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.

Semiring frameworks and algorithms for shortest-distance problems

Abstract: We define general algebraic frameworks for shortest-distance problems based on the structure of semirings. We give a generic algorithm for finding single-source shortest distances in a weighted directed graph when the weights satisfy the conditions of our general semiring framework. The same algorithm can be used to solve efficiently classical shortest paths problems or to find the k-shortest distances in a directed graph. It can be used to solve single-source shortest-distance problems in weighted directed acyclic graphs over any semiring. We examine several semirings and describe some specific instances of our generic algorithms to illustrate their use and compare them with existing methods and algorithms. The proof of the soundness of all algorithms is given in detail, including their pseudocode and a full analysis of their running time complexity.

Node Classification in Social Networks

Abstract: When dealing with large graphs, such as those that arise in the context of online social networks, a subset of nodes may be labeled. These labels can indicate demographic values, interest, beliefs or other characteristics of the nodes (users). A core problem is to use this information to extend the labeling so that all nodes are assigned a label (or labels).

Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures

Abstract: Server consolidation based on virtualization is an important technique for improving power efficiency and resource utilization in cloud infrastructures. However, to ensure satisfactory performance on shared resources under changing application workloads, dynamic management of the resource pool via online adaptation is critical. The inherent tradeoffs between power and performance as well as between the cost of an adaptation and its benefits make such management challenging. In this paper, we present Mistral, a holistic controller framework that optimizes power consumption, performance benefits, and the transient costs incurred by various adaptations and the controller itself to maximize overall utility. Mistral can handle multiple distributed applications and large-scale infrastructures through a multi-level adaptation hierarchy and scalable optimization algorithm. We show that our approach outstrips other strategies that address the tradeoff between only two of the objectives (power, performance, and transient costs).

Estimating flow distributions from sampled flow statistics

Abstract: Passive traffic measurement increasingly employs sampling at the packet level. Many high-end routers form flow statistics from a sampled substream of packets. Sampling is necessary in order to control the consumption of resources by the measurement operations. However, knowledge of the statistics of flows in the unsampled stream remains useful, for understanding both characteristics of source traffic, and consumption of resources in the network.This paper provide methods that use flow statistics formed from sampled packet stream to infer the absolute frequencies of lengths of flows in the unsampled stream. A key part of our work is inferring the numbers and lengths of flows of original traffic that evaded sampling altogether. We achieve this through statistical inference, and by exploiting protocol level detail reported in flow records. The method has applications to detection and characterization of network attacks: we show how to estimate, from sampled flow statistics, the number of compromised hosts that are sending attack traffic past the measurement point. We also investigate the impact on our results of different implementations of packet sampling.

NetWORKers and their Activity in IntensionalNetworks

Abstract: Through ethnographic research, we document the rise of personal social networks in the workplace, which we call i>intensional networks. Paradoxically, we find that the most fundamental unit of analysis for computer-supported cooperative work is i>not at the group level for many tasks and settings, but at the individual level as personal social networks come to be more and more important. Collective subjects are increasingly put together through the assemblage of people found through personal networks rather than being constituted as teams created through organizational planning and structuring. Teams are still important but they are not the centerpiece of labor management they once were, nor are they the chief resource for individual workers. We draw attention to the importance of networks as most CSCW system designs assume a team. We urge that designers take account of networks and the problems they present to workers.