Pub Date : 2005-05-15DOI: 10.1109/E2EMON.2005.1564476
P. Varga, Gergely Kún
This paper introduces a new approach for determining bottleneck link locations in a network. The considered measurement model is passive monitoring of a backbone link. We analyze the properties of packet interarrival time (PIT) distribution functions of network segments and make decisions whether the extracted properties of a link suggest bottleneck behavior or not. The correlation between bottleneck behavior and packet interarrival time distribution is demonstrated through simulations featuring tighter and tighter bottleneck connections. Locating shared bottlenecks with passive monitoring requires effective metrics for distinguishing seriously congested links from normal or underutilized connections. The current paper presents the third and fourth central moments (skewness and kurtosis, respectively) of PIT distribution as possible and promising metrics for bottleneck detection. According to the simulation results, kurtosis of PITs is found to be a powerful measure of bottleneck behavior. This is further validated by investigation of real measurement data.
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Pub Date : 2005-05-15DOI: 10.1109/E2EMON.2005.1564466
K. Ravindran
The paper describes a management-oriented model for cost-effective 'data connectivity' provisioning between the peer entities of a networked multimedia application. The 'connectivity' service provider (SP) may maintain multiple protocol mechanisms to support its clientele: ranging between bandwidth-reserved paths to bandwidth-shared paths. Client applications prescribe the required QoS obligations through a service interface, with the SP instantiating one of the protocol modules with appropriate parameters to meet the QoS requirements. The model allows dynamic switching from one protocol module to another, based on a notion of cost associated with bandwidth usage by the network infrastructure for a given level of QoS offering. The management functions of SP monitor the changes and/or outages in network bandwidth in a dynamic setting, and map them into connectivity costs incurred by the selected protocol mechanism. The paper describes the signaling required between the SP and network infrastructure to install appropriate policy functions that can make the connectivity provisioning cost-optimal.
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Pub Date : 2005-05-15DOI: 10.1109/E2EMON.2005.1564469
C. Man, G. Hasegawa, M. Murata
We previously proposed a new version of TCP, called inline measurement TCP (ImTCP), in Cao Le Thanh Man et al. (2004). The ImTCP sender adjusts the transmission intervals of data packets and then utilizes the arrival intervals of ACK packets for available bandwidth estimation. This type of active measurement is preferred because the obtained results are as accurate as those of other conventional types of active measurement, even though no extra probe traffic is injected onto the network. In the present research, we combine a new capacity measurement function with ImTCP in order to enable simultaneous measurement of both capacity and available bandwidth in ImTCP. The capacity measurement algorithm is a new packet-pair-based measurement technique that utilizes the estimated available bandwidth values for capacity calculation. This new algorithm promises faster measurement than current packet-pair-based measurement algorithms for various situations and works well for high-load networks, in which current algorithms do not work properly. Moreover, the new algorithm provides a confidence interval for the measurement result.
我们之前在Cao Le Thanh Man et al.(2004)中提出了一个新版本的TCP，称为内联测量TCP (ImTCP)。ImTCP发送方调整数据包的传输间隔，然后根据ACK报文到达的间隔估计可用带宽。这种类型的主动测量是首选的，因为获得的结果与其他传统类型的主动测量一样准确，即使没有向网络注入额外的探针流量。在本研究中，我们将一个新的容量测量功能与ImTCP相结合，以便在ImTCP中同时测量容量和可用带宽。容量测量算法是一种新的基于包对的测量技术，利用估计的可用带宽值进行容量计算。这种新算法比当前基于分组对的测量算法在各种情况下的测量速度更快，并且适用于当前算法不能正常工作的高负载网络。此外，该算法还为测量结果提供了置信区间。
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Pub Date : 2005-05-15DOI: 10.1109/E2EMON.2005.1564471
P. Calyam, Chang-Gun Lee, Phani Kumar Arava, Dima Krymskiy, Duhee Lee
In order to satisfy and maintain service level agreements (SLAs), which demand high network availability and good network health, ISPs have started instrumenting their networks with network measurement infrastructures (NMIs) that are composed of dedicated measurement servers. Active measurements are frequently used in NMIs to regularly monitor network health and analyze the experience of end-user application traffic traversing the network. However, active measurements initiated by measurement servers need to be regulated. Unregulated active measurement traffic can cause an unpredictable negative impact on the actual application traffic. Also, running simultaneous conflicting active measurements on measurement servers could result in misleading reports of network performance. In this paper, we describe our active measurements scheduling framework called "OnTimeMeasure" that allows ISPs to regulate the amount of active measurement traffic injected into the network and also prevents conflicts in ongoing active measurements between measurement servers. OnTimeMeasure provides a simple scripting language interface to specify various measurement requirements such as physical topology of measurement server clusters, periodicity of the measurements, and properties of measurement tools. For a given measurement requirements script, OnTimeMeasure uses an efficient heuristic bin-packing algorithm to generate measurement timetables for orchestrating active measurements for a network involving multiple measurement servers, each hosting multiple measurement tools.
{"title":"Ontimemeasure: a scalable framework for scheduling active measurements","authors":"P. Calyam, Chang-Gun Lee, Phani Kumar Arava, Dima Krymskiy, Duhee Lee","doi":"10.1109/E2EMON.2005.1564471","DOIUrl":"https://doi.org/10.1109/E2EMON.2005.1564471","url":null,"abstract":"In order to satisfy and maintain service level agreements (SLAs), which demand high network availability and good network health, ISPs have started instrumenting their networks with network measurement infrastructures (NMIs) that are composed of dedicated measurement servers. Active measurements are frequently used in NMIs to regularly monitor network health and analyze the experience of end-user application traffic traversing the network. However, active measurements initiated by measurement servers need to be regulated. Unregulated active measurement traffic can cause an unpredictable negative impact on the actual application traffic. Also, running simultaneous conflicting active measurements on measurement servers could result in misleading reports of network performance. In this paper, we describe our active measurements scheduling framework called \"OnTimeMeasure\" that allows ISPs to regulate the amount of active measurement traffic injected into the network and also prevents conflicts in ongoing active measurements between measurement servers. OnTimeMeasure provides a simple scripting language interface to specify various measurement requirements such as physical topology of measurement server clusters, periodicity of the measurements, and properties of measurement tools. For a given measurement requirements script, OnTimeMeasure uses an efficient heuristic bin-packing algorithm to generate measurement timetables for orchestrating active measurements for a network involving multiple measurement servers, each hosting multiple measurement tools.","PeriodicalId":354965,"journal":{"name":"Workshop on End-to-End Monitoring Techniques and Services, 2005.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132851331","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}
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