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An User-Driven Active Way to Push ACL in Software-Defined networking 22nd

An User-Driven Active Way to Push ACL in Software-Defined Ne...

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

作者： Yu, Haisheng Liu, Dong Wang, Wenyong Li, Keqiu Zou, Sai Liu, Zhaobin Liu, Yan Macau Univ Sci & Technol Taipa Macao Peoples R China Univ Elect Sci & Technol China Chengdu Peoples R China BII Grp Beijing Peoples R China Tianjin Univ Tianjin Peoples R China Guizhou Univ Guiyang Peoples R China Dalian Maritime Univ Dalian Peoples R China

ISBN: (纸本)9783030967727;9783030967710

Compared with the traditional network, Software-Defined networking (SDN) provides a more convenient network paradigm to build Access Control List (ACL) application. There has been a few studies focusing on ACL application in SDN up to now, but most of the existing work adopts a reactive way to enforce ACL, resulting in new ACL update can not take effect immediately. In this paper, we propose CLACK, an approach for user-driven centralized ACL in SDN. We implement CLACK on both Floodlight and ONOS controller. The experimental results show that CLACK has a better performance than the existing Floodlight firewall application.

关键词： Access Control List (ACL) Software-Defined networking (SDN) Security Floodlight ONOS

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Blockchain-Based distributed Caching with replication for Efficient Service Provision in Edge-cloud Environments 23

Blockchain-Based Distributed Caching with replication for Ef...

引用

6th international conference on networking, Intelligent Systems and Security, NISS 2023

作者： Chanyour, Tarik Kaddari, Abdelhak Lis Lab Science Faculty of Ain-Chock Hassan Ii University Maarif Casablanca Morocco Lmsc Lab Ensa Marrakech Cadi Ayyad University Gueliz Marrakech Morocco

ISBN: (纸本)9798400700194

5G networks promote integrating Multi-access Edge computing (MEC) capabilities in Dense Small Cell (DSC) networks in order to address the strict latency requirement of Smart Mobile Devices (SMDs) services. This article investigates the contribution of a split-cache method integrated within a secure blockchain based MEC system and present a novel method to enhance service provision by distributing the containers' base image chunks among multiple Edge-Cloud Nodes (ECNs). The objective of this study is to minimize the service starting/restarting time by collecting, verifying and compiling the best chunks candidates while resources allocation is considered at each request slot. The formulated problem is a mixed-integer nonlinear program, subject to network bandwidth capacity, base image chunks availability, and services starting deadlines constraint. Finally, the numerical results of the proposed two solutions demonstrate its benefits regarding service provision operations while taking bandwidth,timing and resources into consideration. © 2023 ACM.

关键词： Containers

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Towards distributed Quantum Error Correction for distributed Quantum computing

Towards Distributed Quantum Error Correction for Distributed...

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Quantum Communications, networking, and computing (QCNC), international conference on

作者： Shahram Babaie Chunming Qiao Department of Computer Science and Engineering University at Buffalo Buffalo USA

ISBN: (数字)9798331531591

ISBN: (纸本)9798331531607

Quantum computing as a promising technology can utilize stochastic solutions instead of deterministic approaches for complicated scenarios for which classical computing is inefficient, provided that both the concerns of the error-prone nature of qubits and the limitation of the number of qubits are addressed carefully. In order to address both concerns, a new qubit-based distributed Quantum Error Correction (DQEC) architecture is proposed in which three physical qubits residing on three Quantum Processing Units (QPU) are used to form a logical qubit. This paper illustrates how three QPUs collaboratively generate a joint quantum state in which single bit-flip and phase-flip errors can be properly resolved. By reducing the number of qubits required to form a logical qubit in the proposed architecture, each QPU with its limited number of physical qubits can accommodate more logical qubits than when it has to devote its three physical qubits for each logical qubit. The functional correctness of the proposed architecture is evaluated through the Qiskit tool and stabilizer generators. Moreover, the fidelity of input and output quantum states, the complexity of the proposed designs, and the dependency between error probability and correctness of the proposed architecture are analyzed to prove its effectiveness.

关键词： Error probability Qubit Quantum channels Computer architecture Quantum state Generators Error correction Error correction codes Complexity theory Quantum communication

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Effective Strategies for Resource Allocation and Scheduling in Cloud computing 1

引用

6th international conference on Innovative computing and Communication, ICICC 2023

作者： Jananee, M. Suresh, A. Department of Networking and Communications School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu SRM Nagar Kattankulathur Chennai603203 India

ISBN: (数字)9789819933150

ISBN: (纸本)9789819933143

Cloud computing, the newest paradigm in distributed systems, and opens up vast possibilities for efficiently meeting demands without investing in costly infrastructure. In particular, IaaS clouds offer an accessible, flexible, and scalable infrastructure for the deployment of these scientific applications by giving users access to a virtually endless pool of resources that can be obtained, configured, and used on demand and charged on a pay-as-you-go basis. The main issue with cloud computing is the lack of resources. For cloud providers, managing resources is a challenging issue. To help they manage their resources efficiently and affordably, researchers offer their insightful recommendations. This paper proposes a number of methods for cutting down on scheduling-related expenses and lag time, as well as for making the most of available resources, meeting strict deadlines, and minimizing energy consumption—all without breaching service-level agreements. Comparisons of proposed and established methods have been found to yield positive outcomes in experiments. The utilization rate has been identified in existing system is 88, but the proposed system rate is 88.82. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Energy utilization

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Welcome Message from ICDCN 2024 conference Chairs

ACM International Conference Proceeding Series

引用

ACM international conference Proceeding Series 2024年 III-IV页

作者： Bellavista, Paolo King, Valerie Augustine, John University of Bologna Italy University of Victoria Canada Iit Madras India

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Scalable Federated Unlearning via Isolated and Coded Sharding 33

Scalable Federated Unlearning via Isolated and Coded Shardin...

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33rd international Joint conference on Artificial Intelligence (IJCAI)

作者： Lin, Yijing Gao, Zhipeng Duo, Hongyang Niyato, Dusit Gui, Gui Cui, Shuguang Ren, Jinke Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China Chinese Univ Hong Kong Shenzhen Future Network Intelligence Inst Shenzhen Guangdong Peoples R China Chinese Univ Hong Kong Shenzhen Sch Sci & Engn Shenzhen Guangdong Peoples R China Nanyang Technol Univ Coll Comp & Data Sci Singapore Singapore Cent South Univ Sch Automat Changsha Hunan Peoples R China

ISBN: (纸本)9781956792041

Federated unlearning has emerged as a promising paradigm to erase the client-level data effect without affecting the performance of collaborative learning models. However, the federated unlearning process often introduces extensive storage overhead and consumes substantial computational resources, thus hindering its implementation in practice. To address this issue, this paper proposes a scalable federated unlearning framework based on isolated sharding and coded computing. We first divide distributed clients into multiple isolated shards across stages to reduce the number of clients being affected. Then, to reduce the storage overhead of the central server, we develop a coded computing mechanism by compressing the model parameters across different shards. In addition, we provide the theoretical analysis of time efficiency and storage effectiveness for the isolated and coded sharding. Finally, extensive experiments on two typical learning tasks, i.e., classification and generation, demonstrate that our proposed framework can achieve better performance than three state-of-the-art frameworks in terms of accuracy, retraining time, storage overhead, and F1 scores for resisting membership inference attacks.

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Applying a Task-Based Approach to distributed Machine Learning Workflows

Applying a Task-Based Approach to Distributed Machine Learni...

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High Performance computing, networking, Storage and Analysis, SC-W: Workshops of the international conference for

作者： Fernando Vázquez-Novoa Daniele Lezzi Francesc Lordan Fatemeh Baghdadi Davide Cirillo Department of Computer Sciences Barcelona Supercomputing Center Barcelona Spain Department of Life Sciences Barcelona Supercomputing Center Barcelona Spain

ISBN: (数字)9798350355543

ISBN: (纸本)9798350355550

The growing demands across various scientific fields have led to a significant shift in applications that consume data at the edge of the computing continuum. These applications require unified programming models for the composition of components and coordinating the execution of computational workloads, including training machine learning (ML) models on distributed resources. Personalized healthcare often leverages data generated from wearable devices used to train ML models, can be benefited from distributed computing approaches. Specifically, stroke care can be greatly benefited from distributed ML with modifiable risk factors that can be monitored using wearable devices. In this work, we present an implementation that leverages distributed techniques for large-scale ML workflows using electrocardiogram (ECG) recordings for atrial fibrillation (AF) classification. The application was evaluated using the PhysioNet database, showcasing the potential of distributed, ML in stroke care, opening the way for future creation of more advanced models embedded in edge devices.

关键词： Training Computational modeling Scalability distributed databases Medical services Electrocardiography Data models Recording Wearable devices Classification tree analysis

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Machine Learning Based Feature Selection for DDoS Detection in Named Data networking 4

Machine Learning Based Feature Selection for DDoS Detection ...

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4th international conference on Advances in computing, Communication Control and networking, ICAC3N 2022

作者： Subasri, I. Emil Selvan, G.S.R. Ramkumar, M.P. Thiagarajar College of Engineering Department of Computer Science and Engineering Madurai India

ISBN: (纸本)9781665474368

With the growing recognition that current Internet protocols have significant security flaws;several ongoing research projects are attempting to design potential next-generation Internet architectures to eliminate flaws made in the past. These projects are attempting to address privacy and security as their essential parameters. NDN (Named Data networking) is a new networking paradigm that is being investigated as a potential alternative for the present host-centric IP-based Internet architecture. It concentrates on content delivery, which is probably underserved by IP, and it prioritizes security and privacy. NDN must be resistant to present and upcoming threats in order to become a feasible Internet framework. DDoS (distributed Denial of Service) attacks are serious attacks that have the potential to interrupt servers, systems, or application layers. Due to the probability of this attack, the network security environment is made susceptible. The resilience of any new architecture against the DDoS attacks which afflict today's Internet is a critical concern that demands comprehensive consideration. As a result, research on feature selection approaches was conducted in order to use machine learning techniques to identify DDoS attacks in NDN. In this research, features were chosen using the Information Gain and Data Reduction approach with the aid of the WEKA machine learning tool to identify DDoS attacks. The dataset was tested using K-Nearest Neighbor (KNN), Decision Table, and Artificial Neural Network (ANN) algorithms to categorize the selected features. Experimental results shows that Decision Table classifier outperforms well when compared to other classification algorithms with the with the accuracy of 85.42% and obtained highest precision and recall score with 0.876 and 0.854 respectively when compared to the other classification techniques. © 2022 IEEE.

关键词： Data reduction

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DFaaS: Decentralized Function-as-a-Service for Federated Edge computing 10

DFaaS: Decentralized Function-as-a-Service for Federated Edg...

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10th IEEE international conference on Cloud networking (IEEE CloudNet)

作者： Ciavotta, Michele Motterlini, Davide Savi, Marco Tundo, Alessandro Univ Milano Bicocca Dept Informat Syst & Commun Milan Italy

ISBN: (纸本)9781665435383

Edge computing pushes cloud capabilities to the edge of the network, closer to the users, to address stringent Quality-of-Service requirements and ensure more efficient bandwidth usage. Function-as-a-Service appears to be the most natural service model solution to enhance Edge computing applications' deployment and responsiveness. Unfortunately, the conventional FaaS model does not fit well in distributed and heterogeneous edge environments, where traffic demands arrive to (and are served by) edge nodes that may get overloaded under certain traffic conditions or where the access points of the network might frequently change, as for mobile applications. This short paper tries to fill this gap by proposing DFaaS, a novel decentralized FaaS-based architecture designed to autonomously balance the traffic load across edge nodes belonging to federated Edge computing ecosystems. DFaaS implementation relies on an overlay peer-to-peer network and a distributed control plane that takes decisions on load redistribution. Although preliminary, results confirm the feasibility of the approach, showing that the system can transparently redistribute the load across edge nodes when they become overloaded.

关键词： Function-as-a-Service Edge computing Edge Federation Load Balancing Peer-to-Peer networking

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Edge Cloud Selection Strategy for Micro-service Chain Migration in Mobile Edge computing

Edge Cloud Selection Strategy for Micro-service Chain Migra...

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international conference on Big Data Intelligence and computing, DataCom 2022

作者： Xu, Lanqing Wang, Hongman Huang, Jie Wang, Hongyan State Key Laboratory of Networking and Switching Technology School of Computer Science Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9789819922321

Micro-service, splitting and combining services in a finer granularity, is an emerging service architecture. With the rapid development of 5G and 6G mobile communication network, the migration of micro-services in edge computing has gradually become a hot topic. However, the range of edge cloud is limited, and user movement will increase the service delay. We consider the characteristics of service interdependence and serial parallel relationship in the micro-service chain and put forward an edge cloud selection strategy for micro-service chain migration based on Gibbs Monte Carlo sampling, in order to minimize the total micro-service chain migration delay and the distributed computing resources, and to achieve seamless and realtime response to mobile users’ service request. Experimental results show that, compared with other algorithms, the proposed algorithm can guarantee better global performance and reduce the total delay of service migration effectively. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mobile edge computing

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