Nasim Beigi Mohammadi, Hamzeh Khazaei, Mark Shtern, C. Barna, Marin Litoiu
{"title":"Adaptive service management for cloud applications using overlay networks","authors":"Nasim Beigi Mohammadi, Hamzeh Khazaei, Mark Shtern, C. Barna, Marin Litoiu","doi":"10.23919/INM.2017.7987302","DOIUrl":"https://doi.org/10.23919/INM.2017.7987302","url":null,"abstract":"This paper presents an adaptive service management mechanism that maintains service level agreement through use of overlay networks that are deployed over the cloud provider network. The application autonomic manager strives to maintain the SLA without provisioning new resources for as long as possible. Through continuous monitoring and analysis, autonomic manager uses software defined networking (SDN) to dynamically apply policies to the flows of requests that travel through the application components. We implement and evaluate the proposed method on a hybrid cloud environment. Through extensive experiments, we show that the management mechanism can successfully maintain the SLA of services while it avoids provisioning extra resources which is the common approach in cloud.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133575126","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}
{"title":"A traffic classification approach based on characteristics of subflows and ensemble learning","authors":"Changyu Wang, X. Guan, Tao Qin","doi":"10.23919/INM.2017.7987336","DOIUrl":"https://doi.org/10.23919/INM.2017.7987336","url":null,"abstract":"Recently, network traffic classification has attracted a great deal of attention among researchers. In this paper, we proposed a traffic classification approach based on characteristics of subflows and ensemble learning. Aiming at neutralization of unstable network environment as well as taking advantage of ensemble learning, we divided the traffic flows into different subflows in order to reduce the affection of time. Moreover, we develop truncation method on flows for real-time processing and an aggregation machine learning method based on accuracy of each classifier to different applications. Finally, the experimental results based on actual traffic traces collected from the campus network of Xian Jiaotong University verify the effectiveness of our methods.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"362 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115941334","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}
{"title":"Distributed Management Information Models","authors":"Liam Fallon, J. Keeney, S. Meer","doi":"10.23919/INM.2017.7987306","DOIUrl":"https://doi.org/10.23919/INM.2017.7987306","url":null,"abstract":"The formal structure of information models and the controlled manner of accessing and changing such models brings both flexibility and control when managing network elements. However, keeping information models synchronized and consistent across network elements and management systems is a challenging task. Today this problem is exasperated with the advent of ephemeral network functions and elements and also by the need for distributed scalable cooperating management functions running in containerized cloud deployments.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114849592","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}
D. Tuncer, Tom Sherborne, M. Charalambides, G. Pavlou
{"title":"CacheMAsT: Cache Management Analysis and Visualization Tool","authors":"D. Tuncer, Tom Sherborne, M. Charalambides, G. Pavlou","doi":"10.23919/INM.2017.7987391","DOIUrl":"https://doi.org/10.23919/INM.2017.7987391","url":null,"abstract":"Recent approaches have proposed to empower Internet Service Providers (ISPs) with caching capabilities that can allow them to implement their own cache management strategies and as such have better control over the utilization of their resources. In this demo paper, we present CacheMAsT (Cache Management Analysis and Visualization Tool), a decision support tool to visualize the configuration and performance of in-network cache management approaches. CacheMAsT is aimed at assisting researchers and engineers in analyzing and evaluating the different factors that can affect the performance of a cache management strategy and ultimately decide on the optimal approach to apply.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121766416","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}
L. C. Costa, A. Vieira, E. B. Silva, D. Macedo, Geraldo Gomes, L. H. A. Correia, L. Vieira
{"title":"Performance evaluation of OpenFlow data planes","authors":"L. C. Costa, A. Vieira, E. B. Silva, D. Macedo, Geraldo Gomes, L. H. A. Correia, L. Vieira","doi":"10.23919/INM.2017.7987314","DOIUrl":"https://doi.org/10.23919/INM.2017.7987314","url":null,"abstract":"The decoupling of data and control planes of network switches is the main characteristic of Software Defined Networks. The OpenFlow (OF) protocol implements this concept and it is found today in various off-the-shelf equipment. Despite being widely employed in industry and research there is no systematic evaluation of OF data plane performance in the literature. In this paper we evaluate the performance and maturity of the main features of OF 1.0 on nine hardware and software switches. Results show that the performance varies significantly among implementations. For instance, packet delays vary by one order of magnitude among the evaluated switches, while the packet size does not impact the performance of OF switches.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129964370","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}
{"title":"Online learning and adaptation of network hypervisor performance models","authors":"Christian Sieber, A. Obermair, W. Kellerer","doi":"10.23919/INM.2017.7987462","DOIUrl":"https://doi.org/10.23919/INM.2017.7987462","url":null,"abstract":"Software Defined Networking (SDN) paved the way for a logically centralized entity, the SDN controller, to excerpt near real-time control over the forwarding state of a network. Network hypervisors are an in-between layer to allow multiple SDN controllers to share this control by slicing the network and giving each controller the power over a part of the network. This makes network hypervisors a critical component in terms of reliability and performance. At the same time, compute virtualization is ubiquitous and may not guarantee statically assigned resources to the network hypervisors. It is therefore important to understand the performance of network hypervisors in environments with varying compute resources. In this paper we propose an online machine learning pipeline to synthesize a performance model of a running hypervisor instance in the face of varying resources. The performance model allows precise estimations of the current capacity in terms of control message throughput without time-intensive offline benchmarks. We evaluate the pipeline in a virtual testbed with a popular network hypervisor implementation. The results show that the proposed pipeline is able to estimate the capacity of a hypervisor instance with a low error and furthermore is able to quickly detect and adapt to a change in available resources. By exploring the parameter space of the learning pipeline, we discuss its characteristics in terms of estimation accuracy and convergence time for different parameter choices and use cases. Although we evaluate the approach with network hypervisors, our work can be generalized to other latency-sensitive applications with similar characteristics and requirements as network hypervisors.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130093070","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}
{"title":"On non-parametric models for detecting outages in the mobile network","authors":"Eric Falk, R. Camino, R. State, V. Gurbani","doi":"10.23919/INM.2017.7987448","DOIUrl":"https://doi.org/10.23919/INM.2017.7987448","url":null,"abstract":"The wireless/cellular communications network is composed of a complex set of interconnected computation units that form the mobile core network. The mobile core network is engineered to be fault tolerant and redundant; small errors that manifest themselves in the network are usually resolved automatically. However, some errors remain latent, and if discovered early enough can provide warnings to the network operator about a pending service outage. For mobile network operators, it is of high interest to detect these minor anomalies near real-time. In this work we use performance data from a 4G-LTE network carrier to train two parameter-free models. A first model relies on isolation forests, and the second is histogram based. The trained models represent the data characteristics for normal periods; new data is matched against the trained models to classify the new time period as being normal or abnormal. We show that the proposed methods can gauge the mobile network state with more subtlety than standard success/failure thresholds used in real-world networks today.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130808630","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}
T. Zinner, Stefan Geissler, Fabian Helmschrott, Valentin Burger
{"title":"Comparison of the initial delay for video playout start for different HTTP-based transport protocols","authors":"T. Zinner, Stefan Geissler, Fabian Helmschrott, Valentin Burger","doi":"10.23919/INM.2017.7987428","DOIUrl":"https://doi.org/10.23919/INM.2017.7987428","url":null,"abstract":"This paper details a measurement study on the impact of different HTTP-based application layer protocols, namely HTTP/1, HTTP/2 and QUIC, on video streaming performance. In this context we evaluate the influence on the initial delay until video playout is started using the live version of the YouTube platform. Furthermore, we evaluate how different network parameters, i.e. bandwidth, RTTs and packet loss influence the different protocols. This work presents an overview over the characteristics of the compared protocols and presents a detailed measurement methodology on how the data has been obtained. Finally, the observed data is evaluated in the context of YouTube video streaming.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126069501","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}
Dries Pauwels, Jeroen van der Hooft, Stefano Petrangeli, T. Wauters, D. D. Vleeschauwer, F. Turck
{"title":"A Web-based framework for fast synchronization of live video players","authors":"Dries Pauwels, Jeroen van der Hooft, Stefano Petrangeli, T. Wauters, D. D. Vleeschauwer, F. Turck","doi":"10.23919/INM.2017.7987322","DOIUrl":"https://doi.org/10.23919/INM.2017.7987322","url":null,"abstract":"The increased popularity of social media and mobile devices has radically changed the way people consume multimedia content online. As an example, users can experience the same event (e.g. a sports event or a concert) together using social media, even if they are not in the same physical location. Moreover, the introduction of the HTTP Adaptive Streaming principle has made it possible to deliver video over the best-effort Internet with consistent quality, even for mobile devices. One of the challenges within this context is the synchronization of multimedia playback among geographically distributed clients. To solve this issue, we propose a Web-based framework which allows to synchronize the playback of different clients. We also present a novel hybrid approach for adaptive streaming to allow fast synchronization among different clients, which relies on HTTP/2's server push feature in combination with sub-second video segments. In this paper, we detail the proposed framework and provide a comprehensive analysis of its performance. Experiments show that the novel hybrid approach can reduce synchronization time with 19.4% compared to standard adaptive streaming over HTTP/1.1 when bandwidth is limited to 2.5 Mb/s and an RTT of 150 ms. The gain increases even more when a higher throughput is available. The obtained results entail that the proposed framework can provide quality of experience for all users watching online video together.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126353478","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}
Qinglei Qi, Wendong Wang, Xiangyang Gong, Xirong Que
{"title":"An analytical model for combined SDN Forwarding Element","authors":"Qinglei Qi, Wendong Wang, Xiangyang Gong, Xirong Que","doi":"10.23919/INM.2017.7987332","DOIUrl":"https://doi.org/10.23919/INM.2017.7987332","url":null,"abstract":"Recent studies have shown that the flow table size of hardware SDN switch cannot match the number of concurrent flows. Combined SDN Forwarding Element (CFE), which comprises software switch and hardware switch, becomes an alternative approach for tackling this problem. Because software switch has lower lookup speed than hardware switch, different proportions of traffic allocated to software switches in CFE have different effects on the delay bounds of all flows entering CFE. As delay-guarantee is a nontrivial task for network providers, especially with the increasing number of delay-sensitive applications, a model to analyze the delay bound given a flow allocation in CFE is important. With the one-to-one correspondence between flow allocation and rules placement solution, the analytical model can be used to evaluate and compare rules placement solutions and provide a basis for designing better rules placement solution in CFE. In this paper, we propose an analytical model for CFE based on network calculus, and then validate this model through simulations in NS-3.","PeriodicalId":119633,"journal":{"name":"2017 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126907608","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}