5847118
A self-tuning structure for adaptation in TCP/AQM networks
Congestion control in TCP/AQM networks is expected to perform well for a wide-range of conditions, but recent advances in modeling and analysis indicate that present AQM schemes need an extra dose of adaptability to cope. This paper answers the call and proposes a self-tuning structure wherein AQM parameters are automatically tuned in response to on-line estimation of link capacity and traffic load. This approach is applicable to any AQM scheme that is parameterizable in terms of link capacity and TCP load. In this paper, we will describe this self-tuning structure, illustrate its application to PI and RED AQMs, provide stability analysis, and conduct <tt>ns</tt> simulations to compare with both fixed AQM schemes and the recently proposed adaptive RED.
13845864
On the interaction between overlay routing and underlay routing
In this paper, we study the interaction between overlay routing and traffic engineering (TE) in a single autonomous system (AS). We formulate this interaction as a two-player non-cooperative non-zero sum game, where the overlay tries to minimize the delay of its traffic and the TE's objective is to minimize network cost. We study a Nash routing game with best-reply dynamics, in which the overlay and TE have equal status, and take turns to compute their optimal strategies based on the response of the other player in the previous round. We prove the existence, uniqueness and global stability of Nash equilibrium point (NEP) for a simple network. For general networks, we show that the selfish behavior of an overlay can cause huge cost increases and oscillations to the whole network. Even worse, we have identified cases, both analytically and experimentally, where the overlay's cost increases as the Nash routing game proceeds even though the overlay plays optimally based on TE's routing at each round. Experiments are performed to verify our analysis.
147783
Availability in BitTorrent Systems
In this paper, we investigate the problem of highly available, massive-scale file distribution in the Internet. To this end, we conduct a large-scale measurement study of BitTorrent, a popular class of systems that use swarms of actively downloading peers to assist each other in file distribution. The first generation of BitTorrent systems used a central tracker to enable coordination among peers, resulting in low availability due to the tracker's single point of failure. Our study analyzes the prevalence and impact of two recent trends to improve BitTorrent availability: (i) use of multiple trackers, and (ii) use of Distributed Hash Tables (DHTs), both of which also help to balance load better. The study considered more than 1,400 trackers and 24,000 DHT nodes (extracted from about 20,000 torrents) over a period of two months. We find that both trends improve availability, but for different and somewhat unexpected reasons. Our findings include: (i) multiple trackers improve availability, but the improvement largely comes from the choice of a single highly available tracker, (ii) such improvement is reduced by the presence of correlated failures, (iii) multiple trackers can significantly reduce the connectivity of the overlay formed by peers, (iv) the DHT improves information availability, but induces a higher response latency to peer queries.
6607794
Can an Overlay Compensate for a Careless Underlay?
We investigate the ability of an overlay network to compensate for “careless” routing in the native network layer, i.e., for network-layer routes not optimized for performance. We consider cost/traffic-dependent, overlay routing on top of an underlay routing based on randomly-generated, cost/traffic-independent link weights, and determine the extent to which overlay-overcareless-underlay can achieve performance close to that attainable when underlay routing is performed in an optimal cost/trafficdependent (“careful”) manner. We identify three graph-theoretic metrics that collectively characterize the richness of the underlay network: the tightness (characteristic path length, or CPL), the thickness (cut average) and the weighted sum of node degrees. We find that only when the underlay graph is rich can the overlay compensate for a careless underlay. If network links have linear costs, we prove that overlay cost is a linear increasing function of CPL under some assumptions. Finally, we investigate heuristics (based on the notion of richness) for choosing a set of overlay nodes of fixed size that is likely to result in good overlay performance.
11427190
Exploiting the IPID Field to Infer Network Path and End-System Characteristics
In both active and passive network Internet measurements, the IP packet has a number of important header fields that have played key roles in past measurement efforts, e.g., IP source/destination address, protocol, TTL, port, and sequence number/acknowledgment. The 16-bit identification field (IPID) has only recently been studied to determine what information it might yield for network measurement and performance characterization purposes. We explore several new uses of the IPID field, including how it can be used to infer: (a) the amount of internal (local) traffic generated by a server; (b) the number of servers in a large-scale, load-balanced server complex and; (c) the difference between one-way delays of two machines to a target computer. We illustrate and validate the use of these techniques through empirical measurement studies.
2899757
Providing throughput differentiation for TCP flows using adaptive two-color marking and two-level AQM
In this paper we propose a new paradigm for a Differentiated Service (DiffServ) network consisting of two-color marking at the edges of the network using token buckets coupled with differential treatment in the core. Using fluid-flow modelling, we present existence conditions for token-bucket rates and differential marking probabilities at the core that result in all edges receiving at least their minimum guaranteed rates. We then present an integrated DiffServ architecture comprising of an active rate management controller at the marking edge and a two-level active queue management controller at the core. The validity of the fluid flow model and performance of this new scheme are verified using ns simulations.
37845872
The complexity of learning in PLN networks
Abstract In this paper, the complexity of learning in the feedforward PLN network is investigated by using Markov chain theory, when its training samples are incomplete (i.e., a network with hidden nodes). We present a learning algorithm. A formula for computing the average number of steps that the learning algorithm converges is obtained when the PLN network exists a solution. In the probabilistic sense, the completeness of the learning algorithm is proved. Some computer simulations are given to verify the analysis.
10184956
Mesh Simplification Based on Shading Characteristic
Mesh simplification is a key research area in scientific visualization and virtual reality. The paper presents a new method of polyhedral model simplification based on vision characteristic and edge collapse. This method determines model ’s vision characteristic by computing the maximum product of angle between normal of vertex and adjacent triangles with area of these triangles. It can achieve a high decimation rate, while keeping the details of vision. This algorithm can also be extended to triangle decimation criterion easily.
15559062
Adaptive Geometry Compression Based on 4-Point Interpolatory Subdivision Schemes
We propose an adaptive geometry compression method based on 4-point interpolatory subdivision schemes. It can work on digital curves of arbitrary dimensions. With the geometry compression method, a digital curve is adaptively compressed into several segments with different compression levels. Each segment is a 4-point subdivision curve with a subdivision step. In the meantime, we provide high-speed 4-point interpolatory subdivision curve generation methods for efficiently decompressing the compressed data. In the decompression methods, we consider both the open curve case and the closed curve case. For an arbitrary positive integer k, formulae of the number of the resultant control points of an open or closed 4-point subdivision curve after k subdivision steps are provided. The time complexity of the new approaches are O(n), where n is the number of the points in the given digital curve. Examples are provided as well to illustrate the efficiency of the proposed approaches.
8107037
Forward Shadow Mapping
Forward shadow mapping is a new approach to real-time shadow generation. The traditional shadow map algorithm maps the pixels in the eye’s view backward into the depth buffers of light sources (i.e. shadow maps), which is similiar to and often implemented as an extension to texture mapping. Our algorithm reverses this process by using 3-D image warping techniques to transform shadow map pixels forward into the eye’s view to directly indicate which pixels are lit; it does not interfere with normal texture mapping and easily supports antialiased shadow edges and projective textures. Access to shadow maps and projective textures is in pixel-sequential order. This algorithm has advantages when speed of texture mapping becomes the performance bottleneck, which is often the case in visual simulation and game applications.
4541399
Discriminant analysis with tensor representation
In this paper, we present a novel approach to solving the supervised dimensionality reduction problem by encoding an image object as a general tensor of 2nd or higher order. First, we propose a discriminant tensor criterion (DTC), whereby multiple interrelated lower-dimensional discriminative subspaces are derived for feature selection. Then, a novel approach called k-mode cluster-based discriminant analysis is presented to iteratively learn these subspaces by unfolding the tensor along different tensor dimensions. We call this algorithm discriminant analysis with tensor representation (DATER), which has the following characteristics: 1) multiple interrelated subspaces can collaborate to discriminate different classes; 2) for classification problems involving higher-order tensors, the DATER algorithm can avoid the curse of dimensionality dilemma and overcome the small sample size problem; and 3) the computational cost in the learning stage is reduced to a large extent owing to the reduced data dimensions in generalized eigenvalue decomposition. We provide extensive experiments by encoding face images as 2nd or 3rd order tensors to demonstrate that the proposed DATER algorithm based on higher order tensors has the potential to outperform the traditional subspace learning algorithms, especially in the small sample size cases.