2022 IEEE Future Networks World Forum (FNWF)最新文献_第9页

Cloud Native Applications Profiling using a Graph Neural Networks Approach 使用图神经网络方法分析云原生应用程序

2022 IEEE Future Networks World Forum (FNWF) Pub Date : 2022-10-01 DOI: 10.1109/FNWF55208.2022.00046

Amine Boukhtouta, Taous Madi, M. Pourzandi, H. Alameddine

{"title":"Cloud Native Applications Profiling using a Graph Neural Networks Approach","authors":"Amine Boukhtouta, Taous Madi, M. Pourzandi, H. Alameddine","doi":"10.1109/FNWF55208.2022.00046","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00046","url":null,"abstract":"The convergence of Telecommunication and industry operational networks towards cloud native applications has enabled the idea to integrate protection layers to harden security posture and management of cloud native based deployments. In this paper, we propose a data-driven approach to support detection of anomalies in cloud native application based on a graph neural network. The essence of the profiling relies on capturing interactions between different perspectives in cloud native applications through a network dependency graph and transforming it to a computational graph neural network. The latter is used to profile different deployed assets like micro-service types, workloads' namespaces, worker machines, management and orchestration machines as well as clusters. As a first phase of the profiling, we consider a fine-grained profiling on microservice types with an emphasis on network traffic indicators. These indicators are collected on distributed Kubernetes (K8S) deployment premises. Experimental results shows good trade-off in terms of accuracy and recall with respect to micro-service types profiling (around 96%). In addition, we used predictions entropy scores to infer anomalies in testing data. These scores allow to segregate between benign and anomalous graphs, where we identified 19 out of 23 anomalies. Moreover, by using entropy scores, we can conduct a root cause analysis to infer problematic micro-services.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"418 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123447137","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: 1

An Experimental 5G Testbed for Secure Network Slicing Evaluation 5G安全网络切片评估实验平台

2022 IEEE Future Networks World Forum (FNWF) Pub Date : 2022-10-01 DOI: 10.1109/FNWF55208.2022.00032

H. Kholidy, A. Karam, Jeffrey H. Reed, Yusuf Elazzazi

引用次数: 4

5GLoR: 5G LAN Orchestration for enterprise IoT applications 5GLoR:面向企业物联网应用的5G局域网编排

2022 IEEE Future Networks World Forum (FNWF) Pub Date : 2022-10-01 DOI: 10.1109/FNWF55208.2022.00014

Sandesh Dhawaskar Sathyanarayana, Murugan Sankaradas, S. Chakradhar

{"title":"5GLoR: 5G LAN Orchestration for enterprise IoT applications","authors":"Sandesh Dhawaskar Sathyanarayana, Murugan Sankaradas, S. Chakradhar","doi":"10.1109/FNWF55208.2022.00014","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00014","url":null,"abstract":"5G-LAN is an enterprise local area network (LAN) that leverages 5G technology for wireless connectivity instead of WiFi. 5G technology is unique: it uses network slicing to distinguish customers in the same traffic class using new QoS technologies in the RF domain. This unique ability is not supported by most enterprise LANs, which rely primarily on DiffServ-like technologies that distinguish among traffic classes rather than customers. We first show that this mismatch in QoS between the 5G network and the LAN affects the accuracy of insights from the LAN-resident analytics applications. We systematically analyze the root causes of the QoS mismatch and propose a first-of-a-kind 5G-LAN orchestrator (5GLoR). 5GLoR is a middleware that applications can use to preserve the QoS of their 5G data streams through the enterprise LAN. In most cases, the loss of QoS is not due to the oversubscription of LAN switches but primarily due to the inefficient assignment of 5G data to queues at ingress and egress ports. 5GLoR periodically analyzes the status of these queues, provides suitable DSCP identifiers to the application, and installs relevant switch re-write rules (to change DSCP identifiers between switches) to continuously preserve the QoS of the 5G data through the LAN. 5GLoR improves the RTP frame level delay and inter-frame delay by 212% and 122%, respectively, for the WebRTC application. Additionally, with 5GLoR, the accuracy of two example applications (face detection and recognition) improved by 33%, while the latency was reduced by about 25%. Our experiments show that the performance (accuracy and latency) of applications on a 5G-LAN performs well with the proposed 5GLoR compared to the same applications on MEC. This is significant because 5G-LAN offers an order of magnitude more computing, networking, and storage resources to the applications than the resource-constrained MEC, and mature enterprise technologies can be used to deploy, manage, and update IoT applications.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117264162","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: 2

A Score Function Heuristic for Crosstalk- and Fragmentation-Aware Dynamic Routing, Modulation, Core, and Spectrum Allocation in SDM-EONs sdm - eon中串扰和片段感知动态路由、调制、核心和频谱分配的分数函数启发式算法

2022 IEEE Future Networks World Forum (FNWF) Pub Date : 2022-10-01 DOI: 10.1109/FNWF55208.2022.00023

Jaya Lakshmi Ravipudi, M. Brandt-Pearce

引用次数: 1

Towards 3D Flexible 6G Networks: Status, Challenges and Technical Enablers 迈向3D灵活6G网络:现状、挑战和技术推动因素

2022 IEEE Future Networks World Forum (FNWF) Pub Date : 2022-10-01 DOI: 10.1109/FNWF55208.2022.00122

Sokratis Barmpounakis, A. Georgakopoulos, P. Vlacheas, P. Demestichas

引用次数: 0

Network Traffic as a Federated Testbed Service 作为联邦测试平台服务的网络流量

2022 IEEE Future Networks World Forum (FNWF) Pub Date : 2022-10-01 DOI: 10.1109/FNWF55208.2022.00086

Jack Brassil

{"title":"Network Traffic as a Federated Testbed Service","authors":"Jack Brassil","doi":"10.1109/FNWF55208.2022.00086","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00086","url":null,"abstract":"We describe a prototype of Science Traffic as a Service (STAAS), a decentralized, cooperative system to collect, filter and distribute a diverse collection of real and synthetic data traffic to the global experimental research testbed user community. Available on-demand to networking experimenters through a web dashboard, the tool promises to elevate traffic selection and distribution to a first class experimental instrumentation resource. We believe the alternatives to providing this service on large-scale federated testbeds are increasingly unworkable for experimenters. As backbone networks increasingly deploy 100–1000 Gbps communications links we are moving beyond the point where experimenters can reasonably be asked to independently, safely, and efficiently create test traffic that provides the realism that their investigations will demand. We seek to deploy our prototype at campuses and testbeds attached to the emerging FABRIC mid-scale networking research infrastructure. We describe prototype design, operation and implementation, and how it is integrated with existing campus networking infrastructure. We explain how remote experimenters will request and acquire network traffic to study. We detail our process for forwarding campus traffic onto the experimental testbed, while striving to preserve both the timing integrity of the flows and the data privacy of their payloads.†","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121349658","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

Performance Validation Strategies for 5G-enhanced Transport & Logistics: The 5G-Blueprint Approach 5g增强运输和物流的性能验证策略:5g蓝图方法

2022 IEEE Future Networks World Forum (FNWF) Pub Date : 2022-10-01 DOI: 10.1109/FNWF55208.2022.00100

Nina Slamnik-Kriještorac, W. Vandenberghe, Rakshith Kusumakar, Karel Kural, M. Klepper, G. Kakes, L. Velde, J. Márquez-Barja

{"title":"Performance Validation Strategies for 5G-enhanced Transport & Logistics: The 5G-Blueprint Approach","authors":"Nina Slamnik-Kriještorac, W. Vandenberghe, Rakshith Kusumakar, Karel Kural, M. Klepper, G. Kakes, L. Velde, J. Márquez-Barja","doi":"10.1109/FNWF55208.2022.00100","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00100","url":null,"abstract":"A big challenge of autonomous mobility is guaranteeing safety in all possible extreme and unexpected scenarios. For the last 25 years, the sector therefore focused on improving the automation functions. Nevertheless, autonomous mobility is still not part of daily life. The 5G-Blueprint project follows an alternative approach: direct control teleoperation. This concept relies on 5G connectivity to remove the physical coupling between the human driver or sailor and the controlled vehicle or vessel. This way, automation and teleoperation can be combined as complementary technologies, assigning them to different segments of a single trajectory, realizing driverless mobility in a safe, scalable, and cost-efficient manner. However, this mode of operation brings demanding connectivity requirements, such as high uplink bandwidth, low latency and ultra-reliability at the same time, for which the potential of 5G needs to be studied and explored. In this paper, we present our performance validation strategies to pursue 5G-enhanced teleoperation in real-life environment (e.g., public roads, busy sea ports), including some initial results that we collected during the in-country piloting phase.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132964312","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: 1

Pre-hospital Triage Improvement for Ambulances via 5G Video and Vital Data Communication 通过5G视频和重要数据通信改善救护车院前分诊

2022 IEEE Future Networks World Forum (FNWF) Pub Date : 2022-10-01 DOI: 10.1109/FNWF55208.2022.00104

Haibin Zhang, Y. Toh, Iñaki Martín Soroa, D. Morris, Marie-Pauline Roukens

引用次数: 0

Multi-Stage, Dynamic Control of Wireless Network Slices with Polymorphic Algorithms 基于多态算法的无线网络切片多阶段动态控制

2022 IEEE Future Networks World Forum (FNWF) Pub Date : 2022-10-01 DOI: 10.1109/FNWF55208.2022.00085

Ravi Potluri, Kristen Young, Jin Yang

引用次数: 0

Decoupling Statistical Trends from Data Volume on LDP-Based Spatio-Temporal Data Collection 基于ldp时空数据采集的数据量统计解耦趋势

2022 IEEE Future Networks World Forum (FNWF) Pub Date : 2022-10-01 DOI: 10.1109/FNWF55208.2022.00053

Taisho Sasada, Yuzo Taenaka, Y. Kadobayashi

{"title":"Decoupling Statistical Trends from Data Volume on LDP-Based Spatio-Temporal Data Collection","authors":"Taisho Sasada, Yuzo Taenaka, Y. Kadobayashi","doi":"10.1109/FNWF55208.2022.00053","DOIUrl":"https://doi.org/10.1109/FNWF55208.2022.00053","url":null,"abstract":"Spatio-temporal data is useful for various applications such as urban planning, epidemiology, and natural disasters, but causes exposure of private information, such as home/workplace addresses, because it involves people's trajec-tories. Local Differential Privacy (LDP) based processing is a promising technology for removing sensitive information from spatio-temporal data. A LDP-based processing adds a certain amount of noise to make each piece of data indistinguishable while keeping its intrinsic value. However, LDP is vulnerable to data amplification. When a data store receives data from any device, the data store only appends the received data to existing data. This allows anyone to inject any amount of data into the data and manipulate the trend of the whole data. To tackle this problem, we design a data collection method enabling a data store to collect statistical trends of data from every device irrespective of the data volume. We utilize an Oblivious Transfer (OT) protocol that performs a packet sampling at the reception side, the data store. This sampling enables the collection of statistical trends but requires adjusting LDP processing because the amount of noise is determined by the assumption that the data store receives every piece of LDP-processed data. We then propose an adjustment method for LDP-based process based on the Euclidean algorithm. We conducted qualitative and experimental overhead analysis and showed that the proposed method decouples the relationship between statistical trend and data volume. We also show the processing load can be acceptable on small devices such as smartphones and loT.","PeriodicalId":300165,"journal":{"name":"2022 IEEE Future Networks World Forum (FNWF)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128115396","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: 1