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42
Exploiting process lifetime distributions for dynamic load balancing
 ACM Transactions on Computer Systems
, 1997
"... We consider policies for CPU load balancing in networks of workstations. We address the question of whether preemptive migration (migrating active processes) is necessary, or whether remote execution (migrating processes only at the time of birth) is sufficient for load balancing. We show that resol ..."
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Cited by 313 (31 self)
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We consider policies for CPU load balancing in networks of workstations. We address the question of whether preemptive migration (migrating active processes) is necessary, or whether remote execution (migrating processes only at the time of birth) is sufficient for load balancing. We show that resolving this issue is strongly tied to understanding the process lifetime distribution. Our measurements indicate that the distribution of lifetimes for a UNIX process is Pareto (heavytailed), with a consistent functional form over a variety of workloads. We show how to apply this distribution to derive a preemptive migration policy that requires no handtuned parameters. We used a tracedriven simulation to show that our preemptive migration strategy is far more effective than remote execution, even when the memory transfer cost is high.
On scalable attack detection in the network
, 2007
"... Current intrusion detection and prevention systems seek to detect a wide class of network intrusions (e.g., DoS attacks, worms, port scans) at network vantage points. Unfortunately, even today, many IDS systems we know of keep perconnection or perflow state to detect malicious TCP flows. Thus, it ..."
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Cited by 36 (1 self)
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Current intrusion detection and prevention systems seek to detect a wide class of network intrusions (e.g., DoS attacks, worms, port scans) at network vantage points. Unfortunately, even today, many IDS systems we know of keep perconnection or perflow state to detect malicious TCP flows. Thus, it is hardly surprising that these IDS systems have not scaled to multigigabit speeds. By contrast, both router lookups and fair queuing have scaled to high speeds using aggregation via prefix lookups or DiffServ. Thus, in this paper, we initiate research into the question as to whether one can detect attacks without keeping perflow state. We will show that such aggregation, while making fast implementations possible, immediately causes two problems. First, aggregation can cause behavioral aliasing where, for example, good behaviors can aggregate to look like bad behaviors. Second, aggregated schemes are susceptible to spoofing by which the intruder sends attacks that have appropriate aggregate behavior. We examine a wide variety of DoS and scanning attacks and show that several categories (bandwidth based, claimandhold, portscanning) can be scalably detected. In addition to existing approaches for scalable attack detection, we propose a novel data structure called partial completion filters (PCFs) that can detect claimandhold attacks scalably in the network. We analyze PCFs both analytically and using experiments on real network traces to demonstrate how we can tune PCFs to achieve extremely low false positive and false negative probabilities.
A Comparison of Approximate Interval Estimators for the Bernoulli Parameter
 The American Statistician
, 1996
"... We compare the accuracy of two approximate confidence interval estimators for the Bernoulli parameter p. The approximate confidence intervals are based on the normal and Poisson approximations to the binomial distribution. Charts are given to indicate which approximation is appropriate for certain s ..."
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Cited by 16 (3 self)
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We compare the accuracy of two approximate confidence interval estimators for the Bernoulli parameter p. The approximate confidence intervals are based on the normal and Poisson approximations to the binomial distribution. Charts are given to indicate which approximation is appropriate for certain sample sizes and point estimators.
FOKKERPLANCK APPROXIMATION OF THE MASTER EQUATION IN MOLECULAR BIOLOGY
, 2005
"... The master equation of chemical reactions is solved by first approximating it by the FokkerPlanck equation. Then this equation is discretized in the state space and time by a finite volume method. The difference between the solution of the master equation and the discretized FokkerPlanck equation ..."
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Cited by 15 (6 self)
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The master equation of chemical reactions is solved by first approximating it by the FokkerPlanck equation. Then this equation is discretized in the state space and time by a finite volume method. The difference between the solution of the master equation and the discretized FokkerPlanck equation is analyzed. The solution of the FokkerPlanck equation is compared to the solution of the master equation obtained with Gillespie’s Stochastic Simulation Algorithm (SSA) for problems of interest in the regulation of cell processes. The time dependent and steady state solutions are computed and for equal accuracy in the solutions, the FokkerPlanck approach is more efficient than SSA for low dimensional problems and high accuracy.
Statistical Techniques for Language Recognition: An Introduction and Guide for Cryptanalysts
 Cryptologia
, 1993
"... We explain how to apply statistical techniques to solve several languagerecognition problems that arise in cryptanalysis and other domains. Language recognition is important in cryptanalysis because, among other applications, an exhaustive key search of any cryptosystem from ciphertext alone requir ..."
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Cited by 11 (2 self)
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We explain how to apply statistical techniques to solve several languagerecognition problems that arise in cryptanalysis and other domains. Language recognition is important in cryptanalysis because, among other applications, an exhaustive key search of any cryptosystem from ciphertext alone requires a test that recognizes valid plaintext. Written for cryptanalysts, this guide should also be helpful to others as an introduction to statistical inference on Markov chains. Modeling language as a finite stationary Markov process, we adapt a statistical model of pattern recognition to language recognition. Within this framework we consider four welldefined languagerecognition problems: 1) recognizing a known language, 2) distinguishing a known language from uniform noise, 3) distinguishing unknown 0thorder noise from unknown 1storder language, and 4) detecting nonuniform unknown language. For the second problem we give a most powerful test based on the NeymanPearson Lemma. For the oth...
Spatial maps in frontal and prefrontal cortex
 Neuroimage
, 2006
"... Though the function of prefrontal cortex has been extensively investigated, little is known about the internal organization of individual prefrontal areas. Functional magnetic resonance imaging was used to show that some frontal and prefrontal cortical areas represent visual space in orderly, reprod ..."
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Cited by 10 (0 self)
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Though the function of prefrontal cortex has been extensively investigated, little is known about the internal organization of individual prefrontal areas. Functional magnetic resonance imaging was used to show that some frontal and prefrontal cortical areas represent visual space in orderly, reproducible, topographic maps. The mapcontaining areas partly overlap dorsolateral prefrontal areas engaged by working memory tasks. These maps may be useful for attending to taskrelevant objects at various spatial locations, an aspect of the executive control of attention. D 2005 Elsevier Inc. All rights reserved.
A Generalized Univariate ChangeofVariable Transformation Technique
, 1997
"... o appear in introductory probability and statistics texts. Casella and Berger [3; page 51] discuss transforming random variables using the changeofvariable technique when the entire transformation is manyto1, except for a finite number of points, that is, the cardinality of the set g \Gamma ..."
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Cited by 9 (4 self)
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o appear in introductory probability and statistics texts. Casella and Berger [3; page 51] discuss transforming random variables using the changeofvariable technique when the entire transformation is manyto1, except for a finite number of points, that is, the cardinality of the set g \Gamma1 (y) is the same for almost all y in the support of Y . Hogg and Craig [5; page 190] extend this manyto1 technique to ndimensional random variables. We are concerned with a more general univariate case in which the transformations are "piecewise manyto1," where "many" may vary based on the subinterval of the support of Y under consideration. We state and prove a theorem for this case and present code in a computer algebra system to implement the result. Although the theorem is a straightforward generalization of
The effects of education and farmer productivity in rural Ethiopia
, 1999
"... The Ethiopian education system is characterised by extremely low participation rates, particularly in rural areas. This paper challenges the hypothesis that demand for schooling in rural Ethiopia is constrained by the traditional nature of farm technology and lack of visible benefits of schooling i ..."
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Cited by 9 (0 self)
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The Ethiopian education system is characterised by extremely low participation rates, particularly in rural areas. This paper challenges the hypothesis that demand for schooling in rural Ethiopia is constrained by the traditional nature of farm technology and lack of visible benefits of schooling in terms of farmer productivity. The effects of schooling upon farmer productivity and efficiency are examined employing both average production functions and twostage stochastic frontier production functions. Data drawn from a large household survey conducted in 1994 were used to estimate internal and external benefits of schooling in 14 cerealproducing villages. Empirical analyses reveal substantial internal (private) benefits of schooling for farmer productivity, particularly in terms of efficiency gains. However, a threshold effect is identified: at least four years of primary schooling are required to have a significant effect upon farm productivity. Evidence of strong external (social) benefits of schooling was also uncovered, suggesting that there may be considerable opportunities to take advantage of external benefits of schooling in terms of increased farm productivity if school enrolments in rural areas are increased.
Designing workflow coordination: Centralized versus marketbased mechanisms
 Information Systems Research
, 1999
"... Due to the increasingly distributed nature of organizations, distributed scheduling methods have been proposed as alternatives to centralized, hierarchical, topdown production control schemes. While distributed scheduling methodologies are appealing, one must first address the fundamental questions ..."
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Cited by 6 (0 self)
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Due to the increasingly distributed nature of organizations, distributed scheduling methods have been proposed as alternatives to centralized, hierarchical, topdown production control schemes. While distributed scheduling methodologies are appealing, one must first address the fundamental questions of when and where such a method is appropriate. This paper seeks to provide an answer to these questions. Using a generalized workflow framework, this paper models and compares the total expected costs of using decentralized and centralized organizational designs to coordinate the flows of information and work. This comparison allows one to define the characterisitcs of work environments where distributed scheduling methods are more suitable than hierarchical, topdown production approaches. Finally, from this analysis, one can conclude that distributed scheduling methods work well for systems where information technology is inexpensive relative to production cost, processing times are relatively long, and where the number of agents in the system is not too large.
Input Modeling Using A Computer Algebra System
, 2000
"... Input modeling that involves fitting standard univariate parametric probability distributions is typically performed using an input modeling package. These packages typically fit several distributions to a data set, then determine the distribution with the best fit by comparing goodnessoffit stati ..."
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Cited by 5 (4 self)
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Input modeling that involves fitting standard univariate parametric probability distributions is typically performed using an input modeling package. These packages typically fit several distributions to a data set, then determine the distribution with the best fit by comparing goodnessoffit statistics. But what if an appropriate input model is not included in one of these packages? The modeler must resort to deriving the appropriate estimators by hand for the appropriate input model. The purpose of this paper is to investigate the use of a prototype Maplebased probability language, known as APPL (A Probability Programming Language), for input modeling. This language allows an analyst to specify a standard or nonstandard distribution for an input model, and have the derivations performed automatically. Input modeling serves as an excellent arena for illustrating the applicability and usefulness of APPL. Besides including predefined types for over 45 different continuous and discrete random variables and over 30 procedures for manipulating random variables (e.g., convolution, transformation), APPL contains input modeling procedures for parameter estimation, plotting empirical and fitted CDFs, and performing goodnessoffit tests. Using examples, we illustrate its utility for input modeling.