2016 12th International Conference on Network and Service Management (CNSM)最新文献_第4页

Applying big data technologies to manage QoS in an SDN 应用大数据技术管理SDN的QoS

2016 12th International Conference on Network and Service Management (CNSM) Pub Date : 2016-10-01 DOI: 10.1109/CNSM.2016.7818437

Shashwat Jain, Manish Kumar Khandelwal, Ashutosh Katkar, Joseph Nygate

引用次数: 27

Graph-based diagnosis in software-defined infrastructure 软件定义基础架构中基于图的诊断

2016 12th International Conference on Network and Service Management (CNSM) Pub Date : 2016-10-01 DOI: 10.1109/CNSM.2016.7818425

J. Wahba, Hazem M. Soliman, H. Bannazadeh, A. Leon-Garcia

引用次数: 3

Understanding the role of change in incident prevention 了解变化在事故预防中的作用

2016 12th International Conference on Network and Service Management (CNSM) Pub Date : 2016-10-01 DOI: 10.1109/CNSM.2016.7818430

Sinem Güven, K. Murthy

引用次数: 7

Dynamic resource allocation of smart home workloads in the cloud 云中智能家居工作负载的动态资源分配

2016 12th International Conference on Network and Service Management (CNSM) Pub Date : 2016-10-01 DOI: 10.1109/CNSM.2016.7818449

Shahin Vakilinia, M. Cheriet, J. Rajkumar

{"title":"Dynamic resource allocation of smart home workloads in the cloud","authors":"Shahin Vakilinia, M. Cheriet, J. Rajkumar","doi":"10.1109/CNSM.2016.7818449","DOIUrl":"https://doi.org/10.1109/CNSM.2016.7818449","url":null,"abstract":"Cloud computing offers provision for elastic and scalable infrastructure resource allocation across the network that allows deployment of services for controlling home devices and appliances. Data generated from heterogeneous smart home devices are processed in different application services deployed in the cloud data center. The primary challenge of smart home service provider's is to optimize the cloud resource allocation while satisfying the Quality of Service(QoS) constraints of the application services. Service execution time is one of the most vital QoS parameters. In this paper, a queuing theoretic approach is proposed to model the smart home workload. First, M/M/c queue model is applied to find the response time of smart home tasks with light variation over the arrival rate. Then, Markovian Modulated Poisson Process (MMPP) is used to extend the model to a more advanced type of smart home processing workloads. Next, the optimal number of Virtual Machines(VMs) required deploying the application servers that can satisfy the execution time constraint of incoming workloads is calculated. Finally, total service time of a smart home application is calculated considering into account the possible level of concurrency and dependency among tasks of an application service. In the end, some numerical and simulation examples are provided to validate our findings.","PeriodicalId":334604,"journal":{"name":"2016 12th International Conference on Network and Service Management (CNSM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115410540","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

On the impact of advance reservations for energy-aware provisioning of bare-metal cloud resources 论提前预约对裸机云资源节能配置的影响

2016 12th International Conference on Network and Service Management (CNSM) Pub Date : 2016-10-01 DOI: 10.1109/CNSM.2016.7818424

M. Assunção, L. Lefèvre, François Rossigneux

引用次数: 5

Driver identification and authentication with active behavior modeling 使用主动行为建模的驾驶员识别和身份验证

2016 12th International Conference on Network and Service Management (CNSM) Pub Date : 2016-10-01 DOI: 10.1109/CNSM.2016.7818453

Angela Burton, Tapan S. Parikh, Shannon Mascarenhas, Jue Zhang, Jonathan Voris, N. S. Artan, Wenjia Li

{"title":"Driver identification and authentication with active behavior modeling","authors":"Angela Burton, Tapan S. Parikh, Shannon Mascarenhas, Jue Zhang, Jonathan Voris, N. S. Artan, Wenjia Li","doi":"10.1109/CNSM.2016.7818453","DOIUrl":"https://doi.org/10.1109/CNSM.2016.7818453","url":null,"abstract":"The legitimate driver of a vehicle traditionally gains authorization to access their vehicle via tokens such as ignition keys, some modern versions of which feature RFID tags. However, this token-based approach is not capable of detecting all instances of vehicle misuse. Technology trends have allowed for affordable and efficient collection of various sensor data in real time from the vehicle, its surroundings, and devices carried by the driver, such as smartphones. In this paper, we propose to use this sensory data to actively identify and authenticate the driver of a vehicle by determining characteristics which uniquely categorize individuals' driving behavior. Our approach is capable of continuously authenticating a driver throughout a driving session, as opposed to alternative approaches which are either performed offline or as a session starts. This means our modeling approach can be used to detect mid-session driving attacks, such as carjacking, which are beyond the scope of alternative driver authentication solutions. A simulated driving environment was used to collect sensory data of driver habits including steering wheel position and pedal pressure. These features are classified using a Support Vector Machine (SVM) learning algorithm. Our pilot study with 10 human subjects shows that we can use various aspects of how a vehicle is operated to successfully identify a driver under 2.5 minutes with a 95% confidence interval and with at most one false positive per driving day.","PeriodicalId":334604,"journal":{"name":"2016 12th International Conference on Network and Service Management (CNSM)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123156994","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: 35

CAAMP: Completely automated DDoS attack mitigation platform in hybrid clouds CAAMP:混合云中完全自动化的DDoS攻击缓解平台

2016 12th International Conference on Network and Service Management (CNSM) Pub Date : 2016-10-01 DOI: 10.1109/CNSM.2016.7818409

Nasim Beigi Mohammadi, C. Barna, Mark Shtern, Hamzeh Khazaei, Marin Litoiu

{"title":"CAAMP: Completely automated DDoS attack mitigation platform in hybrid clouds","authors":"Nasim Beigi Mohammadi, C. Barna, Mark Shtern, Hamzeh Khazaei, Marin Litoiu","doi":"10.1109/CNSM.2016.7818409","DOIUrl":"https://doi.org/10.1109/CNSM.2016.7818409","url":null,"abstract":"Distributed Denial of Service (DDoS) attacks are one of the main concerns for online service providers because of their impact on cost/revenue and reputation. This paper presents Completely Automated DDoS Attack Mitigation Platform (CAAMP), a novel platform to mitigate DDoS attacks on public cloud applications using capabilities of software defined infrastructure and network function virtualization techniques. When suspicious traffic is identified, CAAMP deploys a copy of the application's topology on-the-fly (a shark tank) on an isolated environment in a private cloud. It then creates a virtual network that will host the shark tank. Software defined networking (SDN) controller programs the virtual switches dynamically to redirect the suspicious traffic to the shark tank until final decision is made. If traffic is proved to be non-malicious, SDN controller installs flow rules on the switches to redirect the traffic back to the original application. Thus, CAAMP autonomically protects applications against potential DDoS threats and lowers the false positives associated with common detection mechanisms by leveraging resources from a private cloud.","PeriodicalId":334604,"journal":{"name":"2016 12th International Conference on Network and Service Management (CNSM)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116531031","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: 19

BuDDI: Bug detection, debugging, and isolation middlebox for software-defined network controllers BuDDI:用于软件定义网络控制器的错误检测、调试和隔离中间件

2016 12th International Conference on Network and Service Management (CNSM) Pub Date : 2016-10-01 DOI: 10.1109/CNSM.2016.7818438

Rohit Abhishek, Shuai Zhao, Sejun Song, Baek-Young Choi, Henry Zhu, D. Medhi

{"title":"BuDDI: Bug detection, debugging, and isolation middlebox for software-defined network controllers","authors":"Rohit Abhishek, Shuai Zhao, Sejun Song, Baek-Young Choi, Henry Zhu, D. Medhi","doi":"10.1109/CNSM.2016.7818438","DOIUrl":"https://doi.org/10.1109/CNSM.2016.7818438","url":null,"abstract":"Despite tremendous software quality assurance efforts made by network vendors, chastising software bugs is a difficult problem especially, for the network systems in operation. Recent trends towards softwarization and opensourcing of network functions, protocols, controls, and applications tend to cause more software bug problems and pose many critical challenges to handle them. Although many traditional redundancy recovery mechanisms are adopted to the softwarized systems, software bugs cannot be resolved with them due to unexpected failure behavior. Furthermore, they are often bounded by common mode failure and common dependencies (CMFD). In this paper, we propose an online software bug detection, debugging, and isolation (BuDDI) middlebox architecture for software-defined network controllers. The BuDDI architecture consists of a shadow-controller based online debugging facility and a CMFD mitigation module in support of a seamless heterogeneous controller failover. Our proof-of-concept implementation of BuDDI is on the top of OpenVirtex by using Ryu and Pox controllers and verifies that the heterogeneous controller switchover does not cause any additional performance overhead.","PeriodicalId":334604,"journal":{"name":"2016 12th International Conference on Network and Service Management (CNSM)","volume":"66 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126403387","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

Identifying resources for cloud garbage collection 识别用于云垃圾收集的资源

2016 12th International Conference on Network and Service Management (CNSM) Pub Date : 2016-10-01 DOI: 10.1109/CNSM.2016.7818426

Zhiming Shen, Christopher C. Young, Sai Zeng, K. Murthy, Kun Bai

{"title":"Identifying resources for cloud garbage collection","authors":"Zhiming Shen, Christopher C. Young, Sai Zeng, K. Murthy, Kun Bai","doi":"10.1109/CNSM.2016.7818426","DOIUrl":"https://doi.org/10.1109/CNSM.2016.7818426","url":null,"abstract":"Infrastructure as a Service (IaaS) clouds provide users with the ability to easily and quickly provision servers. A recent study found that one in three data center servers continues to consume resources without producing any useful work. A number of techniques have been proposed to identify such unproductive instances. However, those approaches adopt the strategy to identify idle cloud instances based on resource utilization. Resource utilization as indicator alone could be misleading, which is especially true for enterprise cloud environment. In this paper, we present Pleco, a tool that detects unproductive instances in IaaS clouds. Pleco captures dependency information between users and cloud instances by constructing a weighted reference model based on application knowledge. To handle cases of insufficient application knowledge, Pleco also supplements its dependency results with a machine learning model trained on resource utilization data. Pleco gives a confidence level and justification for each identified unproductive instances. Cloud administrators can then take different actions according to the information provided by Pleco. Pleco is lightweight and requires no modification to existing applications.","PeriodicalId":334604,"journal":{"name":"2016 12th International Conference on Network and Service Management (CNSM)","volume":"2019 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126028900","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

Energy-aware quality adaptation for mobile video streaming 移动视频流的能量感知质量适应

2016 12th International Conference on Network and Service Management (CNSM) Pub Date : 2016-10-01 DOI: 10.1109/CNSM.2016.7818427

Stefano Petrangeli, Patrick Van Staey, Maxim Claeys, T. Wauters, F. Turck

{"title":"Energy-aware quality adaptation for mobile video streaming","authors":"Stefano Petrangeli, Patrick Van Staey, Maxim Claeys, T. Wauters, F. Turck","doi":"10.1109/CNSM.2016.7818427","DOIUrl":"https://doi.org/10.1109/CNSM.2016.7818427","url":null,"abstract":"HTTP Adaptive Streaming (HAS) is becoming the de-facto standard for video streaming services over the Internet. In HAS, each video is segmented and stored in different qualities. Rate adaptation heuristics, deployed at the client, allow the most appropriate quality level to be dynamically requested based on the current network conditions, in order to achieve a continuous playout. Due to the ability of HAS protocols to dynamically adapt to bandwidth fluctuations, they are especially suited for the delivery of multimedia content in mobile environments. However, current HAS solutions do not take the battery lifetime into account, which is a typical issue for mobile devices. In this paper, we therefore propose an energy-aware heuristic for HAS. We first present a measurement study to identify and quantify the main factors influencing the battery lifetime on mobile devices. We then develop a heuristic based on these findings, which optimizes both the quality of experience and the battery consumption of a video streaming session. Particularly, we found that the video resolution and display size have the highest impact on the battery lifetime and that our energy-aware heuristic can prolong a streaming session with up to 13%, compared to a standard HAS heuristic. This result represents a consistent improvement for the overall user experience on battery-constrained devices.","PeriodicalId":334604,"journal":{"name":"2016 12th International Conference on Network and Service Management (CNSM)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127172617","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: 7