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.

Congestion-aware single link failure recovery in hybrid SDN networks

Abstract: As service providers have started deploying SDN in their networks, traditional IP routers are gradually upgraded to SDN enabled switches. In other words, the network will have traditional IP routers and SDN switches coexisting, and it is called a hybrid SDN network. With such a network, we take advantage of SDN and propose an approach to guarantee traffic reachability in the presence of any single link failure. By redirecting traffic on the failed link to SDN switches through pre-configured IP tunnels, the proposed approach is able to react to the failures very fast. With the help of coordination among SDN switches, we are also able to explore multiple backup paths for the failure recovery. This allows the proposed approach to avoid potential congestion in the post-recovery network by choosing proper backup paths. Simulation results show that our proposed scheme requires only a very few number of SDN switches in the hybrid SDN network to achieve fast recovery and guarantee 100% reachability from any single link failure. It also shows that the proposed approach is able to better load-balance the post-recovery network comparing to IP Fast Reroute and shortest path re-calculation.

Private Release of Graph Statistics using Ladder Functions

Abstract: Protecting the privacy of individuals in graph structured data while making accurate versions of the data available is one of the most challenging problems in data privacy. Most efforts to date to perform this data release end up mired in complexity, overwhelm the signal with noise, and are not effective for use in practice. In this paper, we introduce a new method which guarantees differential privacy. It specifies a probability distribution over possible outputs that is carefully defined to maximize the utility for the given input, while still providing the required privacy level. The distribution is designed to form a 'ladder', so that each output achieves the highest 'rung' (maximum probability) compared to less preferable outputs. We show how our ladder framework can be applied to problems of counting the number of occurrences of subgraphs, a vital objective in graph analysis, and give algorithms whose cost is comparable to that of computing the count exactly. Our experimental study confirms that our method outperforms existing methods for counting triangles and stars in terms of accuracy, and provides solutions for some problems for which no effective method was previously known. The results of our algorithms can be used to estimate the parameters of suitable graph models, allowing synthetic graphs to be sampled.

Measuring privacy loss and the impact of privacy protection in web browsing

Abstract: Various bits of information about users accessing Web sites. some of which are private, have been gathered since the inception of the Web. Increasingly the gathering, aggregation, and processing has been outsourced to third parties. The goal of this work is to examine the effectiveness of specific techniques to limit this diffusion of private information to third parties. We also examine the impact of these privacy protection techniques on the usability and quality of the Web pages returned. Using objective measures for privacy protection and page quality we examine their tradeoffs for different privacy protection techniques applied to a collection of popular Web sites as well as a focused set of sites with significant privacy concerns. We study privacy protection both at a browser and at a proxy.

Rate-adaptable optics for next generation long-haul transport networks

Abstract: We discuss the emerging rate-adaptable optical transmission technology and how this new technology may be employed to further reduce the transport network cost to meet ever growing bandwidth demand in the core network Two different types of transponders are considered: those adjusting either the transported bit rate (ie, client data rate) or the symbol rate (with a fixed bit rate) We propose a methodology for calculating the (normalized) cost to build out an entire long-haul transport network with several options for bit-rate-adaptable transponders By using link-length demands from an exemplary distance-diverse network, we demonstrate that time-domain hybrid-QAM-enabled fine-grain rate-adaptable transponders can reduce network cost by more than 20 percent within a traditional, fixed-bandwidth, wavelength-division-multiplexed grid We also argue that the total transponder expense using symbol-rate-adaptable technology will be greater than when using bit-rate-adaptable technology, as well as requiring more costly flex-grid ROADMs for channel routing

Tight(er) worst-case bounds on dynamic searching and priority queues

Abstract: We introduce a novel technique for converting static polynomial space search structures for ordered sets into fully-dynamic linear space data structures. Based on this we present optimal bounds for ...