AT&T Labs

About: AT&T Labs is a based out in . It is known for research contribution in the topics: Network packet & The Internet. The organization has 1879 authors who have published 5595 publications receiving 483151 citations.

Deriving traffic demands for operational IP networks: methodology and experience

Abstract: Engineering a large IP backbone network without an accurate network-wide view of the traffic demands is challenging. Shifts in user behavior, changes in routing policies, and failures of network elements can result in significant (and sudden) fluctuations in load. In this paper, we present a model of traffic demands to support traffic engineering and performance debugging of large Internet Service Provider networks. By defining a traffic demand as a volume of load originating from an ingress link and destined to a set of egress links, we can capture and predict how routing affects the traffic traveling between domains. To infer the traffic demands, we propose a measurement methodology that combines flow-level measurements collected at all ingress links with reachability information about all egress links. We discuss how to cope with situations where practical considerations limit the amount and quality of the necessary data. Specifically, we show how to infer interdomain traffic demands using measurements collected at a smaller number of edge links-the peering links connecting the neighboring providers. We report on our experiences in deriving the traffic demands in the AT&T IP BAckbone, by collecting, validating, and joining very large and diverse sets of usage, configuration, and routing data over extended periods of time. The paper concludes with a preliminary analysis of the observed dynamics of the traffic demands and a discussion of the practical implications for traffic engineering.

Issues for routing in the optical layer

Abstract: Optical layer control planes based on MPLS and other Internet protocols hold great promise because of their proven scalability, ability to support rapid provisioning, and auto discovery and self-inventory capabilities and are under intense study in various standards bodies. To date however little attention has been paid to aspects of the optical layer which differ from those found in data networking. We study three such aspects which impact routing: network elements which are reconfigurable, but in constrained ways; transmission impairments which may make some routes unusable; and diversity. We conclude that if emerging optical technology is to be maximally exploited, heterogeneous technologies with dissimilar routing constraints are likely. Four alternative architectures for dealing with this eventuality are identified and some trade-offs between centralizing or distributing some aspects of routing are discussed.

Aligning Conservation Priorities Across Taxa in Madagascar with High-Resolution Planning Tools

Abstract: Globally, priority areas for biodiversity are relatively well known, yet few detailed plans exist to direct conservation action within them, despite urgent need. Madagascar, like other globally recognized biodiversity hot spots, has complex spatial patterns of endemism that differ among taxonomic groups, creating challenges for the selection of within-country priorities. We show, in an analysis of wide taxonomic and geographic breadth and high spatial resolution, that multitaxonomic rather than single-taxon approaches are critical for identifying areas likely to promote the persistence of most species. Our conservation prioritization, facilitated by newly available techniques, identifies optimal expansion sites for the Madagascar government's current goal of tripling the land area under protection. Our findings further suggest that high-resolution multitaxonomic approaches to prioritization may be necessary to ensure protection for biodiversity in other global hot spots.

The pyramid-technique: towards breaking the curse of dimensionality

Abstract: In this paper, we propose the Pyramid-Technique, a new indexing method for high-dimensional data spaces. The Pyramid-Technique is highly adapted to range query processing using the maximum metric Lmax. In contrast to all other index structures, the performance of the Pyramid-Technique does not deteriorate when processing range queries on data of higher dimensionality. The Pyramid-Technique is based on a special partitioning strategy which is optimized for high-dimensional data. The basic idea is to divide the data space first into 2d pyramids sharing the center point of the space as a top. In a second step, the single pyramids are cut into slices parallel to the basis of the pyramid. These slices from the data pages. Furthermore, we show that this partition provides a mapping from the given d-dimensional space to a 1-dimensional space. Therefore, we are able to use a B+-tree to manage the transformed data. As an analytical evaluation of our technique for hypercube range queries and uniform data distribution shows, the Pyramid-Technique clearly outperforms index structures using other partitioning strategies. To demonstrate the practical relevance of our technique, we experimentally compared the Pyramid-Technique with the X-tree, the Hilbert R-tree, and the Linear Scan. The results of our experiments using both, synthetic and real data, demonstrate that the Pyramid-Technique outperforms the X-tree and the Hilbert R-tree by a factor of up to 14 (number of page accesses) and up to 2500 (total elapsed time) for range queries.

Increasing data rate over wireless channels

Abstract: Space-time coding (STC) is a new coding/signal processing framework for wireless communication systems with multiple transmit and multiple receive antennas. This new framework has the potential of dramatically improve the capacity and data rates. In addition, this framework presents the best trade-off between spectral efficiency and power consumption. ST codes (designed so far) come in two different types. ST trellis codes offer the maximum possible diversity gain and a coding gain without any sacrifice in the transmission bandwidth. The decoding of these codes, however, would require the use of a vector form of the Viterbi decoder. Space-time block codes (STBCs) offer a much simpler may of obtaining transmit diversity without any sacrifice in bandwidth and without requiring huge decoding complexity. In fact, the structure of the STBCs is such that it allows for very simple signal processing (linear combining) for encoding/decoding, differential encoding/detection, and interference cancellation. This new signal processing framework offered by ST codes can be used to enhance the data rate and/or capacity in various wireless applications. That is the reason many of these STC ideas have already found their way to some of the current third-generation wireless systems standards.