Abstract-The Border Gateway Protocol (BGP) maintains inter-domain routing information by announcing and withdrawing IP prefixes, possibly resulting in temporary prefix unreachability. Prefix availability observed from different vantage points in the Internet can be lower than standards promised by Service Level Agreements (SLAs).In this paper, we develop a framework for predicting long-term prefix availability, given short-duration prefix information from publicly available BGP routing databases. We compare three prediction models, and find that bagged decision trees perform the best when predicting for long future durations, whereas a simple model works well for short prediction durations. We show that mean time to failure and to recovery outperform past availability in terms of their importance for predicting availability for long durations. We also find that predictability is higher in the year 2009, compared to four years earlier. Our models allow ISPs to adjust BGP routing policies if predicted availability is low, and the models are useful for cloud computing systems, P2P, and VoIP applications.
Abstract-Cloud-computing systems are rapidly gaining momentum, providing flexible alternatives to many services. We study the Domain Name System (DNS) service, used to convert host names to IP addresses, which has historically been provided by a client's Internet Service Provider (ISP). With the advent of cloud-based DNS providers such as Google and OpenDNS, clients are increasingly using these DNS systems for URL and other name resolution.Performance degradation with cloud-based DNS has been reported, especially when accessing content hosted on highly distributed CDNs like Akamai. In this work, we investigate this problem in depth using Akamai as the content provider and Google DNS as the cloud-based DNS system. We demonstrate that the problem is rooted in the disparity between the number and location of servers of the two providers, and develop a new technique for geolocating data centers of cloud providers. Additionally, we explore the design space of methods for cloudbased DNS systems to be effective. Client-side, cloud-side, and hybrid approaches are presented and compared, with the goal of achieving the best client-perceived performance. Our work yields valuable insight into Akamai's DNS system, revealing previously unknown features.
Abstract-Data dissemination strategies and communication protocols that minimize the use of energy can significantly prolong the lifetime of a sensor network. Data-centric dissemination strategies seek energy efficiency by employing short metadata descriptions in advertisements (ADVs) of the availability of data, short requests (REQs) to obtain the data by nodes that are interested in it, and data transmissions (DATA) to deliver data to the requesting nodes. An important decision in this process is whether the DATA transmission should be made at full power in broadcast mode or at low power in multi-hop unicast mode. The determining factor is shown in this paper to be the fraction of nodes that are interested in the DATA, as shown by the number of REQs that are generated. Closed form expressions for this critical fraction of interested nodes is derived when the nodes have no memory or infinite memory for state information and when transmissions are reliable and not reliable. These results can be used during both the design and operation of the network to increase energy efficiency and network longevity.
a b s t r a c tThe Border Gateway Protocol (BGP) maintains inter-domain routing information by announcing and withdrawing IP prefixes. These routing updates can cause prefixes to be unreachable for periods of time, reducing prefix availability observed from different vantage points on the Internet. The observed prefix availability values may not meet the standards promised by Service Level Agreements (SLAs).In this paper, we develop a framework for predicting long-term availability of prefixes, given short-duration prefix information from publicly available BGP routing databases like RouteViews, and prediction models constructed from information about other Internet prefixes. We compare three prediction models and find that machine learning-based prediction methods outperform a baseline model that predicts the future availability of a prefix to be the same as its past availability. Our results show that mean time to failure is the most important attribute for predicting availability. We also quantify how prefix availability is related to prefix length and update frequency. Our prediction models achieve 82% accuracy and 0.7 ranking quality when predicting for a future duration equal to the learning duration. We can also predict for a longer future duration, with graceful performance reduction. Our models allow ISPs to adjust BGP routing policies if predicted availability is low, and are generally useful for cloud computing systems, content distribution networks, P2P, and VoIP applications.
Abstract-The reachability of IP address prefixes exhibits significant fluctuations due to changes in both physical connectivity and ISP routing policies. In the late 1990s, Labovitz et al. performed an extensive study of inter-domain path stability by analyzing BGP routing data. To reduce the noise in the BGP data, e.g., transient updates during route convergence, they applied several filters to preprocess the raw BGP data.In this work, we investigate prefix reachability as advertised by BGP, while revisiting the preprocessing filter design problem. We show that the reachability analysis results are highly sensitive to the specific filters applied and the parameters that control the strength of the filters. In particular, we compute the Mean Time to Failure and Recovery (MTTF and MTTR) as well as the upto-downtime ratios of prefixes, and find that these can fluctuate by a factor of 10 by varying the filter parameters. We analyze the impact of recent fiber cuts in the Mediterranean sea and the Middle East, and study prefix reachability during a nine-month period in 2007 to evaluate the general health of the Internet 1 .
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