BGP routing dynamics revisited
Understanding BGP routing dynamics is critical to the solid growth and maintenance of the Internet routing infrastructure. However, while the most extensive study on BGP dynamics is nearly a decade old, many factors that could affect BGP dynamics have changed considerably. We revisit this important topic in this paper, focusing on not only comparing with the previous results, but also issues not well explored before. We have found that, compared to almost a decade ago, although certain characteristics remain unchanged (such as some temporal properties), BGP dynamics are now â busier,â and more importantly, now have much less pathological behavior and are â healthierâ ; for example, forwarding dynamics are now not only dominant, but also more consistent across different days. Contributions to BGP dynamics by different BGP peersâ which are not proportional to the size of a peerâ s ASâ are also more stable, and dynamics due to policy changes or duplicate announcements are usually from specific peers

title: An internet routing forensics framework for discovering rules of abnormal BGP events
abstract: Abnormal BGP events such as attacks, misconfigurations, electricity failures, can cause anomalous or pathological routing behavior at either global level or prefix level, and thus must be detected in their early stages. Instead of using ad hoc methods to analyze BGP data, in this paper we introduce an Internet Routing Forensics framework to systematically process BGP routing data, discover rules of abnormal BGP events, and apply these rules to detect the occurrences of these events. In particular, we leverage data mining techniques to train the framework to learn rules of abnormal BGP events, and our results from two case studies show that these rules are effective. In one case study, rules of worm events discovered from the BGP data during the outbreaks of the CodeRed and Nimda worms were able to successfully detect worm impact on BGP when an independent worm, the Slammer, subsequently occurred. Similarly, in another case study, rules of electricity blackout events obtained using BGP data from the 2003 East Coast blackout were able to detect the BGP impact from the Florida blackout caused by Hurricane Frances in 2004.

title: SAVE: source address validity enforcement protocol
abstract: Forcing all IP packets to carry correct source addresses can greatly help network security, attack tracing, and network problem debugging. However, due to asymmetries in today's Internet routing, routers do not have readily available information to verify the correctness of the source address for each incoming packet. In this paper we describe a new protocol, named SAVE, that can provide routers with the information needed for source address validation. SAVE messages propagate valid source address information from the source location to all destinations, allowing each router along the way to build an incoming table that associates each incoming interface of the router with a set of valid source address blocks. This paper presents the protocol design and evaluates its correctness and performance by simulation experiments. The paper also discusses the issues of protocol security, the effectiveness of partial SAVE deployment, and the handling of unconventional forms of network routing, such as mobile IP and tunneling.

title: OntSum: A Semantic Query Routing Scheme in P2P Networks Based on Concise Ontology Indexing
abstract: Locating desirable resources is very important for a large distributed system. However, the distributed, heterogeneous, and unstructured nature of the system makes this issue very challenging. The discovering mechanism has to be not only semantically rich, in order to cope with complex queries, but also scalable to handle large numbers of information sources. In this paper, we address these problems by proposing OntSum, an efficient peer-to-peer query routing scheme based on concise ontology indexing. Unlike most existing systems, our system does not assume a global ontology but heterogeneous ontologies. Peers in the system use their own ontologies to describe their resource knowledge and the network topology is adjusted according to peers' ontological properties. A novel indexing strategy enables forwarding queries only to semantically related nodes. The architecture improves interoperability among network participants and aids efficient resource discovery through an expressive query language.

title: Text and picture segmentation by the distribution analysis of wavelet coefficients
abstract: This paper presents an algorithm to segment text and picture in an image using two features based on the statistical distribution of the wavelet coefficients in high frequency bands. The algorithm breaks the image into blocks and classifies every block as background, text or picture according to the two features. The block size is variable so that the segmentation can be accurate at the boundary of two types and avoids misclassifying due to over-localized region analysis.

title: Online estimation of trifocal tensors for augmenting live video
abstract: We propose a method to augment live video based on the tracking of natural features, and the online estimation of the trinocular geometry. Previous without-marker approaches require the computation of camera pose to render virtual objects. The strength of our proposed method is that it doesn 7 require tracking of camera pose, and exploits the usual advantages of marker-based approaches for a fast implementation. A 3-view AR system is used to demonstrate our approach. It consists of an uncalibrated camera that moves freely inside the scene of interest, and of three reference frames taken at the time of system initialization. As the camera is moving, image features taken from an initial triplet set are tracked throughout the video sequence. And the trifocal tensor associated with each frame is estimated online. With this tensor, the square pattern that was visible in the reference frames is transferred to the video. This invisible pattern is then used by the ARToolkit to embed virtual objects.

title: Power-performance considerations of parallel computing on chip multiprocessors
abstract: This paper looks at the power-performance implications of running parallel applications on chip multiprocessors (CMPs). First, we develop an analytical model that, for the first time, puts together parallel efficiency, granularity of parallelism, and voltage/frequency scaling, to establish a formal connection with the power consumption and performance of a parallel code running on a CMP. We then conduct detailed simulations of parallel applications running on a detailed power-performance CMP model to confirm the analytical results and provide further insights. Both analytical and experimental models show that parallel computing can bring significant power savings and still meet a given performance target by choosing granularity and voltage/frequency levels judiciously. The particular choice, however, is dependent on the application's parallel efficiency curve and the process technology utilized, which our model captures. Likewise, analytical model and experiments show the effect of a limited power budget on the application's scalability curve. In particular, we show that a limited power budget can cause a rapid performance degradation beyond a number of cores, even in the case of applications with excellent scalability properties. On the other hand, our experiments show that, when a limited power budget is in place, power-thrifty memory-bound applications may actually enjoy better scalability than more compute-intensive codes, even if the latter would exhibit higher scalability in a power-unconstrained scenario.

title: Using fixed point theorems to model the binding in protein-protein interactions
abstract: The binding in protein-protein interactions exhibits a kind of biochemical stability in cells. The mathematical notion of fixed points also describes stability. A point is a fixed point if it remains unchanged after a transformation by a function. Many points may not be a fixed point, but they may approach a stable status after multiple steps of transformation. In this paper, we define a point as a protein motif pair consisting of two traditional protein motifs. We propose a function and propose a method to discover stable motif pairs of this function from a large protein interaction, sequence data set. There are many interesting properties for this function (for example, the convergence). Some of them are useful for gaining much efficiency in the discovery of those stable motif pairs; some are useful for explaining why our proposed fixed point theorems are a good way to model the binding of protein interactions. Our results are also compared to biological results to elaborate the effectiveness, of our method.