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Sampling Graphs with a Prescribed Joint Degree Distribution Using Markov Chains
"... One of the most influential results in network analysis is that many natural networks exhibit a powerlaw or lognormal degree distribution. This has inspired numerous generative models that match this property. However, more recent work has shown that while these generative models do have the right ..."
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Cited by 2 (0 self)
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the right degree distribution, they are not good models for real life networks due to their differences on other important metrics like conductance. We believe this is, in part, because many of these realworld networks have very different joint degree distributions, i.e. the probability that a randomly
A Constructing and Sampling Graphs with a Prescribed Joint Degree Distribution
"... One of the most influential recent results in network analysis is that many natural networks exhibit a powerlaw or lognormal degree distribution. This has inspired numerous generative models that match this property. However, more recent work has shown that while these generative models do have th ..."
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Cited by 13 (0 self)
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the right degree distribution, they are not good models for real life networks due to their differences on other important metrics like conductance. We believe this is, in part, because many of these realworld networks have very different joint degree distributions, i.e. the probability that a randomly
Distributed Database Systems
"... this article, we discuss the fundamentals of distributed DBMS technology. We address the data distribution and architectural design issues as well as the algorithms that need to be implemented to provide the basic DBMS functions such as query processing, concurrency control, reliability, and replica ..."
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Cited by 586 (26 self)
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this article, we discuss the fundamentals of distributed DBMS technology. We address the data distribution and architectural design issues as well as the algorithms that need to be implemented to provide the basic DBMS functions such as query processing, concurrency control, reliability
DISTRIBUTED SYSTEMS
, 1985
"... Growth of distributed systems has attained unstoppable momentum. If we better understood how to think about, analyze, and design distributed systems, we could direct their implementation with more confidence. ..."
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Cited by 755 (1 self)
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Growth of distributed systems has attained unstoppable momentum. If we better understood how to think about, analyze, and design distributed systems, we could direct their implementation with more confidence.
N Degrees of Separation: MultiDimensional Separation of Concerns
 IN PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING
, 1999
"... Done well, separation of concerns can provide many software engineering benefits, including reduced complexity, improved reusability, and simpler evolution. The choice of boundaries for separate concerns depends on both requirements on the system and on the kind(s) of decompositionand composition a ..."
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Cited by 514 (8 self)
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Done well, separation of concerns can provide many software engineering benefits, including reduced complexity, improved reusability, and simpler evolution. The choice of boundaries for separate concerns depends on both requirements on the system and on the kind(s) of decompositionand composition a given formalism supports. The predominant methodologies and formalisms available, however, support only orthogonal separations of concerns, along single dimensions of composition and decomposition. These characteristics lead to a number of wellknown and difficult problems. This paper describes a new paradigm for modeling and implementing software artifacts, one that permits separation of overlapping concerns along multiple dimensions of composition and decomposition. This approach addresses numerous problems throughout the software lifecycle in achieving wellengineered, evolvable, flexible software artifacts and traceability across artifacts.
Coda: A Highly Available File System for a Distributed Workstation Environment
 In IEEE Transactions on Computers
, 1990
"... Abstract Coda is a file system for a largescale distributed computing environment composed of Unix workstations. It provides resiliency to server and network failures through the use of two distinct but complementary mechanisms. One mechanism, server replication,stores copies of a file at multiple ..."
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Cited by 530 (46 self)
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, and strives to provide the highest degree of consistency attainable in the light of these objectives. Measurements from a prototype show that the performance cost of providing high availability in Coda is reasonable. Index Terms Andrew, availability, caching, disconnected operation, distributed file system
Scale and performance in a distributed file system
 ACM Transactions on Computer Systems
, 1988
"... The Andrew File System is a locationtransparent distributed tile system that will eventually span more than 5000 workstations at Carnegie Mellon University. Large scale affects performance and complicates system operation. In this paper we present observations of a prototype implementation, motivat ..."
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Cited by 937 (47 self)
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The Andrew File System is a locationtransparent distributed tile system that will eventually span more than 5000 workstations at Carnegie Mellon University. Large scale affects performance and complicates system operation. In this paper we present observations of a prototype implementation
A Critical Point For Random Graphs With A Given Degree Sequence
, 2000
"... Given a sequence of nonnegative real numbers 0 ; 1 ; : : : which sum to 1, we consider random graphs having approximately i n vertices of degree i. Essentially, we show that if P i(i \Gamma 2) i ? 0 then such graphs almost surely have a giant component, while if P i(i \Gamma 2) i ! 0 the ..."
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Cited by 511 (8 self)
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Given a sequence of nonnegative real numbers 0 ; 1 ; : : : which sum to 1, we consider random graphs having approximately i n vertices of degree i. Essentially, we show that if P i(i \Gamma 2) i ? 0 then such graphs almost surely have a giant component, while if P i(i \Gamma 2) i ! 0
The Amoeba Distributed Operating System
, 1992
"... INTRODUCTION Roughly speaking, we can divide the history of modern computing into the following eras: d 1970s: Timesharing (1 computer with many users) d 1980s: Personal computing (1 computer per user) d 1990s: Parallel computing (many computers per user) Until about 1980, computers were huge, e ..."
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Cited by 1070 (5 self)
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people's computers or share files in various (often ad hoc) ways. Nowadays some systems have many processors per user, either in the form of a parallel computer or a large collection of CPUs shared by a small user community. Such systems are usually called parallel or distributed computer systems
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