2022 IEEE 11th International Conference on Cloud Networking (CloudNet)最新文献_第3页

Deployment Guidelines for Cloud-RAN in Future Mobile Networks 云- ran在未来移动网络中的部署指南

2022 IEEE 11th International Conference on Cloud Networking (CloudNet) Pub Date : 2022-11-07 DOI: 10.1109/CloudNet55617.2022.9978902

Line M. P. Larsen, H. Christiansen, S. Ruepp, M. Berger

{"title":"Deployment Guidelines for Cloud-RAN in Future Mobile Networks","authors":"Line M. P. Larsen, H. Christiansen, S. Ruepp, M. Berger","doi":"10.1109/CloudNet55617.2022.9978902","DOIUrl":"https://doi.org/10.1109/CloudNet55617.2022.9978902","url":null,"abstract":"This work identifies and addresses current challenges and shortcomings arising in deployment and expansions of today’s mobile networks, in order to determine the future of the Cloud-Radio Access Network (C-RAN) architecture. C-RAN proposes a three-fold RAN architecture, improving the flexibility, energy efficiency and performance of the RAN. On the other hand, C-RAN requires a division of the base station functionalities resulting in very high requirements to the interconnecting transport network, the xhaul. C-RAN has been promoted as the network architecture for 5G and future mobile networks; however, it has not yet been adopted by the majority of network operators. This work studies existing deployment scenarios and evaluates deployment opportunities for green- and brownfield installations in rural, urban, high mobility and latency sensitive areas. The studies are backed up by examinations of real-life network traffic, predicting that in a group of cells covering multiple different areas, C-RAN will improve network resource utilisation by a factor > 2. The outcome of this work results in a set of concrete deployment guidelines for the introduction of C-RAN in brownfield network installations and future greenfield installations. The deployment guidelines include functional divisions of the RAN, functional placement scenarios and xhaul network requirements.","PeriodicalId":260541,"journal":{"name":"2022 IEEE 11th International Conference on Cloud Networking (CloudNet)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132585997","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

Terabytes and Terabits/s Packet Caching in ICN Routers using Programmable Switches 使用可编程交换机的ICN路由器中的tb和tb /s数据包缓存

2022 IEEE 11th International Conference on Cloud Networking (CloudNet) Pub Date : 2022-11-07 DOI: 10.1109/CloudNet55617.2022.9978805

Junji Takemasa, Y. Koizumi, T. Hasegawa

引用次数: 0

NS3SaaS: Cloud-based “Network Simulator as a Service” with customisable resource scheduling NS3SaaS:基于云的“网络模拟器即服务”，具有可定制的资源调度

2022 IEEE 11th International Conference on Cloud Networking (CloudNet) Pub Date : 2022-11-07 DOI: 10.1109/CloudNet55617.2022.9978899

K. Antonopoulos, Dimitris Ringas, E. Christopoulou, G. Keramidas, Christos D. Antonopoulos, N. Voros

{"title":"NS3SaaS: Cloud-based “Network Simulator as a Service” with customisable resource scheduling","authors":"K. Antonopoulos, Dimitris Ringas, E. Christopoulou, G. Keramidas, Christos D. Antonopoulos, N. Voros","doi":"10.1109/CloudNet55617.2022.9978899","DOIUrl":"https://doi.org/10.1109/CloudNet55617.2022.9978899","url":null,"abstract":"This paper presents the design, development and evaluation of a novel cloud-based Network Simulator as a Service. It wraps a discrete-event network simulator and deploys it as an elastic service, which can then be used for interactive and batch simulations execution, enhanced with results post-processing and analysis as well as presentation features. It addresses the requirement to rapidly carry out large numbers of network simulations in order to test and validate appropriate and domain specific optimisations in industry, research and education settings. This cloud based service drastically enhances the capabilities of a researcher by allowing arbitrary definition of simulation scenarios along with sets of parameters and commission of large scale simulation executions. It is based on an ensemble of efficient open-source tools, which, when properly coordinated, deliver to the end user a cloud based service that is novel, robust, extendible and extensible. It has been deployed within ESDA Lab (UoP, Greece) where several performance evaluation research scenarios were carried out testing different simulation scheduling schemes in order to evaluate the usefulness of our system and its efficiency under different prioritisation settings. Results demonstrate that, compared to the default general purpose network simulator, the offered cloud-based service significantly enhances end-users capabilities by tailor fitting to their different prioritisation requirements, e.g. favouring interactive users, minimising turnaround times, offering custom resources allocation, etc. In addition to that the offered service effectively hides the peculiarities of the standalone network simulator enabling its use by non-experts and significantly expanding the potential target group of end users.","PeriodicalId":260541,"journal":{"name":"2022 IEEE 11th International Conference on Cloud Networking (CloudNet)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124335830","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

DDoS Attack Detection via Privacy-aware Federated Learning and Collaborative Mitigation in Multi-domain Cyber Infrastructures 多域网络基础设施中基于隐私感知的联邦学习和协同缓解的DDoS攻击检测

2022 IEEE 11th International Conference on Cloud Networking (CloudNet) Pub Date : 2022-11-07 DOI: 10.1109/CloudNet55617.2022.9978815

Marinos Dimolianis, D. Kalogeras, Nikos Kostopoulos, B. Maglaris

{"title":"DDoS Attack Detection via Privacy-aware Federated Learning and Collaborative Mitigation in Multi-domain Cyber Infrastructures","authors":"Marinos Dimolianis, D. Kalogeras, Nikos Kostopoulos, B. Maglaris","doi":"10.1109/CloudNet55617.2022.9978815","DOIUrl":"https://doi.org/10.1109/CloudNet55617.2022.9978815","url":null,"abstract":"Interconnected cyber infrastructures, accessible via the Internet, are a common target of DDoS attacks intending to downgrade their operations and services. Collaborative protection mechanisms are prime candidates to defend against massive attacks but, although collaborations were instrumental in the Internet success story, this is largely not extended to multi-domain cyber security. Notably, collaborative DDoS detection is hindered by data privacy legislations, while mitigation is limited to operations of stand-alone rigid firewalls. Motivated by these shortcomings, we propose a Federated Learning schema for collaborative privacy-aware DDoS detection. Coordination is orchestrated by a third trusted party that aggregates machine learning models proposed by collaborators based on their private attack and benign traces, without exchanging sensitive data. Attacks detected via the privacy-aware federated model are subsequently mitigated by efficient and scalable firewalls, implemented within the eXpress Data Path (XDP) data plane programmability framework. Our approach was evaluated using production traffic traces in terms of packet classification accuracy and packet processing performance. We conclude that our proposed Federated Learning framework enabled collaborators to accurately classify benign and attack packets, thereby improving individual domain accuracy. Furthermore, our data plane programmable firewalls promptly mitigated large-scale attacks in emulated federated cyber infrastructures.","PeriodicalId":260541,"journal":{"name":"2022 IEEE 11th International Conference on Cloud Networking (CloudNet)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125041940","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

On the Implementation of a Software-Defined Memory Control Plane for Disaggregated Datacenters 分布式数据中心软件定义内存控制平面的实现

2022 IEEE 11th International Conference on Cloud Networking (CloudNet) Pub Date : 2022-11-07 DOI: 10.1109/CloudNet55617.2022.9978885

Ilias Syrigos, D. Syrivelis, T. Korakis

{"title":"On the Implementation of a Software-Defined Memory Control Plane for Disaggregated Datacenters","authors":"Ilias Syrigos, D. Syrivelis, T. Korakis","doi":"10.1109/CloudNet55617.2022.9978885","DOIUrl":"https://doi.org/10.1109/CloudNet55617.2022.9978885","url":null,"abstract":"By adopting a disaggregated hardware architecture, datacenters can achieve considerable efficiency gains and transition to a more sustainable and green future. By decoupling resources from a single monolithic server and connecting them through a high-speed optical network, it is possible to significantly increase resource utilization and reduce power consumption by consolidating workloads into fewer resource units. In this paper, we design and develop a software-defined control plane for disaggregated memory datacenters. Its core component, the Software-Defined Memory Controller, is the orchestrating software, which efficiently materializes the disaggregation concept. It accomplishes this by managing and monitoring remote resource pools, allocating resources to workloads, instrumenting the dynamic configuration of the underlying optical network for interconnecting remote compute and memory resources and interacting with software agents residing in host and guest Operating Systems for coordinating the attachment of remote memory. A major contribution of our design is the minimization of the delay for scheduling workloads and Virtual Machines in a disaggregated datacenter, which is accomplished with the efficient modelling of the disaggregated resources and networking elements into a graph for retrieving configuration data, as well as the optimization of the graph implementation. The architecture is based on the Everything-as-a-Service paradigm and is tightly coupled with OpenStack, the leading cloud infrastructure management software. Evaluation experiments validated the employment of a graph database system by the Software-Defined Memory Controller by demonstrating 58 percent faster query times than relational databases for a small-to-medium-sized datacenter, with the percentage increasing as the size of the datacenter grows.","PeriodicalId":260541,"journal":{"name":"2022 IEEE 11th International Conference on Cloud Networking (CloudNet)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127831295","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

Robust Multi-Resource Allocation Against Controller Failures in Network Slice Provisioning 针对控制器故障的网络切片鲁棒多资源分配

2022 IEEE 11th International Conference on Cloud Networking (CloudNet) Pub Date : 2022-11-07 DOI: 10.1109/CloudNet55617.2022.9978814

Laiza de Lara, Francesca Fossati, Stéphane Rovedakis

引用次数: 0

Virtual Network Embedding using a Federated DRL Approach 使用联邦DRL方法的虚拟网络嵌入

2022 IEEE 11th International Conference on Cloud Networking (CloudNet) Pub Date : 2022-11-07 DOI: 10.1109/CloudNet55617.2022.9978803

Saurav Chakraborty, K. Sivalingam

{"title":"Virtual Network Embedding using a Federated DRL Approach","authors":"Saurav Chakraborty, K. Sivalingam","doi":"10.1109/CloudNet55617.2022.9978803","DOIUrl":"https://doi.org/10.1109/CloudNet55617.2022.9978803","url":null,"abstract":"This paper deals with allocating resources for virtual network requests in the underlying substrate of an infrastructure provider (INP). This is called the virtual network embedding problem. A client’s virtual network request (VNR) is accepted if the INP’s Virtual Network Embedding (VNE) agent successfully maps all the virtual nodes and links to suitable substrate nodes and links satisfying the CPU and bandwidth requirements of nodes and links. We consider a scenario where multiple INPs exist, catering to the VNR requests of their respective clients. In this paper, we have used a Federated Deep Reinforcement Learning (Federated DRL) approach, where the INPs individually train their agents based on DRL. During the training, the DRL agent learns to map the virtual nodes to substrate nodes. Subsequently, the INPs operators learn collaboratively by sharing only the respective trained model information, without revealing any detailed vital information to each other. The federated reinforcement learning model is implemented using TensorFlow; the VNRs arrival is modeled using SimPy package, and the network graphs for virtual and substrate networks are created using the NetworkX package. The proposed solution accepts around 5% more VNRs, accumulates around 7% more revenue, and performs around 10% better in terms of the revenue to embedding cost ratio compared to existing algorithms.","PeriodicalId":260541,"journal":{"name":"2022 IEEE 11th International Conference on Cloud Networking (CloudNet)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132485392","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

Fingerprinting Web Pages and Smartphone Apps from Encrypted Network Traffic with WebScanner 指纹网页和智能手机应用程序从加密的网络流量与WebScanner

2022 IEEE 11th International Conference on Cloud Networking (CloudNet) Pub Date : 2022-11-07 DOI: 10.1109/CloudNet55617.2022.9978877

P. Casas, Nikolas Wehner, Sarah Wassermann, Michael Seufert

{"title":"Fingerprinting Web Pages and Smartphone Apps from Encrypted Network Traffic with WebScanner","authors":"P. Casas, Nikolas Wehner, Sarah Wassermann, Michael Seufert","doi":"10.1109/CloudNet55617.2022.9978877","DOIUrl":"https://doi.org/10.1109/CloudNet55617.2022.9978877","url":null,"abstract":"Traffic encryption reduces the visibility of Internet Service Providers (ISPs) on the services consumed by their customers. This is particularly challenging for monitoring and analysis of web and apps traffic, which is highly complex and heterogeneous. Loading a web-page or app today requires tens of flows to download the various resources located in distributed cloud servers from different content providers. We introduce WebScanner, a web-page and app fingerprinting approach capable to identify all the traffic flows corresponding to individual web-page and app loading sessions within concurrent web pages traffic, enabling highly detailed, per web-page analysis in practical deployments. Different from the state of the art in web and app traffic fingerprinting, WebScanner automatically performs the parsing of all the (encrypted) traffic generated by a web visit and its isolation from concurrent traffic, instead of assuming that an external oracle system does so. WebScanner also implements a deep fingerprinting approach to detect user action-dependent traffic from apps, relying on simple machine learning models and strong input features as fingerprints. Extensive evaluation across a large measurement dataset of popular web pages and mobile apps confirms the outstanding performance of WebScanner, identifying the top-500 Alexa websites with precision and recall (P/R) above 95%, isolating their full contents with P/R above 80% for up to 15 concurrent web pages visited by the same device, and detecting specific action-dependent apps traffic with average P/R above 92%.","PeriodicalId":260541,"journal":{"name":"2022 IEEE 11th International Conference on Cloud Networking (CloudNet)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128965477","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

Acceleration of MQTT-SN protocol using P4 使用P4加速MQTT-SN协议

2022 IEEE 11th International Conference on Cloud Networking (CloudNet) Pub Date : 2022-11-07 DOI: 10.1109/CloudNet55617.2022.9978851

Ryohei Banno, K. Osawa

{"title":"Acceleration of MQTT-SN protocol using P4","authors":"Ryohei Banno, K. Osawa","doi":"10.1109/CloudNet55617.2022.9978851","DOIUrl":"https://doi.org/10.1109/CloudNet55617.2022.9978851","url":null,"abstract":"MQTT-SN is one of the protocols attracting attention for Internet of Things (IoT) systems. It is suitable for collecting data from sensor devices due to its lightweight protocol design and loose coupling nature derived from the publish/subscribe model. To handle enormous IoT data, the performance of MQTT-SN brokers is a significant concern. Typical approaches to improving performance are using multiple brokers for load distribution and bringing out the hardware performance. However, the former involves larger latency due to cooperation overhead among brokers, and the latter has less flexibility than generic software brokers. To address these problems, we propose PAMS, an in-network acceleration method of the MQTT-SN protocol. PAMS makes a network switch perform a part of broker functionality by using P4, a leading data plane programming language. Although PAMS introduces in-network acceleration for performance improvement, it uses a software broker for the principal functionality of MQTT-SN so that we obtain flexibility as well. From analytical and quantitative evaluation, we clarify that PAMS lowers the load of the broker and reduces latency.","PeriodicalId":260541,"journal":{"name":"2022 IEEE 11th International Conference on Cloud Networking (CloudNet)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121645254","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

Bifrost: A Secure, Scalable and Efficient File Sharing System Based on Dual Deduplication Bifrost:基于双重复数据删除的安全、可扩展、高效的文件共享系统

2022 IEEE 11th International Conference on Cloud Networking (CloudNet) Pub Date : 2022-11-07 DOI: 10.1109/CloudNet55617.2022.9978810

Hadi Sehat, D. Lucani, Elena Pagnin

{"title":"Bifrost: A Secure, Scalable and Efficient File Sharing System Based on Dual Deduplication","authors":"Hadi Sehat, D. Lucani, Elena Pagnin","doi":"10.1109/CloudNet55617.2022.9978810","DOIUrl":"https://doi.org/10.1109/CloudNet55617.2022.9978810","url":null,"abstract":"We consider the problem of sharing sensitive files across users while relying on a common, untrusted third-party, e.g., a Cloud Storage Provider (CSP). Although users can rely on a secure peer-to-peer (P2P) channel for file sharing, this introduces potential delay on the data transfer and requires the sender to remain connected while the transfer process occurs. Instead, users can upload information about the file on a common CSP and share only the essential information that enables the receiver to recover the original file. However, using encryption to protect the uploaded information from the untrusted cloud hinders deduplication capabilities, which is undesirable for CSPs. This paper introduces Bifrost, an innovative file sharing method inspired by recent results on dual deduplication. Bifrost achieves secure file sharing using an untrusted cloud, and simultaneously guarantees that (1) the CSP can efficiently deduplicate outsourced data; (2) the secure P2P channel is used only to transmit short, but crucial information; (3) users can check for data integrity, i.e., detect if the CSP alters the outsourced data; and (4) only the sender and the intended receiver can recover the sensitive file, i.e., the cloud or no malicious adversary can infer useful information about the shared file. We analyze compression and bandwidth performance using a proof-of-concept implementation. Our experiments show that secure file sharing can be achieved by sending as little as 640 bits on the P2P channel, irrespective of file size, while the CSP that aids the sharing can enjoy a deduplication rate of 86.9 %.","PeriodicalId":260541,"journal":{"name":"2022 IEEE 11th International Conference on Cloud Networking (CloudNet)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122687947","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