17168623
Traffic classification for application specific peering
Peer-to-Peer (P2P) applications [4], [6], [2], [3] have increased traffic significantly. We propose application specific peering that allows searches for a resource (using existing or modified P2P protocols) to be directed to a copy of resource on an ISP's network, using a novel technique that automatically classifies traffic (shown in Fig 1) as belonging to an ISP, its customers, peers, or their customers. We examined a large amount of traffic belonging to three popular P2P protocols and used a graph transformation to detect connected components. We partition traffic in each component into signaling and data sections based on request/response sizes of P2P protocols and extract high traffic volume (by bytes) entities by examining large connected components in the graph. We discuss the important components of our traffic classification system here. We analyzed router-level data from multiple Internet Gateway Routers (IGRs) across AT&T IP backbone using Cisco's NetFlow services. Note that statistics are from a subset of IGRs at some AT&T's peering links. They are not representative of overall traffic pattem on AT&T IP backbone. We examined DirectConnect[2], Gnutella[3], and FastTrack[4], extracting records that matched the default application ports (source or destina• tion, 411/412, 6346/6347, and 1214 (FastTrack) respectively), involving TCP traffic. Data was gathered over three separate months in 2001, each lasting 5-7 days. The number of netflow records varies from a low of 0.5M (DirectConnect) to a high
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.
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
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
9192804
Efficient and robust streaming provisioning in VPNs
Today, most large companies maintain virtual private networks (VPNs) to connect their remote locations into a single secure network. VPNs can be quite large covering more than 1000 locations and in most cases use standard Internet protocols and services. Such VPNs are implemented using a diverse set of technologies such as Frame Relay, MPLS, or IPSEC to achieve the goal of privacy and performance isolation from the public Internet.Using VPNs to distribute live content has recently received tremendous interest. For example, a VPN could be used to broadcast a CEO-employee town hall meeting. To distribute this type of content economically without overloading the network, the deployment of streaming caches or splitters is most likely required.In this paper, we address the problem of optimally placing such streaming splitters or caches to broadcast to a given set of VPN endpoints under the constraints typically found within a VPN. In particular, we introduce an efficient algorithm with complexity O(V), V being the number of routers in the VPN. This guarantees the optimal cache placement if interception is used for redirection. We prove that the general problem is NP-hard and introduce multiple heuristics for efficient and robust cache placement suitable under different constraints. At the expense of increased implementation complexity, each heuristic solution provides additional saving in the number of caches required. We evaluate proposed solutions using extensive simulations. In particular, we show our flow-based solution is very close to the optimal.
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.
16255139
Narrowband interference suppression in time-hopping impulse radio ultra-wideband communications
Ultra-wideband (UWB) technology has been considered an innovative solution for future short-range high-speed wireless communications. Interference suppression is important for the UWB devices to operate over spectrum occupied by narrowband systems. In this paper, the use of a notch filter in time-hopping impulse radio (TH-IR) for UWB communication is considered, where a Gaussian monopulse is employed with pulse position modulation. Lognormal channel fading is assumed, and a complete analytical framework is provided for the performance evaluation of using a transversal-type notch filter to reject narrowband interference (NBI). A closed-form expression of bit-error probability is derived, and the numerical results show that the use of a notch filter can improve the system performance significantly. Furthermore, a performance comparison between TH-IR and multicarrier code-division multiple-access (MC-CDMA) UWB systems is made under the conditions of the same transmit power, the same data rate, and the same bandwidth. It is shown that in the presence of NBI, the TH-IR system and MC-CDMA system achieve similar performance when both use a notch filter
14470248
MosaicShape: stochastic region grouping with shape prior
A method that combines shape-based object recognition and image segmentation is proposed for shape retrieval from images. Given a shape prior represented in a multi-scale curvature form, the proposed method identifies the target objects in images by grouping oversegmented image regions. The problem is formulated in a unified probabilistic framework, and object segmentation and recognition are accomplished simultaneously by a stochastic Markov Chain Monte Carlo (MCMC) mechanism. Within each sampling move during the simulation process, probabilistic region grouping operations are influenced by both the image information and the shape similarity constraint. The latter constraint is measured by a partial shape matching process. A generalized cluster sampling algorithm is presented in A. Barbu and S. Zhu (2003), combined with a large sampling jump and other implementation improvements, and greatly speeds up the overall stochastic process. The proposed method supports the segmentation and recognition of multiple occluded objects in images. Experimental results are provided for both synthetic and real images.
15313247
Performance of a MAC protocol for WDM networks with on-line scheduling
This paper investigates the performance of media access protocols based on on-line scheduling for an optically connected star-coupled system with wavelength division multiple access channels. Hybrid access protocols combining reservation and pre-allocation of receiver channels have been previously proposed. Transmission consisted of a reservation phase followed by a data phase. Each node was allowed to place a reservation for one WDM channel. This protocol is extended in this paper by allowing reservations on multiple channels and using simple on-line scheduling algorithms. Existing scheduling algorithms (all are off-line) for similar reservation problems tend to have high implementation and computational complexity. We require that scheduling algorithms be real-time and amenable to hardware implementation. The performance of the extended protocol incorporating two simple on-line scheduling algorithms is presented in this paper. We show that the slight increased computational overhead with scheduling is justified by reduced packet latency and higher utilization, especially for client-server traffic.
3104346
Selecting discriminant eigenfaces for face recognition
In realistic face recognition applications, such as surveillance photo identification, supervised learning algorithms usually fail when only one training sample per subject is available. The lack of training samples and the considerable image variations due to aging, illumination and pose variations, make recognition a challenging task. This letter proposes a development of the traditional eigenface solution by applying a feature selection process on the extracted eigenfaces. The proposal calls for the establishment of a feature subspace in which the intrasubject variation is minimized while the intersubject variation is maximized. Extensive experimentation following the FERET evaluation protocol suggests that in the scenario considered here, the proposed scheme improves significantly the recognition performance of the eigenface solution and outperforms other state-of-the-art methods.
2466525
Clustering of the SOM easily reveals distinct gene expression patterns: results of a reanalysis of lymphoma study
BackgroundA method to evaluate and analyze the massive data generated by series of microarray experiments is of utmost importance to reveal the hidden patterns of gene expression. Because of the complexity and the high dimensionality of microarray gene expression profiles, the dimensional reduction of raw expression data and the feature selections necessary for, for example, classification of disease samples remains a challenge. To solve the problem we propose a two-level analysis. First self-organizing map (SOM) is used. SOM is a vector quantization method that simplifies and reduces the dimensionality of original measurements and visualizes individual tumor sample in a SOM component plane. Next, hierarchical clustering and K-means clustering is used to identify patterns of gene expression useful for classification of samples.ResultsWe tested the two-level analysis on public data from diffuse large B-cell lymphomas. The analysis easily distinguished major gene expression patterns without the need for supervision: a germinal center-related, a proliferation, an inflammatory and a plasma cell differentiation-related gene expression pattern. The first three patterns matched the patterns described in the original publication using supervised clustering analysis, whereas the fourth one was novel.ConclusionsOur study shows that by using SOM as an intermediate step to analyze genome-wide gene expression data, the gene expression patterns can more easily be revealed. The "expression display" by the SOM component plane summarises the complicated data in a way that allows the clinician to evaluate the classification options rather than giving a fixed diagnosis.