2018 IEEE 7th International Conference on Cloud Networking (CloudNet)最新文献_第4页

NFV-Inspector: A Systematic Approach to Profile and Analyze Virtual Network Functions NFV-Inspector:一种系统的虚拟网络功能分析方法

2018 IEEE 7th International Conference on Cloud Networking (CloudNet) Pub Date : 2018-10-01 DOI: 10.1109/CloudNet.2018.8549333

Michel Gokan Khan, S. Bastani, J. Taheri, A. Kassler, Shuiguang Deng

{"title":"NFV-Inspector: A Systematic Approach to Profile and Analyze Virtual Network Functions","authors":"Michel Gokan Khan, S. Bastani, J. Taheri, A. Kassler, Shuiguang Deng","doi":"10.1109/CloudNet.2018.8549333","DOIUrl":"https://doi.org/10.1109/CloudNet.2018.8549333","url":null,"abstract":"Network Function Virtualization (NFV) focuses on decoupling network functions from proprietary hardware (i.e., middleboxes) by leveraging virtualization technology. Combining it with Software Defined Networking (SDN) enables us to chain network services much easier and faster. The main idea of using these technologies is to consolidate several Virtual Network Functions (VNFs) into a fewer number of commodity servers to reduce costs, increase VNFs fluidity and improve resource efficiency. However, the resource allocation and placement of VNFs in the network is a multifaceted decision problem that depends on many factors, including VNFs resource demand characteristics, arrival rate, configuration of underlying infrastructure, available resources and agreed Quality of Services (QoS) in Service Level Agreements (SLAs). This paper presents a bottom-up open-source NFV analysis platform (NFV-Inspector) to (1) systematically profile and classify VNFs based on resource capacities, traffic demand rate, underlying system properties, placement of VNFs in the network, etc. and (2) extract/calculate the correlation among the QoS metrics and resource utilization of VNFs. We evaluated our approach using an emulated virtual Evolved Packet Core platform (Open5GCore) to showcase how complex relation among various NFV service chains can be systematically profiled and analyzed.","PeriodicalId":436842,"journal":{"name":"2018 IEEE 7th International Conference on Cloud Networking (CloudNet)","volume":"8 1-2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114047259","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: 12

Optimal Service Function Chain Placement Modeling for Minimizing Setup and Operation Cost 最小设置和运营成本的服务功能链布局优化模型

2018 IEEE 7th International Conference on Cloud Networking (CloudNet) Pub Date : 2018-10-01 DOI: 10.1109/CloudNet.2018.8549288

Yansen Xu, Ved P. Kafle

引用次数: 0

Evaluation of Virtual Customer Premises Equipment Prototype System with Open Source Software 基于开源软件的虚拟客户端设备原型系统评估

2018 IEEE 7th International Conference on Cloud Networking (CloudNet) Pub Date : 2018-10-01 DOI: 10.1109/CloudNet.2018.8549554

Akihiro Kimura, S. Kawano, Hideo Tsuchiya, Shunsuke Homma, Akihiro Okada

引用次数: 4

Efficient Dynamic Flow Tracking for Packet Analyzers 高效动态流量跟踪数据包分析

2018 IEEE 7th International Conference on Cloud Networking (CloudNet) Pub Date : 2018-10-01 DOI: 10.1109/CloudNet.2018.8549214

Paul Emmerich, Maximilian Pudelko, Quirin Scheitle, G. Carle

{"title":"Efficient Dynamic Flow Tracking for Packet Analyzers","authors":"Paul Emmerich, Maximilian Pudelko, Quirin Scheitle, G. Carle","doi":"10.1109/CloudNet.2018.8549214","DOIUrl":"https://doi.org/10.1109/CloudNet.2018.8549214","url":null,"abstract":"Analyzing large amounts of traffic at the packet or flow level is an important part of managing and monitoring cloud network infrastructure. Common scenarios that require low-level packet analysis are troubleshooting problems, accounting traffic, and security applications such as intrusion detection systems or firewalls. Moreover, researchers often analyze traffic for scientific purposes. For such low-level traffic analyses, tracking flows is a feature required for both commercial and scientific purposes. However, there is no good shared library available to implement this functionality in an efficient, configurable, and dynamic way that is suitable for real-time analysis. We implement a high-performant generic flow tracker that can track millions of simultaenous flows based on arbitrarily complex definitions of a flow. We make this implementation available as open source in our traffic analysis tool FlowScope. The highly efficient realtime tracking of flows by arbitrarily complex user-defined flow criteria and filters is enabled by just-in-time (JIT) compilation of flow tracking rules. The code and evaluation scripts are available as free and open source at","PeriodicalId":436842,"journal":{"name":"2018 IEEE 7th International Conference on Cloud Networking (CloudNet)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122313534","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: 9

Time Efficient Energy-Aware Routing in Software Defined Networks 软件定义网络中的时间高效能量感知路由

2018 IEEE 7th International Conference on Cloud Networking (CloudNet) Pub Date : 2018-10-01 DOI: 10.1109/CloudNet.2018.8549457

Yu-Hao Chen, T. Chin, Chin-Ya Huang, Shan-Hsiang Shen, Ruei-Yan Huang

{"title":"Time Efficient Energy-Aware Routing in Software Defined Networks","authors":"Yu-Hao Chen, T. Chin, Chin-Ya Huang, Shan-Hsiang Shen, Ruei-Yan Huang","doi":"10.1109/CloudNet.2018.8549457","DOIUrl":"https://doi.org/10.1109/CloudNet.2018.8549457","url":null,"abstract":"As devices and traffic in the Internet increase, power consumption becomes a critical issue for Information and Communication Technology (ICT) industry. The emerging technology, Software Defined Networking (SDN), can adaptively manage the network resources and control the power consumption. In this paper, we first investigate the time efficient energy aware routing in SDN enabled networks, and then propose a Time Efficient Energy Aware Routing (TEAR) algorithm. The goal of this work is to effectively reduce the number of used links for packet delivery so that the energy consumption can be decreased. Different from most existing schemes which only focus on static demands, the proposed TEAR algorithm considers both the temporal variation in demand and computational efficiency when finding routing paths. Specifically, the energy consumption problem for routing traffic in a network is formulated as an integer linear programming problem. Hence, the proposed TEAR algorithm can dynamically route flows in a time efficient manner. The evaluation results show that the proposed scheme outperforms other schemes in terms of computation time and energy consumption of the network.","PeriodicalId":436842,"journal":{"name":"2018 IEEE 7th International Conference on Cloud Networking (CloudNet)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123169165","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

A Distributed Algorithm for Multi-Stage Computation Offloading 一种分布式多阶段计算卸载算法

2018 IEEE 7th International Conference on Cloud Networking (CloudNet) Pub Date : 2018-10-01 DOI: 10.1109/CloudNet.2018.8549534

Tobias Mahn, Dennis Becker, Hussein Al-Shatri, A. Klein

{"title":"A Distributed Algorithm for Multi-Stage Computation Offloading","authors":"Tobias Mahn, Dennis Becker, Hussein Al-Shatri, A. Klein","doi":"10.1109/CloudNet.2018.8549534","DOIUrl":"https://doi.org/10.1109/CloudNet.2018.8549534","url":null,"abstract":"A scenario consisting of several mobile users, an access point (AP) and a cloud server in a multi-stage hierarchy is considered. Each user has a computation task which can be computed locally or offloaded to the AP or to the cloud server. Considering the shared access channel between users and the AP, the shared computation resources at the AP and the shared backhaul link connection from the AP to the cloud, an energy minimization computation offloading problem with a time constraint is tackled. The time constraint guarantees that the offloading time will not exceed the local computation time. In this paper, we propose a distributed game theoretic algorithm which decomposes the offloading problem into the subproblems of resource allocation and offloading decisions. The algorithm works iteratively between the two subproblems as follows: The AP receives offloading decisions from the users and accordingly optimizes the fractions of the bandwidth on the access channel, the fractions of the backhaul link rate and the fractions of the computation resource at the AP for all offloading users. Based on the assigned resources, each user autonomously decides between local computation or offloading to the AP or to the cloud server and reports its decision to the AP. Our proposed algorithm is shown to require only limited signaling between users and AP and converges in significantly few iterations. Furthermore, the results show that our algorithm performs close to the optimal policy.","PeriodicalId":436842,"journal":{"name":"2018 IEEE 7th International Conference on Cloud Networking (CloudNet)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121571198","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

An HTTP Adaptive Streaming Method Considering Motion Intensity 一种考虑运动强度的HTTP自适应流方法

2018 IEEE 7th International Conference on Cloud Networking (CloudNet) Pub Date : 2018-10-01 DOI: 10.1109/CloudNet.2018.8549555

Shungo Mori, Yu Mizoguchi, M. Bandai

引用次数: 0

Anomaly Detection for Black Box Services in Edge Clouds Using Packet Size Distribution 基于数据包大小分布的边缘云黑匣子业务异常检测

2018 IEEE 7th International Conference on Cloud Networking (CloudNet) Pub Date : 2018-10-01 DOI: 10.1109/CloudNet.2018.8549546

Marcel Wallschläger, Anton Gulenko, Florian Schmidt, Alexander Acker, O. Kao

{"title":"Anomaly Detection for Black Box Services in Edge Clouds Using Packet Size Distribution","authors":"Marcel Wallschläger, Anton Gulenko, Florian Schmidt, Alexander Acker, O. Kao","doi":"10.1109/CloudNet.2018.8549546","DOIUrl":"https://doi.org/10.1109/CloudNet.2018.8549546","url":null,"abstract":"Future services in fields like autonomous driving and virtual reality rely on cloud computing resources located at the edge of Internet Service Provider(ISP) networks. Instead of deploying many service-specific monitoring and reliability platforms, a centralized monitoring solution can reduce the usage of the already sparse edge cloud resources. The ISP can offer such a service using the black box monitoring approach presented in this paper. Current cloud providers already collect data about customer services for cloud performance and cloud reliability. We propose to extend current monitoring solutions for virtual machines by real-time analysis of network packet headers. In particular, we use the packet size distribution and the TCP connection time to infer the operational state of the service. We conduct an evaluation of the presented approach using a content delivery system which is set into different load and anomaly states. The random forest algorithm trained to differentiate normal from abnormal service states based on the collected data resulted in an accuracy of 94%. The overhead of collecting the data on a commodity hardware hypervisor using eBPF is about 3% CPU at 10GB/s.","PeriodicalId":436842,"journal":{"name":"2018 IEEE 7th International Conference on Cloud Networking (CloudNet)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133216320","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

Exploring Computing at the Edge: A Multi-Interface System Architecture Enabled Mobile Device Cloud 探索边缘计算:支持移动设备云的多接口系统架构

2018 IEEE 7th International Conference on Cloud Networking (CloudNet) Pub Date : 2018-10-01 DOI: 10.1109/CloudNet.2018.8549296

V. Balasubramanian, M. Aloqaily, Faisal Zaman, Y. Jararweh

{"title":"Exploring Computing at the Edge: A Multi-Interface System Architecture Enabled Mobile Device Cloud","authors":"V. Balasubramanian, M. Aloqaily, Faisal Zaman, Y. Jararweh","doi":"10.1109/CloudNet.2018.8549296","DOIUrl":"https://doi.org/10.1109/CloudNet.2018.8549296","url":null,"abstract":"Today, mobile applications advancements have overcome limited device capabilities by offloading to costly public cloud. As the edge computing paradigm began to take precedence, a mobile device cloud (MDC) formed at the edge based on idle intra-device resources emerged. This is a result of a customized user-centric composition service request for a time-bound application. Herein, devices volunteer their intra-device resources for producing a compute environment in turn satisfying the needs of the consumer. Now, with the growth of device technology and the available interfaces for accessing multiple radio technologies, a new transport layer protocol called Multipath TCP was introduced in literature. This protocol enables multiple sub-flows to join for transmitting data simultaneously. However, in scenarios like formation of device clouds, there are issues pertaining to sub-flows that are involved in a device cloud composition. One such issue is the management of sub-flow buffer. As each of these sub-flows have their own respective buffering and characteristic delays, it leads to sub-optimal performance in term of buffer occupancy. Thereby, degrading the quality of the device cloud composition. To this end, we propose an OS side architecture that plays a crucial role in managing the traffic coming from different flows. We model an agent that works conservatively satisfying Kleinrock's law and show a proof of concept experiment","PeriodicalId":436842,"journal":{"name":"2018 IEEE 7th International Conference on Cloud Networking (CloudNet)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131944138","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: 25

IEEE CloudNet 2018 Organizing Committee IEEE CloudNet 2018组委会

2018 IEEE 7th International Conference on Cloud Networking (CloudNet) Pub Date : 2018-10-01 DOI: 10.1109/cloudnet.2018.8549416

引用次数: 0