arXiv - CS - Networking and Internet Architecture最新文献_第5页

Adaptive Multi-Layer Deployment for A Digital Twin Empowered Satellite-Terrestrial Integrated Network 自适应多层部署，打造数字孪生星地一体化网络

arXiv - CS - Networking and Internet Architecture Pub Date : 2024-09-09 DOI: arxiv-2409.05480

Yihong Tao, Bo Lei, Haoyang Shi, Jingkai Chen, Xing Zhang

{"title":"Adaptive Multi-Layer Deployment for A Digital Twin Empowered Satellite-Terrestrial Integrated Network","authors":"Yihong Tao, Bo Lei, Haoyang Shi, Jingkai Chen, Xing Zhang","doi":"arxiv-2409.05480","DOIUrl":"https://doi.org/arxiv-2409.05480","url":null,"abstract":"With the development of satellite communication technology,\u0000satellite-terrestrial integrated networks (STIN), which integrate satellite\u0000networks and ground networks, can realize seamless global coverage of\u0000communication services. Confronting the intricacies of network dynamics, the\u0000diversity of resource heterogeneity, and the unpredictability of user mobility,\u0000dynamic resource allocation within networks faces formidable challenges.\u0000Digital twin (DT), as a new technique, can reflect a physical network to a\u0000virtual network to monitor, analyze, and optimize the physical network.\u0000Nevertheless, in the process of constructing the DT model, the deployment\u0000location and resource allocation of DTs may adversely affect its performance.\u0000Therefore, we propose a STIN model, which alleviates the problem of\u0000insufficient single-layer deployment flexibility of the traditional edge\u0000network by deploying DTs in multi-layer nodes in a STIN. To address the\u0000challenge of deploying DTs in the network, we propose multi-layer DT deployment\u0000in a STIN to reduce system delay. Then we adopt a multi-agent reinforcement\u0000learning (MARL) scheme to explore the optimal strategy of the DT multi-layer\u0000deployment problem. The implemented scheme demonstrates a notable reduction in\u0000system delay, as evidenced by simulation outcomes.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards Practical Overlay Networks for Decentralized Federated Learning 面向分散式联合学习的实用重叠网络

arXiv - CS - Networking and Internet Architecture Pub Date : 2024-09-09 DOI: arxiv-2409.05331

Yifan Hua, Jinlong Pang, Xiaoxue Zhang, Yi Liu, Xiaofeng Shi, Bao Wang, Yang Liu, Chen Qian

{"title":"Towards Practical Overlay Networks for Decentralized Federated Learning","authors":"Yifan Hua, Jinlong Pang, Xiaoxue Zhang, Yi Liu, Xiaofeng Shi, Bao Wang, Yang Liu, Chen Qian","doi":"arxiv-2409.05331","DOIUrl":"https://doi.org/arxiv-2409.05331","url":null,"abstract":"Decentralized federated learning (DFL) uses peer-to-peer communication to\u0000avoid the single point of failure problem in federated learning and has been\u0000considered an attractive solution for machine learning tasks on distributed\u0000devices. We provide the first solution to a fundamental network problem of DFL:\u0000what overlay network should DFL use to achieve fast training of highly accurate\u0000models, low communication, and decentralized construction and maintenance?\u0000Overlay topologies of DFL have been investigated, but no existing DFL topology\u0000includes decentralized protocols for network construction and topology\u0000maintenance. Without these protocols, DFL cannot run in practice. This work\u0000presents an overlay network, called FedLay, which provides fast training and\u0000low communication cost for practical DFL. FedLay is the first solution for\u0000constructing near-random regular topologies in a decentralized manner and\u0000maintaining the topologies under node joins and failures. Experiments based on\u0000prototype implementation and simulations show that FedLay achieves the fastest\u0000model convergence and highest accuracy on real datasets compared to existing\u0000DFL solutions while incurring small communication costs and being resilient to\u0000node joins and failures.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Positioning of a Next Generation Mobile Cell to Maximise Aggregate Network Capacity 定位下一代移动蜂窝，最大限度地提高网络总容量

arXiv - CS - Networking and Internet Architecture Pub Date : 2024-09-09 DOI: arxiv-2409.06098

Paulo Furtado Correia, Andre Coelho, Manuel Ricardo

引用次数: 0

Coordinated Sampling in SDNs with Dynamic Flow Rates 具有动态流速的 SDN 中的协调采样

arXiv - CS - Networking and Internet Architecture Pub Date : 2024-09-09 DOI: arxiv-2409.05966

Soroosh Esmaeilian, Mahdi Dolati, Sogand Sadrhaghighi, Majid Ghaderi

{"title":"Coordinated Sampling in SDNs with Dynamic Flow Rates","authors":"Soroosh Esmaeilian, Mahdi Dolati, Sogand Sadrhaghighi, Majid Ghaderi","doi":"arxiv-2409.05966","DOIUrl":"https://doi.org/arxiv-2409.05966","url":null,"abstract":"Traffic sampling has become an indispensable tool in network management.\u0000While there exists a plethora of sampling systems, they generally assume flow\u0000rates are stable and predictable over a sampling period. Consequently, when\u0000deployed in networks with dynamic flow rates, some flows may be missed or\u0000under-sampled, while others are over-sampled. This paper presents the design\u0000and evaluation of dSamp, a network-wide sampling system capable of handling\u0000dynamic flow rates in Software-Defined Networks (SDNs). The key idea in dSamp\u0000is to consider flow rate fluctuations when deciding on which network switches\u0000and at what rate to sample each flow. To this end, we develop a general model\u0000for sampling allocation with dynamic flow rates, and then design an efficient\u0000approximate integer linear program called APX that can be used to compute\u0000sampling allocations even in large-scale networks. To show the efficacy of\u0000dSamp for network monitoring, we have implemented APX and several existing\u0000solutions in ns-3 and conducted extensive experiments using model-driven as\u0000well as trace-driven simulations. Our results indicate that, by considering\u0000dynamic flow rates, APX outperforms the existing solutions by up to 10% in\u0000sampling more flows at a given sampling rate.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How We Lost The Internet 我们是如何失去互联网的

arXiv - CS - Networking and Internet Architecture Pub Date : 2024-09-09 DOI: arxiv-2409.05264

Micah Beck, Terry Moore

{"title":"How We Lost The Internet","authors":"Micah Beck, Terry Moore","doi":"arxiv-2409.05264","DOIUrl":"https://doi.org/arxiv-2409.05264","url":null,"abstract":"In this paper we reexamine an assumption that underpinned the development of\u0000the Internet architecture, namely that a stateless and loosely synchronous\u0000point-to-point datagram delivery service would be sufficient to meet the needs\u0000of all network applications, including those which deliver content and services\u0000to a mass audience at global scale. Such applications are inherently\u0000asynchronous and point-to-multipoint in nature. We explain how the inability of\u0000distributed systems based on this stateless datagram service to provide\u0000adequate and affordable support for them within the public (I.e., universally\u0000shared and available) network led to the development of private overlay\u0000infrastructures, specifically Content Delivery Networks and distributed Cloud\u0000data centers. We argue that the burdens imposed by reliance on these private\u0000overlays may have been an obstacle to achieving the Open Data Networking goals\u0000of early Internet advocates. The contradiction between those initial goals and\u0000the exploitative commercial imperatives of hypergiant overlay operators is\u0000offered as a possibly important reason for the negative impact of their most\u0000profitable applications (e.g., social media) and monetization strategies (e.g.,\u0000targeted advertisement). We propose that one important step in resolving this\u0000contradiction may be to reconsider the adequacy Internet's stateless datagram\u0000service model.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing Vehicular Users Association in Urban Mobile Networks 优化城市移动网络中的车载用户关联

arXiv - CS - Networking and Internet Architecture Pub Date : 2024-09-09 DOI: arxiv-2409.05845

Geymerson S. Ramos, Razvan Stanica, Rian G. S. Pinheiro, Andre L. L. Aquino

引用次数: 0

NetDPSyn: Synthesizing Network Traces under Differential Privacy NetDPSyn：差异隐私下的网络痕迹合成

arXiv - CS - Networking and Internet Architecture Pub Date : 2024-09-08 DOI: arxiv-2409.05249

Danyu Sun, Joann Qiongna Chen, Chen Gong, Tianhao Wang, Zhou Li

引用次数: 0

Towards an AI/ML-driven SMO Framework in O-RAN: Scenarios, Solutions, and Challenges 在 O-RAN 中建立人工智能/ML 驱动的 SMO 框架：场景、解决方案和挑战

arXiv - CS - Networking and Internet Architecture Pub Date : 2024-09-08 DOI: arxiv-2409.05092

Mohammad Asif Habibi, Bin Han, Merve Saimler, Ignacio Labrador Pavon, Hans D. Schotten

{"title":"Towards an AI/ML-driven SMO Framework in O-RAN: Scenarios, Solutions, and Challenges","authors":"Mohammad Asif Habibi, Bin Han, Merve Saimler, Ignacio Labrador Pavon, Hans D. Schotten","doi":"arxiv-2409.05092","DOIUrl":"https://doi.org/arxiv-2409.05092","url":null,"abstract":"The emergence of the open radio access network (O-RAN) architecture offers a\u0000paradigm shift in cellular network management and service orchestration,\u0000leveraging data-driven, intent-based, autonomous, and intelligent solutions.\u0000Within O-RAN, the service management and orchestration (SMO) framework plays a\u0000pivotal role in managing network functions (NFs), resource allocation, service\u0000provisioning, and others. However, the increasing complexity and scale of\u0000O-RANs demand autonomous and intelligent models for optimizing SMO operations.\u0000To achieve this goal, it is essential to integrate intelligence and automation\u0000into the operations of SMO. In this manuscript, we propose three scenarios for\u0000integrating machine learning (ML) algorithms into SMO. We then focus on\u0000exploring one of the scenarios in which the non-real-time RAN intelligence\u0000controller (Non-RT RIC) plays a major role in data collection, as well as model\u0000training, deployment, and refinement, by proposing a centralized ML\u0000architecture. Finally, we identify potential challenges associated with\u0000implementing a centralized ML solution within SMO.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PANTS: Practical Adversarial Network Traffic Samples against ML-powered Networking Classifiers PANTS：针对 ML 驱动的网络分类器的实用对抗性网络流量样本

arXiv - CS - Networking and Internet Architecture Pub Date : 2024-09-07 DOI: arxiv-2409.04691

Minhao Jin, Maria Apostolaki

{"title":"PANTS: Practical Adversarial Network Traffic Samples against ML-powered Networking Classifiers","authors":"Minhao Jin, Maria Apostolaki","doi":"arxiv-2409.04691","DOIUrl":"https://doi.org/arxiv-2409.04691","url":null,"abstract":"Multiple network management tasks, from resource allocation to intrusion\u0000detection, rely on some form of ML-based network-traffic classification (MNC).\u0000Despite their potential, MNCs are vulnerable to adversarial inputs, which can\u0000lead to outages, poor decision-making, and security violations, among other\u0000issues. The goal of this paper is to help network operators assess and enhance the\u0000robustness of their MNC against adversarial inputs. The most critical step for\u0000this is generating inputs that can fool the MNC while being realizable under\u0000various threat models. Compared to other ML models, finding adversarial inputs\u0000against MNCs is more challenging due to the existence of non-differentiable\u0000components e.g., traffic engineering and the need to constrain inputs to\u0000preserve semantics and ensure reliability. These factors prevent the direct use\u0000of well-established gradient-based methods developed in adversarial ML (AML). To address these challenges, we introduce PANTS, a practical white-box\u0000framework that uniquely integrates AML techniques with Satisfiability Modulo\u0000Theories (SMT) solvers to generate adversarial inputs for MNCs. We also embed\u0000PANTS into an iterative adversarial training process that enhances the\u0000robustness of MNCs against adversarial inputs. PANTS is 70% and 2x more likely\u0000in median to find adversarial inputs against target MNCs compared to two\u0000state-of-the-art baselines, namely Amoeba and BAP. Integrating PANTS into the\u0000adversarial training process enhances the robustness of the target MNCs by\u000052.7% without sacrificing their accuracy. Critically, these PANTS-robustified\u0000MNCs are more robust than their vanilla counterparts against distinct\u0000attack-generation methodologies.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reinforcement Learning-Based Adaptive Load Balancing for Dynamic Cloud Environments 基于强化学习的动态云环境自适应负载平衡

arXiv - CS - Networking and Internet Architecture Pub Date : 2024-09-07 DOI: arxiv-2409.04896

Kavish Chawla

{"title":"Reinforcement Learning-Based Adaptive Load Balancing for Dynamic Cloud Environments","authors":"Kavish Chawla","doi":"arxiv-2409.04896","DOIUrl":"https://doi.org/arxiv-2409.04896","url":null,"abstract":"Efficient load balancing is crucial in cloud computing environments to ensure\u0000optimal resource utilization, minimize response times, and prevent server\u0000overload. Traditional load balancing algorithms, such as round-robin or least\u0000connections, are often static and unable to adapt to the dynamic and\u0000fluctuating nature of cloud workloads. In this paper, we propose a novel\u0000adaptive load balancing framework using Reinforcement Learning (RL) to address\u0000these challenges. The RL-based approach continuously learns and improves the\u0000distribution of tasks by observing real-time system performance and making\u0000decisions based on traffic patterns and resource availability. Our framework is\u0000designed to dynamically reallocate tasks to minimize latency and ensure\u0000balanced resource usage across servers. Experimental results show that the\u0000proposed RL-based load balancer outperforms traditional algorithms in terms of\u0000response time, resource utilization, and adaptability to changing workloads.\u0000These findings highlight the potential of AI-driven solutions for enhancing the\u0000efficiency and scalability of cloud infrastructures.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142183696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0