12315543
On network-aware clustering of Web clients
Being able to identify the groups of clients that are responsible for a significant portion of a Web site's requests can be helpful to both the Web site and the clients. In a Web application, it is beneficial to move content closer to groups of clients that are responsible for large subsets of requests to an origin server. We introduce clusters---a grouping of clients that are close together topologically and likely to be under common administrative control. We identify clusters using a ``network-aware" method, based on information available from BGP routing table snapshots.
15532439
Scalable and accurate identification of AS-level forwarding paths
Traceroute is used heavily by network operators and researchers to identify the IP forwarding path from a source to a destination. In practice, knowing the autonomous system (AS) associated with each hop in the path is also quite valuable. In previous work we showed that the IP-to-AS mapping extracted from BGP routing tables is not sufficient for determining the AS-level forwarding paths. By comparing BGP and traceroute AS paths from multiple vantage points, Z. Morley Mao et al. (2003) proposed heuristics that identify the root causes of the mismatches and fix the inaccurate IP-to-AS mappings. These heuristics, though effective, are labor-intensive and mostly ad hoc. This paper proposes a systematic way to construct accurate IP-to-AS mappings using dynamic programming and iterative improvement. Our algorithm reduces the initial mismatch ratio of 15% between BGP and traceroute AS paths to 5% while changing only 2.9% of the assignments in the initial IP-to-AS mappings. This is in contrast to the results of Z. Morley Mao et al. (2003), where 10% of the assignments were modified and the mismatch ratio was only reduced to 9%. We show that our algorithm is robust and can yield near-optimal results even when the initial mapping is corrupted or when the number of probing sources or destinations is reduced. Our work is a key step towards building a scalable and accurate AS-level traceroute tool
2808817
BGP routing stability of popular destinations
The Border Gateway Protocol (BGP) plays a crucial role in the delivery of traffic in the Internet. Fluctuations in BGP routes cause degradation in user performance, increased processing load on routers, and changes in the distribution of traffic load over the network. Although earlier studies have raised concern that BGP routes change quite often, previous work has not considered whether these routing fluctuations affect a significant portion of the traffic. This paper shows that the small number of popular destinations responsible for the bulk of Internet traffic have remarkably stable BGP routes. The vast majority of BGP instability stems from a small number of unpopular destinations. We draw these conclusions from a joint analysis of BGP update messages and flow-level traffic measurements from AT&T's IP backbone. In addition, we analyze the routing stability of destination prefixes corresponding to the NetRating's list of popular Web sites using the update messages collected by the RouteViews and RIPE-NCC servers. Our results suggest that operators can engineer their networks under the assumption that the BGP advertisements associated with most of the traffic are reasonably stable.
584549
A measurement study on the impact of routing events on end-to-end internet path performance
Extensive measurement studies have shown that end-to-end Internet path performance degradation is correlated with routing dynamics. However, the root cause of the correlation between routing dynamics and such performance degradation is poorly understood. In particular, how do routing changes result in degraded end-to-end path performance in the first place? How do factors such as topological properties, routing policies, and iBGP configurations affect the extent to which such routing events can cause performance degradation? Answers to these questions are critical for improving network performance.In this paper, we conduct extensive measurement that involves both controlled routing updates through two tier-1 ISPs and active probes of a diverse set of end-to-end paths on the Internet. We find that routing changes contribute to end-to-end packet loss significantly. Specifically, we study failover events in which a link failure leads to a routing change and recovery events in which a link repair causes a routing change. In both cases, it is possible to experience data plane performance degradation in terms of increased long loss burst as well as forwarding loops. Furthermore, we find that common routing policies and iBGP configurations of ISPs can directly affect the end-to-end path performance during routing changes. Our work provides new insights into potential measures that network operators can undertake to enhance network performance.
14749331
Early measurements of a cluster-based architecture for P2P systems
Peer-to-peer applications such as Napster [4], Freenet [1], and Gnutella [2], [7] have gained much attention recently. These applications are mainly designed and used for largescale sharing of MP3 files. In such systems, end-hosts self-organize into an overlay network and share content with each other. Compared to the traditional client-server model, files are served in a distributed manner and replicated among the network on demand. Since hosts participating in peer-to-peer (P2P) networks also devote some computing resources, such systems scale with the number of hosts in terms of hardware, bandwidth, and disk space. With the wide deployment of P2P applications, the P2P traffic is becoming a growing portion of the Internet traffic. There has been very little examination of P2P traffic patterns and how they differ from traditional service models. Studying and understanding P2P traffic is thus important to provide efficient application-level content location and routing within the network. The existing applications use their own approach to do content location and routing and none of them are scalable. Napster uses a centralized server to locate content, while Gnutella clients broadcast queries to all their neighbors. [8] discusses the query locality observed in Gnutella traces and suggests caching as a short-term approach to increase Gnutella’s scalability. Recent designs such as CAN [5], Chord [9], Pastry [6], and Tapestry [10] propose distributed indexing schemes based on hashing to locate content. These systems assume a flat content delivery mesh. Each object’s location is stored at one or more nodes selected deterministically by a uniform hash function; queries for the object will be routed incrementally to the node. Although hash functions can help locate content deterministically, they lack the flexibility of keyword searching—a useful operation to find content without prior knowledge of exact object names. There is no real deployment at present and thus no measurement information is available for understanding the usability and scalability of
7334644
Analyzing peer-to-peer traffic across large networks
The use of peer-to-peer (P2P) applications is growing dramatically, particularly for sharing large video/audio files and software. In this paper, we analyze P2P traffic by measuring flow-level information collected at multiple border routers across a large ISP network, and report our investigation of three popular P2P systems-FastTrack, Gnutella, and Direct-Connect. We characterize the P2P traffic observed at a single ISP and its impact on the underlying network. We observe very skewed distribution in the traffic across the network at different levels of spatial aggregation (IP, prefix, AS). All three P2P systems exhibit significant dynamics at short time scale and particularly at the IP address level. Still, the fraction of P2P traffic contributed by each prefix is more stable than the corresponding distribution of either Web traffic or overall traffic. The high volume and good stability properties of P2P traffic suggests that the P2P workload is a good candidate for being managed via application-specific layer-3 traffic engineering in an ISP's network.
1358360
A Web service for efficient ontology comparison
In this paper, we develop a Web service for ontology comparison based on a novel senses refinement algorithm, which builds senses sets to represent the semantics of the input ontologies. The senses refinement algorithm converts the measurement of ontology difference into simple set operations based on set theory, thus ensures the efficiency and accuracy of the ontology comparison. We believe our Web service is the first available online measurement tool for ontology comparison.
41575427
Ranking Web News Via Homepage Visual Layout and Cross-Site Voting
Reading news is one of the most popular activities when people surf the internet. As too many news sources provide independent news information and each has its own preference, detecting unbiased important news might be very useful for users to keep up to date with what are happening in the world. In this paper we present a novel method to identify important news in web environment which consists of diversified online news sites. We observe that a piece of important news generally occupies visually significant place in some homepage of a news site and import news event will be reported by many news sites. To explore these two properties, we model the relationship between homepages, news and latent events by a tripartite graph, and present an algorithm to identify important news in this model. Based on this algorithm, we implement a system TOPSTORY to dynamically generate homepages for users to browse important news reports. Our experimental study indicates the effectiveness of proposed approach.
206566936
Approximate Tree Matching in the Presence of Variable Length Don't Cares
Ordered labeled trees are trees in which the sibling order matters. This paper presents algorithms for three problems having to do with approximate matching for such trees with variable length don′t cares (VLDCs). In strings, a VLDC symbol in the pattern may substitute for zero or more symbols in the data string. For example, if "com∗er" is the pattern, then the "∗" would substitute for the substring "put" when matching the data string "computer." Approximate VLDC matching in strings means that after the best possible substitution, the pattern still need not be the same as the data string for a match to be allowed. For example, "com∗er" matches "counter" within distance one (representing the cost of removing the "m" from "com∗er" and having the "∗" substitute for "unt"). We generalize approximate VLDC string matching to three algorithms for approximate VLDC matching on trees. The time complexity of our algorithms is O(|P| × |D| × min(depth(P), leaves(P)) × min(depth(D), leaves(D))) (where |P| and |D| are the number of nodes respectively of the pattern P and the data tree D), the same as for the best approximate tree matching algorithm without VLDCs previously reported.
21940463
A hybrid method for unconstrained handwritten numeral recognition by combining structural and neural "gas" classifiers
Abstract This paper presents a hybrid method for handwritten numeral recognition that combines two compensatory recognition algorithms by analysing their performance for several aspects. The skeleton-based structural recognition algorithm employed in this method is robust under distortion but sensitive to noise and flaws. On the other hand, the neural network classifier, which uses scaled binary images as features and the neural “gas” model for classification, is relatively immune to noise and flaws but sensitive to distortion. The different performances of the two algorithms for broken, connected or slanted numerals, and the measurement-level decision provided by the neural network are detected and combined with different strategies to develop matching rules for each recognition method. Five combination methods based on performance analysis are developed to meet different requirements. As the two algorithms have fairly compensatory properties, the proposed method improves the recognition rate and reliability by exploiting the advantages and avoiding the weaknesses of each classifier. The experimental results from a large set of data show the efficiency and robustness of the proposed method.
12107864
Kernel Trick Embedded Gaussian Mixture Model
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter estimation algorithm for GMM in feature space. Kernel GMM could be viewed as a Bayesian Kernel Method. Compared with most classical kernel methods, the proposed method can solve problems in probabilistic framework. Moreover, it can tackle nonlinear problems better than the traditional GMM. To avoid great computational cost problem existing in most kernel methods upon large scale data set, we also employ a Monte Carlo sampling technique to speed up kernel GMM so that it is more practical and efficient. Experimental results on synthetic and real-world data set demonstrate that the proposed approach has satisfing performance.