3C algorithms exhibit promising results in improving the latency of web applications in MEC environments. However, the A3C algorithm outperforms the DQN algorithm in terms of CPU utilization and memory usage. Overall, our study highlights the potential of reinforcement learning algorithms in improving the performance of MEC-based web applications.

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Security Constraints for Placement of Latency Sensitive 5G MEC Applications 9

Security Constraints for Placement of Latency Sensitive 5G M...

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9th international conference on Future Internet of things and Cloud, FiCloud 2022

作者： Artych, Rafal Bocianiak, Krzysztof Carlinet, Yannick Niewolski, Wojciech Perrot, Nancy Podlasek, Aleksandra Wary, Jean-Philippe Orange Innovation Poland Orange Polska S.A. Warsaw Poland Orange Innovation Orange S.A. Paris France

ISBN: (数字)9781665493505

ISBN: (纸本)9781665493505

Multi-Access Edge computing (MEC) is one of the key enablers in 5G, offering to external parties computing capabilities very close to the end users. To attain this objective, the 5G operator needs to provide distributed computing infrastructure tightly integrated with its network. In this paper, we propose a model for MEC infrastructure and MEC applications together with the definition of the problem of optimal application placement taking into account various constraints including security imposed by technical and business conditions. Data models for virtualized MEC infrastructure based on virtual machines and MEC standardization are proposed. Furthermore, the implementation of the proposed data models for MEC applications orchestration on the OpenStack platform is presented. © 2022 IEEE.

关键词： Edge computing

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Scheduling Linear Workflows with Multicriteria based Partial Computations in a Cloud–Fog–Mist Environment

Scheduling Linear Workflows with Multicriteria based Partial...

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international conference on Fog and Mobile Edge computing (FMEC)

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

ISBN: (数字)9798350366488

ISBN: (纸本)9798350366495

In distributed computing architectures, workloads often comprise jobs with varying levels of security requirements. In such environments, it is crucial to implement security-aware scheduling schemes to ensure the appropriate execution of applications. this research focuses on security-aware scheduling techniques for linear workflow (LW) applications within a cloud-fog-mist computing platform. Mist resources are allocated to process LW jobs with the highest security requirements, classified as mist jobs. LW jobs identified as fog jobs possess intermediate security levels and can execute on either fog or mist resources. LW jobs without security requirements can run on cloud or fog resources; however, when executed on fog resources, they may undergo partial computations based on multiple criteria to prioritize fog jobs and ensure timeliness. Extensive simulation experiments were conducted to evaluate the impact of partial computations on performance. the results provide valuable insights into how dynamic adjustments of partial computations during runtime affect system performance across different scenarios.

关键词： Runtime Multi-access edge computing Processor scheduling System performance Computer architecture Security distributed computing

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