10887794
Packet doppler: network monitoring using packet shift detection
Due to recent large-scale deployments of delay and loss-sensitive applications, there are increasingly stringent demands on the monitoring of service level agreement metrics. Although many end-to-end monitoring methods have been proposed, they are mainly based on active probing and thus inject measurement traffic into the network. In this paper, we propose a new scheme for monitoring service level agreement metrics, in particular, delay distribution. Our scheme is passive and therefore will not cause perturbation to real traffic. Using realistic delay and traffic demands, we show that our scheme achieves high accuracy and can detect burst events that will be missed by probing based methods.
36787117
Parallelizing Support Vector Machines on Distributed Computers
Support Vector Machines (SVMs) suffer from a widely recognized scalability problem in both memory use and computational time. To improve scalability, we have developed a parallel SVM algorithm (PSVM), which reduces memory use through performing a row-based, approximate matrix factorization, and which loads only essential data to each machine to perform parallel computation. Let n denote the number of training instances, p the reduced matrix dimension after factorization (p is significantly smaller than n), and m the number of machines. PSVM reduces the memory requirement from O(n2) to O(np/m), and improves computation time to O(np2/m). Empirical study shows PSVM to be effective. PSVM Open Source is available for download at http://code.google.com/p/psvm/.
4409694
On route selection for interdomain traffic engineering
In this article we investigate a model of route selection for interdomain traffic engineering where routing to multiple destinations can be coordinated. We identify potential routing instability and inefficiency problems, and derive a set of practical guidelines to guarantee stability without global coordination. Using a realistic Internet topology, we show that route oscillations can happen even when a small number of ASes coordinate route selection for just a small number of destinations if the coordination does not follow our guidelines. Wc further extend our model so that ASes can adopt any route selection algorithms in a class of algorithms we call rational route selection algorithms; and the local ranking of routes of an AS can depend on ingress traffic patterns. We show that persistent route oscillations can happen in certain network settings even if the ASes strictly follow the constraints imposed by business considerations, and adopt any rational route selection algorithms.
4427518
On the stability of rational, heterogeneous interdomain route selection
The recent discovery of instability caused by the interaction of local routing policies of multiple ASes has led to extensive research on the subject. However, previous studies analyze stability under a specific route selection algorithm. In this paper, instead of studying a specific route selection algorithm, we study a general class of route selection algorithms which we call rational route selection algorithms. We present a sufficient condition to guarantee routing convergence in a heterogeneous network where each AS runs any rational route selection algorithm. Applying our general results, we study the potential instability of a network where the preference of an AS depends on not only its egress routes to the destinations but also its inbound traffic patterns (i.e., the distribution of incoming traffic from its neighbors). We show that there exist networks which will have persistent route oscillations even when the ASes strictly follow the constraints imposed by business considerations, and adopt any rational route selection algorithms.
9852672
NXG06-6: On the Efficient Implementation of Pipelined Heaps for Network Processing
Priority queues are often used in many network processing applications. Applications include sophisticated per-flow scheduling for providing advanced quality-of-service (QoS) guarantees, fast packet buffer memory management, and exact maintenance of statistics counters for real-time network measurements. In all these applications, the priority queues used must operate at very high-speeds, e.g. at 40 Gbps rates and beyond. One widely used data structure for implementing priority queues is the heap data structure. However, the logarithmic time complexity of heap operations is often too slow for increasingly fast line rates. To achieve constant time complexity, the pipelined heap structure has been proposed. In this paper, we describe new architecture techniques for the efficient implementation of pipelined heaps. In particular, we focus on aggressive memory management and pipelining techniques.
49376
Pipelined van Emde Boas Tree: Algorithms, Analysis, and Applications
Priority queues are essential for various network processing applications, including per-flow queueing with quality-of-service (QoS) guarantees, management of large fast packet buffers, and management of statistics counters. In this paper, we propose a new data structure for implementing high-performance priority queues based on a pipelined version of the van Emde Boas tree. We show that we can achieve O(1) amortized time operations using our architecture, but we can achieve this algorithmic efficiency using only O (log log u) number of pipelined stages, where u is the size of the universe used to represent the priority keys.
27202859
Affective interaction based on person-independent facial expression space
This paper proposes a person-independent facial expression space (PIFES) to analyze and synthesize facial expressions based on supervised locality preserving projections (SLPP), which aligns different subjects and different intensities of facial expressions on one generalized expression manifold. Interactive curves of different patterns are generated according to the input facial expression image sequence, and target responsive expression images are synthesized for different emotions. In order to synthesize arbitrary expressions for a new person with natural details, a novel approach based on local geometry preserving between the input face image and the target expression image is proposed. Experimental results clearly demonstrate the efficiency of the proposed algorithm.
16457860
A New Secure Authentication Scheme Based Threshold ECDSA For Wireless Sensor Network
Security is an important issue for Wireless Sensor Network (WSN), especially for security-sensitive application. In this paper, we address secure authentication problems in WSN. First, we propose distributed authentication model for WSN, and secondly, advance the threshold ECDSA authentication scheme in this model, finally construct a new way to choose distributed CA severs of threshold authentication scheme. Our simulation results and analysis show that our scheme can reduce effectively bandwidth and computation resources while providing a robust, highly secure and highly available authentication service.
18359442
General Approach for Simulating Heterogeneity of Car-Following Behaviors
This paper presents a general approach to simulate heterogeneity of car-following behaviors in freeway traffic. This is achieved by proposing a new car-following model called General Individual Based car-following Model (GIBM) which takes into account the characteristics of the individual driver. The model parameters are expressed as functions with regard to “aggressiveness level” of drivers. The numerical simulation of the perturbation propagation in dense traffic flow by using the GIBM shows that small perturbations could develop into stable moving jams, growing moving jam, and decaying moving jams randomly, due to the heterogeneity of individual car-following behaviors in traffic flow. The result of the simulation is consistent with the empirical observation. The GIBM appears promising for application to microscopic simulations of traffic dynamics including randomness. It presents a general approach to simulate the heterogeneity of car-following behaviors efficiently and simply.
10926021
Agora: Grid Community in Vega Grid
In grid environment, how to organize, discover and use grid resources is one of the basic research problems. In this paper, we introduce a new concept called agora, which refers grid community in our Vega grid project. We propose a principle on agora as one of the basic design principles of Vega grid, which is the community principle. We give a detailed definition of the agora as a 4-tuple(S, O, C, P), representing the set of Subject, Object, Context, and Policy respectively. Our research methodology is comparative studies, drawing an analog between the grid and other platform systems such as OS, CPU, and MPI. We also study some properties about the agora, for example, grid law of inertia. This agora approach could be used to unify the grid invariability and dynamic variability effectively, develop the appropriate technology to support the dynamic and open properties of the grid, and deal with the complexity in the grid more efficiently.
15500084
Understanding the Prediction of Transmembrane Proteins by Support Vector Machine using Association Rule Mining
With the efforts to understand protein structure, many computational approaches have been made recently. Among them, the support vector machine (SVM) methods have been recently applied and showed successful performance compared with other machine learning schemes. However, despite the high performance, the SVM approaches suffer from the problem of understandability since it is a black-box model. To overcome this limitation, this study attempted to combine the SVM with the association rule based classifier which can present the meaningful explanation about the prediction. To perform this task, a new association rule based classifier (PCPAR) was devised based on the existing classifier, CPAR, to handle the sequential data. PCPAR creates the patterns by merging the generated rules and then classifies the sequential data based on the pattern match. The experimental result presents the following: with sequential data, the PCPAR scheme shows better performance with respect to the accuracy and the number of generated patterns than CPAR method whether applied alone or combined with SVM. The combined scheme of SVMPCPAR generates more compact patterns than the combined scheme of SVM with decision tree, SVM DT, with similar performance. These patterns are easily understandable and biologically meaningful