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Minimum energy mobile wireless networks
 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
, 1999
"... We describe a distributed positionbased network protocol optimized for minimum energy consumption in mobile wireless networks that support peertopeer communications. Given any number of randomly deployed nodes over an area, we illustrate that a simple local optimization scheme executed at each n ..."
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Cited by 750 (0 self)
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node guarantees strong connectivity of the entire network and attains the global minimum energy solution for stationary networks. Due to its localized nature, this protocol proves to be selfreconfiguring and stays close to the minimum energy solution when applied to mobile networks. Simulation results
Fuzzy extractors: How to generate strong keys from biometrics and other noisy data
, 2008
"... We provide formal definitions and efficient secure techniques for • turning noisy information into keys usable for any cryptographic application, and, in particular, • reliably and securely authenticating biometric data. Our techniques apply not just to biometric information, but to any keying mater ..."
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Cited by 533 (38 self)
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for various measures of “closeness” of input data, such as Hamming distance, edit distance, and set difference.
Clustering by passing messages between data points
 Science
, 2007
"... Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars ” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only if that initi ..."
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Cited by 699 (8 self)
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if that initial choice is close to a good solution. We devised a method called “affinity propagation,” which takes as input measures of similarity between pairs of data points. Realvalued messages are exchanged between data points until a highquality set of exemplars and corresponding clusters gradually emerges
The Node Distribution of the Random Waypoint Mobility Model for Wireless Ad Hoc Networks
, 2003
"... The random waypoint model is a commonly used mobility model in the simulation of ad hoc networks. It is known that the spatial distribution of network nodes moving according to this model is, in general, nonuniform. However, a closedform expression of this distribution and an indepth investigation ..."
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Cited by 376 (10 self)
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The random waypoint model is a commonly used mobility model in the simulation of ad hoc networks. It is known that the spatial distribution of network nodes moving according to this model is, in general, nonuniform. However, a closedform expression of this distribution and an in
Fuzzy identitybased encryption
 In EUROCRYPT
, 2005
"... We introduce a new type of IdentityBased Encryption (IBE) scheme that we call Fuzzy IdentityBased Encryption. In Fuzzy IBE we view an identity as set of descriptive attributes. A Fuzzy IBE scheme allows for a private key for an identity, ω, to decrypt a ciphertext encrypted with an identity, ω ′ , ..."
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Cited by 375 (20 self)
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′ , if and only if the identities ω and ω ′ are close to each other as measured by the “set overlap ” distance metric. A Fuzzy IBE scheme can be applied to enable encryption using biometric inputs as identities; the errortolerance property of a Fuzzy IBE scheme is precisely what allows for the use of biometric
WEAK KAM THEORY TOPICS IN THE STATIONARY ERGODIC SETTING
, 2009
"... We perform a qualitative analysis of the critical equation associated with a stationary ergodic Hamiltonian through a stochastic version of the metric method, where the notion of closed random stationary set, issued from stochastic geometry, plays a major role. Our purpose is to give an appropriat ..."
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Cited by 7 (3 self)
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We perform a qualitative analysis of the critical equation associated with a stationary ergodic Hamiltonian through a stochastic version of the metric method, where the notion of closed random stationary set, issued from stochastic geometry, plays a major role. Our purpose is to give
Mining timechanging data streams
 IN PROC. OF THE 2001 ACM SIGKDD INTL. CONF. ON KNOWLEDGE DISCOVERY AND DATA MINING
, 2001
"... Most statistical and machinelearning algorithms assume that the data is a random sample drawn from a stationary distribution. Unfortunately, most of the large databases available for mining today violate this assumption. They were gathered over months or years, and the underlying processes genera ..."
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Cited by 337 (5 self)
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Most statistical and machinelearning algorithms assume that the data is a random sample drawn from a stationary distribution. Unfortunately, most of the large databases available for mining today violate this assumption. They were gathered over months or years, and the underlying pro
On the local connectivity number of stationary random closed sets
 PROCEEDINGS TO THE 7TH INTERNATIONAL SYMPOSIUM ON MATHEMATICAL MORPHOLOGY
, 2005
"... Random closed sets (RACS) in the d–dimensional Euclidean space are considered, whose realizations belong to the extended convex ring. A family of nonparametric estimators is investigated for the simultaneous estimation of the vector of all specific Minkowski functionals (or, equivalently, the speci ..."
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Cited by 3 (3 self)
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Random closed sets (RACS) in the d–dimensional Euclidean space are considered, whose realizations belong to the extended convex ring. A family of nonparametric estimators is investigated for the simultaneous estimation of the vector of all specific Minkowski functionals (or, equivalently
Stationary Distributions for the Random Waypoint Mobility Model
 IEEE Transactions on Mobile Computing
, 2003
"... In simulations of mobile ad hoc networks, the probability distribution governing the movement of the nodes typically varies over time, and converges to a "steadystate" distribution, known in the probability literature as the stationary distribution. Some published simulation results ig ..."
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Cited by 189 (7 self)
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ignore this initialization discrepancy. For those results that attempt to account for this discrepancy, the practice is to discard an initial sequence of observations from a simulation in the hope that the remaining values will closely represent the stationary distribution. This approach
A Stochastic Model of TCP/IP with Stationary Random Losses
 ACM SIGCOMM
, 2000
"... In this paper, we present a model for TCP/IP congestion control mechanism. The rate at which data is transmitted increases linearly in time until a packet loss is detected. At this point, the transmission rate is divided by a constant factor. Losses are generated by some exogenous random process whi ..."
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Cited by 209 (42 self)
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In this paper, we present a model for TCP/IP congestion control mechanism. The rate at which data is transmitted increases linearly in time until a packet loss is detected. At this point, the transmission rate is divided by a constant factor. Losses are generated by some exogenous random process
Results 1  10
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1,494,047