2020 IEEE 9th International Conference on Cloud Networking (CloudNet)最新文献_第3页

On Providing Low-cost Flow Monitoring for SDN Networks 浅谈为SDN网络提供低成本流量监控

2020 IEEE 9th International Conference on Cloud Networking (CloudNet) Pub Date : 2020-11-09 DOI: 10.1109/CloudNet51028.2020.9335797

Haythem Yahyaoui, M. Zhani

{"title":"On Providing Low-cost Flow Monitoring for SDN Networks","authors":"Haythem Yahyaoui, M. Zhani","doi":"10.1109/CloudNet51028.2020.9335797","DOIUrl":"https://doi.org/10.1109/CloudNet51028.2020.9335797","url":null,"abstract":"Traffic monitoring at the flow or even at the packet level has recently gained momentum with the emergence of critical and high-precision network applications like telesurgery, teleportation, and video gaming. However, achieving such fine-grained, continuous, and high-frequency monitoring is particularly challenging as it may result in a high monitoring traffic load on the network consuming significant amounts of bandwidth (referred to as monitoring cost), especially when this traffic has to cross several hops to reach the collecting point. Another challenge is to ensure that the statistics reporting delay ( i.e., the time needed to retrieve the statistics) does not exceed a certain threshold in order to analyze the statistics in a timely manner. In this paper, we address the problem of minimizing the monitoring cost while satisfying the flows' reporting delays by carefully selecting the switch reporting statistics of each flow in the network and taking into consideration the bandwidth available for monitoring and the capacity of the switches. Specifically, we formulate the problem of switch-to-flow selection as an integer linear program and put forward a heuristic algorithm to cope with large-scale instances where the number of flows and switches are significant. Through extensive simulations, we show that the proposed algorithm outperforms two existing monitoring strategies in terms of monitoring cost and reporting delay and provides near-optimal solution with minimal computation time.","PeriodicalId":156419,"journal":{"name":"2020 IEEE 9th International Conference on Cloud Networking (CloudNet)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131897710","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: 6

[Title page] (标题页)

2020 IEEE 9th International Conference on Cloud Networking (CloudNet) Pub Date : 2020-11-09 DOI: 10.1109/cloudnet51028.2020.9335815

引用次数: 0

Optimal VNF Placement and Traffic Steering using Column Generation 使用列生成的最佳VNF放置和流量控制

2020 IEEE 9th International Conference on Cloud Networking (CloudNet) Pub Date : 2020-11-09 DOI: 10.1109/CloudNet51028.2020.9335707

Devyani Gupta, J. Kuri

{"title":"Optimal VNF Placement and Traffic Steering using Column Generation","authors":"Devyani Gupta, J. Kuri","doi":"10.1109/CloudNet51028.2020.9335707","DOIUrl":"https://doi.org/10.1109/CloudNet51028.2020.9335707","url":null,"abstract":"VNF placement and traffic steering have received considerable attention in the literature, ever since business pressures started driving telecom operators to embrace virtualization technologies instead of continuing with the expensive “dedicated hardware and appliance” approach. However, most proposed solutions are not exact. When the formulated problem results in an Integer Linear Program (ILP) or a Mixed Integer Linear Program (MILP), the focus shifts to searching for heuristics. We show that using the Column Generation (CG) technique, exact solutions can be obtained quickly. The CG approach can be used to solve problems in both offline and online scenarios. For the aggregate bandwidth minimization problem, the exact solution provided by CG improves significantly upon “DP-COA”, a recently proposed heuristic. However, aggregate bandwidth minimization can lead to highly uneven link loading. Motivated by this, we formulate another problem in which the objective is to minimize the maximum link bandwidth consumed over all links in the network. This problem is also solved exactly using CG. Results indicate that this approach can help achieve balanced traffic demand placement.","PeriodicalId":156419,"journal":{"name":"2020 IEEE 9th International Conference on Cloud Networking (CloudNet)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123384181","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

Optimal Virtual Network Function Placement in Chains Using Backups with Availability Schedule 使用带可用性计划的备份的链中的最优虚拟网络功能布局

2020 IEEE 9th International Conference on Cloud Networking (CloudNet) Pub Date : 2020-11-09 DOI: 10.1109/CloudNet51028.2020.9335802

R. Kang, Fujun He, E. Oki

{"title":"Optimal Virtual Network Function Placement in Chains Using Backups with Availability Schedule","authors":"R. Kang, Fujun He, E. Oki","doi":"10.1109/CloudNet51028.2020.9335802","DOIUrl":"https://doi.org/10.1109/CloudNet51028.2020.9335802","url":null,"abstract":"A suitable virtual network function (VNF) placement considering a node availability schedule extends service continuous serviceable time by suppressing service interruption caused by function reallocation and node unavailabilities. However, function placement cannot avoid service interruption caused by node unavailabilities. This paper considers a primary and backup VNF placement model to avoid service interruption caused by node unavailabilities by using backup functions. The considered backup functions have a period of startup time for preparation before they can be used and the number of them is limited. The proposed model is formulated as an integer linear programming problem to place the primary and backup VNFs based on the availability schedule at continuous time slots. We aim to maximize the minimum number of continuously available time slots in all service function chains (SFCs) over the deterministic availability schedule. We obverse that the proposed model considering the limited number of backup functions outperforms baseline models in terms of the minimum number of longest continuous available time slots in all SFCs. We introduce an algorithm to estimate the number of key unavailabilities at each time slot, which can find the unavailable nodes which are the bottlenecks to increase the service continuous available time at each time slot.","PeriodicalId":156419,"journal":{"name":"2020 IEEE 9th International Conference on Cloud Networking (CloudNet)","volume":"196 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124550949","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

Comparative experimental analysis of Docker container networking drivers Docker容器联网驱动程序的对比实验分析

2020 IEEE 9th International Conference on Cloud Networking (CloudNet) Pub Date : 2020-11-09 DOI: 10.1109/CloudNet51028.2020.9335811

Lucas Litter Mentz, W. J. Loch, G. Koslovski

引用次数: 3

Sustainability Analysis in Data Center Dense Architectures 数据中心密集架构中的可持续性分析

2020 IEEE 9th International Conference on Cloud Networking (CloudNet) Pub Date : 2020-11-09 DOI: 10.1109/CloudNet51028.2020.9335791

Kádna Camboim, João Ferreira, J. Araujo, Fernanda M. R. Alencar

{"title":"Sustainability Analysis in Data Center Dense Architectures","authors":"Kádna Camboim, João Ferreira, J. Araujo, Fernanda M. R. Alencar","doi":"10.1109/CloudNet51028.2020.9335791","DOIUrl":"https://doi.org/10.1109/CloudNet51028.2020.9335791","url":null,"abstract":"Nowadays, energy projects for data centers need to consider the high consumption loads per rack due to the density achieved with modern IT equipment. Capacity management aims to ensure availability when supplying electricity at a safe level so that the available capacity is greater than the capacity used, without prejudice to future sizing, without burden to the total cost of ownership, but efficient enough to meet current needs. Nevertheless, organizations must include $CO_{2}$ emissions in their list of concerns because of electricity production/consumption. In this way, this paper estimates the critical load demand for data centers and propose energy flow models (EFM) for four architectures, evaluating the minimum energy required for the project and the metrics of exergy, costs, PUE, and efficiency. We use a Power Load Distribution Algorithm (PLDA) to evaluate energy consumption and calculate the impact of environmental sustainability concerning raw material used in power production. The results show that even a data center denser in IT infrastructure can emit less $CO_{2}$ and be more ecologically sustainable when the choice of energy sources is cleaner.","PeriodicalId":156419,"journal":{"name":"2020 IEEE 9th International Conference on Cloud Networking (CloudNet)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126194802","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: 3

A Lightweight Authentication and Inter-Cloud Payment Protocol for Edge Computing 面向边缘计算的轻量级认证和云间支付协议

2020 IEEE 9th International Conference on Cloud Networking (CloudNet) Pub Date : 2020-11-09 DOI: 10.1109/CloudNet51028.2020.9335814

Mohamed Seifelnasr, M. Nakkar, A. Youssef, R. Altawy

引用次数: 4

A Graph Neural Network Approach for Scalable and Dynamic IP Similarity in Enterprise Networks 企业网络中可扩展和动态IP相似度的图神经网络方法

2020 IEEE 9th International Conference on Cloud Networking (CloudNet) Pub Date : 2020-10-09 DOI: 10.1109/CloudNet51028.2020.9335789

Hazem M. Soliman, Geoffrey Salmon, Dusan Sovilj, M. Rao

{"title":"A Graph Neural Network Approach for Scalable and Dynamic IP Similarity in Enterprise Networks","authors":"Hazem M. Soliman, Geoffrey Salmon, Dusan Sovilj, M. Rao","doi":"10.1109/CloudNet51028.2020.9335789","DOIUrl":"https://doi.org/10.1109/CloudNet51028.2020.9335789","url":null,"abstract":"Measuring similarity between IP addresses is an important task in the daily operations of any enterprise network. Applications that depend on an IP similarity measure include measuring correlation between security alerts, building baselines for behavioral modelling, debugging network failures and tracking persistent attacks. However, IPs do not have a natural similarity measure by definition. Deep Learning architectures are a promising solution here since they are able to learn numerical representations for IPs directly from data, allowing various distance measures to be applied on the calculated representations. Current works have utilized Natural Language Processing (NLP) techniques for learning IP embeddings. However, these approaches have no systematic way to handle out-of-vocabulary (OOV) IPs not seen during training. In this paper, we propose a novel approach for IP embedding using an adapted graph neural network (GNN) architecture. This approach has the advantages of working on the raw data, scalability and, most importantly, induction, i.e. the ability to measure similarity between previously unseen IPs. Using data from an enterprise network, our approach is able to identify high similarities between local DNS servers and root DNS servers even though some of these machines are never encountered during the training phase.","PeriodicalId":156419,"journal":{"name":"2020 IEEE 9th International Conference on Cloud Networking (CloudNet)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134380020","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: 4