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.

A Tale of One City: Using Cellular Network Data for Urban Planning

Abstract: Cellular data from call detail records can help urban planners better understand city dynamics. The authors use CDR data to analyze people flow in and out of a suburban city near New York City.

The distribution of faults in a large industrial software system

Abstract: A case study is presented using thirteen releases of a large industrial inventory tracking system. Several types of questions are addressed in this study. The first involved examining how faults are distributed over the different files. This included making a distinction between the release during which they were discovered, the lifecycle stage at which they were first detected, and the severity of the fault. The second category of questions we considered involved studying how the size of modules affected their fault density. This included looking at questions like whether or not files with high fault densities at early stages of the lifecycle also had high fault densities during later stages. A third type of question we considered was whether files that contained large numbers of faults during early stages of development, also had large numbers of faults during later stages, and whether faultiness persisted from release to release. Finally, we examined whether newly written files were more fault-prone than ones that were written for earlier releases of the product. The ultimate goal of this study is to help identify characteristics of files that can be used as predictors of fault-proneness, thereby helping organizations determine how best to use their testing resources.

The prize collecting Steiner tree problem: theory and practice

Abstract: We consider variants on the Prize Collecting Steiner Tree problem and on the primal-dual 2-approximation algorithm devised for it by Goemans and Williamson. We introduce an improved pruning rule for the algorithm that is slightly faster and provides solutions that are at least as good and typically significantly better. On a selection of real-world instances whose underlying graphs are county street maps, the improvement in the standard objective function ranges from 1.7% to 9.2%. Substantially better improvements are obtained for the complementary "net worth" objective function and for randomly generated instances. We also show that modifying the growth phase of the GoemansWilliamson algorithm to make it independent of the choice of root vertex does not significantly affect the algorithm's worst-case guarantee or behavior in practice. The resulting algorithm can be fttrther modified so that, without an increase in running time, it becomes a 2-approximation algorithm for finding the best subtree over all choices of root. In the second part of the paper, we consider quota and budget versions of the problem. In the first, one is looking for the tree with minimum edge cost that contains vertices whose total prize is at least a given quota; in the second one is looking for the tree with maximum prize, given that the total edge cost is within a given budget. The quota problem is a generalization of the k-MST problem, and we observe how constant-factor approximation algorithms for that problem can be extended to it. We also show how a (5 ÷ e)approximation algorithm for the (unrooted) budget problem can be derived from Gaxg's 3-approximation algorithm for the k-MST. None of these algorithms are likely to be used in ~ ractice, but we show how the general approach behind them which involves performing multiple runs of the GoemansWiUiamson algorithm using an increasing sequence of prizemultipliers) can be incorporated into a practical heuristic. We also uncover some surprising properties of the cost/prize tradeoff curves generated (and used) by this approach. 1 Prob lem Def in i t ions In the Prize Collecting Steiner Tree" (PCST) problem, one is given a graph G = (V, E) , a non-negative edge cost c(e) for each edge e 6 E , a non-negative vertex prize p(v) for each vertex v 6 V, and a specified root vertex vo 6 V. In this paper we shall consider four different optimization problems based on this scenario, the first being the one initially studied in [6, 7]: " ¢ / ~ T Labs, Room C239, 180 Park Avenue, Florham Park, NJ 07932. Email: dsj@research.att.com ?MIT Lab. for Computer Science, 545 Tech Square, Cambridge, MA 02139. Emaih mariam@theory.lcs.mit.edu SAT&T Labs, Room A003, 180 Park Avenue, Florham Park, NJ 07932. Emaih phillips@reseoxch.att.com Steven Phillips 1. The Goemans-WiUiamson Minimization problem: Find a subtree T ' = (V',E') of G tha t minimizes the cost of the edges in the tree plus the prizes of the vertices not in the tree, i.e., tha t minimizes GW(T') = Z c(e) + Z p(v)

Comparisons of a computer-based propagation prediction tool with experimental data collected in urban microcellular environments

Abstract: Engineers designing and installing outdoor and indoor wireless communications systems need effective and practical tools to help them determine base station antenna locations for adequate signal coverage. Computer-based radio propagation prediction tools are now often used in designing these systems. We assess the performance of such a propagation tool based on ray-tracing and advanced computational methods. We have compared its predictions with outdoor experimental data collected in Manhattan and Boston (at 900 MHz and 2 GHz). The comparisons show that the computer-based propagation tool can predict signal strengths in these environments with very good accuracy. The prediction errors are within 6 dB in both mean and standard deviation. This shows that simulations, rather than costly field measurements, can lead to accurate determination of the coverage area for a given system design.

A first look at cellular machine-to-machine traffic: large scale measurement and characterization

Abstract: Cellular network based Machine-to-Machine (M2M) communication is fast becoming a market-changing force for a wide spectrum of businesses and applications such as telematics, smart metering, point-of-sale terminals, and home security and automation systems. In this paper, we aim to answer the following important question: Does traffic generated by M2M devices impose new requirements and challenges for cellular network design and management? To answer this question, we take a first look at the characteristics of M2M traffic and compare it with traditional smartphone traffic. We have conducted our measurement analysis using a week-long traffic trace collected from a tier-1 cellular network in the United States. We characterize M2M traffic from a wide range of perspectives, including temporal dynamics, device mobility, application usage, and network performance.Our experimental results show that M2M traffic exhibits significantly different patterns than smartphone traffic in multiple aspects. For instance, M2M devices have a much larger ratio of uplink to downlink traffic volume, their traffic typically exhibits different diurnal patterns, they are more likely to generate synchronized traffic resulting in bursty aggregate traffic volumes, and are less mobile compared to smartphones. On the other hand, we also find that M2M devices are generally competing with smartphones for network resources in co-located geographical regions. These and other findings suggest that better protocol design, more careful spectrum allocation, and modified pricing schemes may be needed to accommodate the rise of M2M devices.