Results 1  10
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799,161
Predicting Internet Network Distance with CoordinatesBased Approaches
 In INFOCOM
, 2001
"... In this paper, we propose to use coordinatesbased mechanisms in a peertopeer architecture to predict Internet network distance (i.e. roundtrip propagation and transmission delay) . We study two mechanisms. The first is a previously proposed scheme, called the triangulated heuristic, which is bas ..."
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Cited by 633 (5 self)
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is based on relative coordinates that are simply the distances from a host to some special network nodes. We propose the second mechanism, called Global Network Positioning (GNP), which is based on absolute coordinates computed from modeling the Internet as a geometric space. Since end hosts maintain
The performance of TCP/IP for networks with high bandwidthdelay products and random loss
, 1997
"... This paper examines the performance of TCP/IP, the Internet data transport protocol, over Wide Area Networks (WANs) in which data traffic could coexist with realtime traffic such as voice and video. Specifically, we attempt to develop a basic understanding, using analysis and simulation, of the pro ..."
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Cited by 464 (6 self)
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, of the properties of TCP/IP in a regime where (1) the bandwidthdelay product of the network is high compared to the buffering in the network, and (2) there may be transient congestion due to fluctuations in realtime traffic, modeled here as producing random losses among the packets of the TCP connection
Measuring ISP Topologies with Rocketfuel
 In Proc. ACM SIGCOMM
, 2002
"... To date, realistic ISP topologies have not been accessible to the research community, leaving work that depends on topology on an uncertain footing. In this paper, we present new Internet mapping techniques that have enabled us to directly measure routerlevel ISP topologies. Our techniques reduce t ..."
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Cited by 838 (30 self)
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the number of required traces compared to a bruteforce, alltoall approach by three orders of magnitude without a significant loss in accuracy. They include the use of BGP routing tables to focus the measurements, exploiting properties of IP routing to eliminate redundant measurements, better alias
Optimization Flow Control, I: Basic Algorithm and Convergence
 IEEE/ACM TRANSACTIONS ON NETWORKING
, 1999
"... We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm. In thi ..."
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Cited by 690 (64 self)
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We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using gradient projection algorithm
Markov Logic Networks
 MACHINE LEARNING
, 2006
"... We propose a simple approach to combining firstorder logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a firstorder knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects in the ..."
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Cited by 811 (39 self)
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We propose a simple approach to combining firstorder logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a firstorder knowledge base with a weight attached to each formula (or clause). Together with a set of constants representing objects
Bayesian Network Classifiers
, 1997
"... Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competitive with stateoftheart classifiers such as C4.5. This fact raises the question of whether a classifier with less restr ..."
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Cited by 788 (23 self)
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restrictive assumptions can perform even better. In this paper we evaluate approaches for inducing classifiers from data, based on the theory of learning Bayesian networks. These networks are factored representations of probability distributions that generalize the naive Bayesian classifier and explicitly
A DelayTolerant Network Architecture for Challenged Internets
, 2003
"... The highly successful architecture and protocols of today’s Internet may operate poorly in environments characterized by very long delay paths and frequent network partitions. These problems are exacerbated by end nodes with limited power or memory resources. Often deployed in mobile and extreme env ..."
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Cited by 937 (13 self)
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environments lacking continuous connectivity, many such networks have their own specialized protocols, and do not utilize IP. To achieve interoperability between them, we propose a network architecture and application interface structured around optionallyreliable asynchronous message forwarding, with limited
Directed Diffusion for Wireless Sensor Networking
 IEEE/ACM Transactions on Networking
, 2003
"... Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diffusion paradigm for such ..."
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Cited by 658 (9 self)
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for such coordination. Directed diffusion is datacentric in that all communication is for named data. All nodes in a directed diffusionbased network are applicationaware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data innetwork (e.g., data
Finding community structure in networks using the eigenvectors of matrices
, 2006
"... We consider the problem of detecting communities or modules in networks, groups of vertices with a higherthanaverage density of edges connecting them. Previous work indicates that a robust approach to this problem is the maximization of the benefit function known as “modularity ” over possible div ..."
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Cited by 500 (0 self)
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number of possible algorithms for detecting community structure, as well as several other results, including a spectral measure of bipartite structure in networks and a new centrality measure that identifies those vertices that occupy central positions within the communities to which they belong
Active Learning with Statistical Models
, 1995
"... For manytypes of learners one can compute the statistically "optimal" way to select data. We review how these techniques have been used with feedforward neural networks [MacKay, 1992# Cohn, 1994]. We then showhow the same principles may be used to select data for two alternative, statist ..."
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Cited by 677 (12 self)
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For manytypes of learners one can compute the statistically "optimal" way to select data. We review how these techniques have been used with feedforward neural networks [MacKay, 1992# Cohn, 1994]. We then showhow the same principles may be used to select data for two alternative
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799,161